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Krrish Dholakia
Ishaan Jaffer
info

This is a pre-release version.

The production version will be released on Wednesday.

Deploy this version​

docker run litellm
docker run
-e STORE_MODEL_IN_DB=True
-p 4000:4000
ghcr.io/berriai/litellm:main-v1.72.6.rc

TLDR​

  • Why Upgrade
    • Codex-mini on Claude Code: You can now use codex-mini (OpenAI’s code assistant model) via Claude Code.
    • MCP Permissions Management: Manage permissions for MCP Servers by Keys, Teams, Organizations (entities) on LiteLLM.
    • UI: Turn on/off auto refresh on logs view.
    • Rate Limiting: Support for output token-only rate limiting.
  • Who Should Read
    • Teams using /v1/messages API (Claude Code)
    • Teams using MCP
    • Teams giving access to self-hosted models and setting rate limits
  • Risk of Upgrade
    • Low
      • No major changes to existing functionality or package updates.

Key Highlights​

MCP Permissions Management​

This release brings support for managing permissions for MCP Servers by Keys, Teams, Organizations (entities) on LiteLLM. When a MCP client attempts to list tools, LiteLLM will only return the tools the entity has permissions to access.

This is great for use cases that require access to restricted data (e.g Jira MCP) that you don't want everyone to use.

For Proxy Admins, this enables centralized management of all MCP Servers with access control. For developers, this means you'll only see the MCP tools assigned to you.

Codex-mini on Claude Code​

This release brings support for calling codex-mini (OpenAI’s code assistant model) via Claude Code.

This is done by LiteLLM enabling any Responses API model (including o3-pro) to be called via /chat/completions and /v1/messages endpoints. This includes:

  • Streaming calls
  • Non-streaming calls
  • Cost Tracking on success + failure for Responses API models

Here's how to use it today

New / Updated Models​

Pricing / Context Window Updates​

ProviderModelContext WindowInput ($/1M tokens)Output ($/1M tokens)Type
VertexAIvertex_ai/claude-opus-4200K$15.00$75.00New
OpenAIgpt-4o-audio-preview-2025-06-03128k$2.5 (text), $40 (audio)$10 (text), $80 (audio)New
OpenAIo3-pro200k2080New
OpenAIo3-pro-2025-06-10200k2080New
OpenAIo3200k28Updated
OpenAIo3-2025-04-16200k28Updated
Azureazure/gpt-4o-mini-transcribe16k1.25 (text), 3 (audio)5 (text)New
Mistralmistral/magistral-medium-latest40k25New
Mistralmistral/magistral-small-latest40k0.51.5New

Updated Models​

Bugs​

  • Watsonx
    • Ignore space id on Watsonx deployments (throws json errors) - PR
  • Ollama
    • Set tool call id for streaming calls - PR
  • Gemini (VertexAI + Google AI Studio)
    • Fix tool call indexes - PR
    • Handle empty string for arguments in function calls - PR
    • Add audio/ogg mime type support when inferring from file url’s - PR
  • Custom LLM
    • Fix passing api_base, api_key, litellm_params_dict to custom_llm embedding methods - PR s/o ElefHead
  • Huggingface
    • Add /chat/completions to endpoint url when missing - PR
  • Deepgram
    • Support async httpx calls - PR
  • Anthropic
    • Append prefix (if set) to assistant content start - PR

Features​

  • VertexAI
    • Support vertex credentials set via env var on passthrough - PR
    • Support for choosing ‘global’ region when model is only available there - PR
    • Anthropic passthrough cost calculation + token tracking - PR
    • Support ‘global’ vertex region on passthrough - PR
  • Anthropic
  • Perplexity
  • Mistral
  • SGLang
    • Map context window exceeded error for proper handling - PR
  • Deepgram
    • Provider specific params support - PR
  • Azure
    • Return content safety filter results - PR

LLM API Endpoints​

Bugs​

Features​

  • MCP
    • Add controls for MCP Permission Management - PR, Docs
    • Add permission management for MCP List + Call Tool operations - PR, Docs
    • Streamable HTTP server support - PR, PR, Docs
    • Use Experimental dedicated Rest endpoints for list, calling MCP tools - PR
  • Responses API
    • NEW API Endpoint - List input items - PR
    • Background mode for OpenAI + Azure OpenAI - PR
    • Langfuse/other Logging support on responses api requests - PR
  • Chat Completions
    • Bridge for Responses API - allows calling codex-mini via /chat/completions and /v1/messages - PR, PR

Spend Tracking​

Bugs​

Management Endpoints / UI​

Bugs​

  • Users
    • /user/info - fix passing user with + in user id
    • Add admin-initiated password reset flow - PR
    • Fixes default user settings UI rendering error - PR
  • Budgets
    • Correct success message when new user budget is created - PR

Features​

  • Leftnav
    • Show remaining Enterprise users on UI
  • MCP
    • New server add form - PR
    • Allow editing mcp servers - PR
  • Models
    • Add deepgram models on UI
    • Model Access Group support on UI - PR
  • Keys
    • Trim long user id’s - PR
  • Logs
    • Add live tail feature to logs view, allows user to disable auto refresh in high traffic - PR
    • Audit Logs - preview screenshot - PR

Logging / Guardrails Integrations​

Bugs​

Features​

  • Lasso Guardrails
    • [NEW] Lasso Guardrails support - PR
  • Users
    • New organizations param on /user/new - allows adding users to orgs on creation - PR
  • Prevent double logging when using bridge logic - PR

Performance / Reliability Improvements​

Bugs​

Features​

  • Caching
    • New optional ‘litellm[caching]’ pip install for adding disk cache dependencies - PR

General Proxy Improvements​

Bugs​

  • aiohttp
    • fixes for transfer encoding error on aiohttp transport - PR

Features​

  • aiohttp
    • Enable System Proxy Support for aiohttp transport - PR (s/o idootop)
  • CLI
    • Make all commands show server URL - PR
  • Unicorn
    • Allow setting keep alive timeout - PR
  • Experimental Rate Limiting v2 (enable via EXPERIMENTAL_MULTI_INSTANCE_RATE_LIMITING="True")
    • Support specifying rate limit by output_tokens only - PR
    • Decrement parallel requests on call failure - PR
    • In-memory only rate limiting support - PR
    • Return remaining rate limits by key/user/team - PR
  • Helm
    • support extraContainers in migrations-job.yaml - PR

New Contributors​

Demo Instance​

Here's a Demo Instance to test changes:

Git Diff​

Krrish Dholakia
Ishaan Jaffer

Deploy this version​

docker run litellm
docker run
-e STORE_MODEL_IN_DB=True
-p 4000:4000
ghcr.io/berriai/litellm:main-v1.72.2-stable

TLDR​

  • Why Upgrade
    • Performance Improvements for /v1/messages: For this endpoint LiteLLM Proxy overhead is now down to 50ms at 250 RPS.
    • Accurate Rate Limiting: Multi-instance rate limiting now tracks rate limits across keys, models, teams, and users with 0 spillover.
    • Audit Logs on UI: Track when Keys, Teams, and Models were deleted by viewing Audit Logs on the LiteLLM UI.
    • /v1/messages all models support: You can now use all LiteLLM models (gpt-4.1, o1-pro, gemini-2.5-pro) with /v1/messages API.
    • Anthropic MCP: Use remote MCP Servers with Anthropic Models.
  • Who Should Read
    • Teams using /v1/messages API (Claude Code)
    • Proxy Admins using LiteLLM Virtual Keys and setting rate limits
  • Risk of Upgrade
    • Medium
      • Upgraded ddtrace==3.8.0, if you use DataDog tracing this is a medium level risk. We recommend monitoring logs for any issues.

/v1/messages Performance Improvements​

This release brings significant performance improvements to the /v1/messages API on LiteLLM.

For this endpoint LiteLLM Proxy overhead latency is now down to 50ms, and each instance can handle 250 RPS. We validated these improvements through load testing with payloads containing over 1,000 streaming chunks.

This is great for real time use cases with large requests (eg. multi turn conversations, Claude Code, etc.).

Multi-Instance Rate Limiting Improvements​

LiteLLM now accurately tracks rate limits across keys, models, teams, and users with 0 spillover.

This is a significant improvement over the previous version, which faced issues with leakage and spillover in high traffic, multi-instance setups.

Key Changes:

  • Redis is now part of the rate limit check, instead of being a background sync. This ensures accuracy and reduces read/write operations during low activity.
  • LiteLLM now uses Lua scripts to ensure all checks are atomic.
  • In-memory caching uses Redis values. This prevents drift, and reduces Redis queries once objects are over their limit.

These changes are currently behind the feature flag - EXPERIMENTAL_ENABLE_MULTI_INSTANCE_RATE_LIMITING=True. We plan to GA this in our next release - subject to feedback.

Audit Logs on UI​

This release introduces support for viewing audit logs in the UI. As a Proxy Admin, you can now check if and when a key was deleted, along with who performed the action.

LiteLLM tracks changes to the following entities and actions:

  • Entities: Keys, Teams, Users, Models
  • Actions: Create, Update, Delete, Regenerate

New Models / Updated Models​

Newly Added Models

ProviderModelContext WindowInput ($/1M tokens)Output ($/1M tokens)
Anthropicclaude-4-opus-20250514200K$15.00$75.00
Anthropicclaude-4-sonnet-20250514200K$3.00$15.00
VertexAI, Google AI Studiogemini-2.5-pro-preview-06-051M$1.25$10.00
OpenAIcodex-mini-latest200K$1.50$6.00
Cerebrasqwen-3-32b128K$0.40$0.80
SambaNovaDeepSeek-R132K$5.00$7.00
SambaNovaDeepSeek-R1-Distill-Llama-70B131K$0.70$1.40

Model Updates​

  • Anthropic
    • Cost tracking added for new Claude models - PR
      • claude-4-opus-20250514
      • claude-4-sonnet-20250514
    • Support for MCP tool calling with Anthropic models - PR
  • Google AI Studio
    • Google Gemini 2.5 Pro Preview 06-05 support - PR
    • Gemini streaming thinking content parsing with reasoning_content - PR
    • Support for no reasoning option for Gemini models - PR
    • URL context support for Gemini models - PR
    • Gemini embeddings-001 model prices and context window - PR
  • OpenAI
    • Cost tracking for codex-mini-latest - PR
  • Vertex AI
    • Cache token tracking on streaming calls - PR
    • Return response_id matching upstream response ID for stream and non-stream - PR
  • Cerebras
    • Cerebras/qwen-3-32b model pricing and context window - PR
  • HuggingFace
    • Fixed embeddings using non-default input_type - PR
  • DataRobot
    • New provider integration for enterprise AI workflows - PR
  • DeepSeek
    • DeepSeek R1 family model configuration via Together AI - PR
    • DeepSeek R1 pricing and context window configuration - PR

LLM API Endpoints​

  • Images API
    • Azure endpoint support for image endpoints - PR
  • Anthropic Messages API
    • Support for ALL LiteLLM Providers (OpenAI, Azure, Bedrock, Vertex, DeepSeek, etc.) on /v1/messages API Spec - PR
    • Performance improvements for /v1/messages route - PR
    • Return streaming usage statistics when using LiteLLM with Bedrock models - PR
  • Embeddings API
    • Provider-specific optional params handling for embedding calls - PR
    • Proper Sagemaker request attribute usage for embeddings - PR
  • Rerank API
    • New HuggingFace rerank provider support - PR, Guide

Spend Tracking​

  • Added token tracking for anthropic batch calls via /anthropic passthrough route- PR

Management Endpoints / UI​

  • SSO/Authentication
    • SSO configuration endpoints and UI integration with persistent settings - PR
    • Update proxy admin ID role in DB + Handle SSO redirects with custom root path - PR
    • Support returning virtual key in custom auth - PR
    • User ID validation to ensure it is not an email or phone number - PR
  • Teams
    • Fixed Create/Update team member API 500 error - PR
    • Enterprise feature gating for RegenerateKeyModal in KeyInfoView - PR
  • SCIM
    • Fixed SCIM running patch operation case sensitivity - PR
  • General
    • Converted action buttons to sticky footer action buttons - PR
    • Custom Server Root Path - support for serving UI on a custom root path - Guide

Logging / Guardrails Integrations​

Logging​

  • S3
    • Async + Batched S3 Logging for improved performance - PR
  • DataDog
    • Add instrumentation for streaming chunks - PR
    • Add DD profiler to monitor Python profile of LiteLLM CPU% - PR
    • Bump DD trace version - PR
  • Prometheus
    • Pass custom metadata labels in litellm_total_token metrics - PR
  • GCS
    • Update GCSBucketBase to handle GSM project ID if passed - PR

Guardrails​

  • Presidio
    • Add presidio_language yaml configuration support for guardrails - PR

Performance / Reliability Improvements​

  • Performance Optimizations
    • Don't run auth on /health/liveliness endpoints - PR
    • Don't create 1 task for every hanging request alert - PR
    • Add debugging endpoint to track active /asyncio-tasks - PR
    • Make batch size for maximum retention in spend logs controllable - PR
    • Expose flag to disable token counter - PR
    • Support pipeline redis lpop for older redis versions - PR

Bug Fixes​

  • LLM API Fixes
    • Anthropic: Fix regression when passing file url's to the 'file_id' parameter - PR
    • Vertex AI: Fix Vertex AI any_of issues for Description and Default. - PR
    • Fix transcription model name mapping - PR
    • Image Generation: Fix None values in usage field for gpt-image-1 model responses - PR
    • Responses API: Fix _transform_responses_api_content_to_chat_completion_content doesn't support file content type - PR
    • Fireworks AI: Fix rate limit exception mapping - detect "rate limit" text in error messages - PR
  • Spend Tracking/Budgets
    • Respect user_header_name property for budget selection and user identification - PR
  • MCP Server
    • Remove duplicate server_id MCP config servers - PR
  • Function Calling
    • supports_function_calling works with llm_proxy models - PR
  • Knowledge Base
    • Fixed Knowledge Base Call returning error - PR

New Contributors​

Demo Instance​

Here's a Demo Instance to test changes:

Git Diff​

Krrish Dholakia
Ishaan Jaffer

Deploy this version​

docker run litellm
docker run
-e STORE_MODEL_IN_DB=True
-p 4000:4000
ghcr.io/berriai/litellm:main-v1.72.0-stable

Key Highlights​

LiteLLM v1.72.0-stable.rc is live now. Here are the key highlights of this release:

  • Vector Store Permissions: Control Vector Store access at the Key, Team, and Organization level.
  • Rate Limiting Sliding Window support: Improved accuracy for Key/Team/User rate limits with request tracking across minutes.
  • Aiohttp Transport used by default: Aiohttp transport is now the default transport for LiteLLM networking requests. This gives users 2x higher RPS per instance with a 40ms median latency overhead.
  • Bedrock Agents: Call Bedrock Agents with /chat/completions, /response endpoints.
  • Anthropic File API: Upload and analyze CSV files with Claude-4 on Anthropic via LiteLLM.
  • Prometheus: End users (end_user) will no longer be tracked by default on Prometheus. Tracking end_users on prometheus is now opt-in. This is done to prevent the response from /metrics from becoming too large. Read More

Vector Store Permissions​

This release brings support for managing permissions for vector stores by Keys, Teams, Organizations (entities) on LiteLLM. When a request attempts to query a vector store, LiteLLM will block it if the requesting entity lacks the proper permissions.

This is great for use cases that require access to restricted data that you don't want everyone to use.

Over the next week we plan on adding permission management for MCP Servers.

Aiohttp Transport used by default​

Aiohttp transport is now the default transport for LiteLLM networking requests. This gives users 2x higher RPS per instance with a 40ms median latency overhead. This has been live on LiteLLM Cloud for a week + gone through alpha users testing for a week.

If you encounter any issues, you can disable using the aiohttp transport in the following ways:

On LiteLLM Proxy

Set the DISABLE_AIOHTTP_TRANSPORT=True in the environment variables.

Environment Variable
export DISABLE_AIOHTTP_TRANSPORT="True"

On LiteLLM Python SDK

Set the disable_aiohttp_transport=True to disable aiohttp transport.

Python SDK
import litellm

litellm.disable_aiohttp_transport = True # default is False, enable this to disable aiohttp transport
result = litellm.completion(
    model="openai/gpt-4o",
    messages=[{"role": "user", "content": "Hello, world!"}],
)
print(result)

New Models / Updated Models​

  • Bedrock
    • Video support for Bedrock Converse - PR
    • InvokeAgents support as /chat/completions route - PR, Get Started
    • AI21 Jamba models compatibility fixes - PR
    • Fixed duplicate maxTokens parameter for Claude with thinking - PR
  • Gemini (Google AI Studio + Vertex AI)
    • Parallel tool calling support with parallel_tool_calls parameter - PR
    • All Gemini models now support parallel function calling - PR
  • VertexAI
    • codeExecution tool support and anyOf handling - PR
    • Vertex AI Anthropic support on /v1/messages - PR
    • Thinking, global regions, and parallel tool calling improvements - PR
    • Web Search Support PR
  • Anthropic
    • Thinking blocks on streaming support - PR
    • Files API with form-data support on passthrough - PR
    • File ID support on /chat/completion - PR
  • xAI
    • Web Search Support PR
  • Google AI Studio
    • Web Search Support PR
  • Mistral
    • Updated mistral-medium prices and context sizes - PR
  • Ollama
    • Tool calls parsing on streaming - PR
  • Cohere
    • Swapped Cohere and Cohere Chat provider positioning - PR
  • Nebius AI Studio
    • New provider integration - PR

LLM API Endpoints​

Management Endpoints / UI​

  • Vector Stores
    • Permission management for LiteLLM Keys, Teams, and Organizations - PR
    • UI display of vector store permissions - PR
    • Vector store access controls enforcement - PR
    • Object permissions fixes and QA improvements - PR
  • Teams
    • "All proxy models" display when no models selected - PR
    • Removed redundant teamInfo call, using existing teamsList - PR
    • Improved model tags display on Keys, Teams and Org pages - PR
  • SSO/SCIM
    • Bug fixes for showing SCIM token on UI - PR
  • General UI
    • Fix "UI Session Expired. Logging out" - PR
    • Support for forwarding /sso/key/generate to server root path URL - PR

Logging / Guardrails Integrations​

Logging​

  • Prometheus
    • End users will no longer be tracked by default on Prometheus. Tracking end_users on prometheus is now opt-in. PR
  • Langfuse
    • Performance improvements: Fixed "Max langfuse clients reached" issue - PR
  • Helicone
    • Base URL support - PR
  • Sentry
    • Added sentry sample rate configuration - PR

Guardrails​

Performance / Reliability Improvements​

  • aiohttp Transport
    • Handling for aiohttp.ClientPayloadError - PR
    • SSL verification settings support - PR
    • Rollback to httpx==0.27.0 for stability - PR
  • Request Limiting
    • Sliding window logic for parallel request limiter v2 - PR

Bug Fixes​

  • LLM API Fixes
    • Added missing request_kwargs to get_available_deployment call - PR
    • Fixed calling Azure O-series models - PR
    • Support for dropping non-OpenAI params via additional_drop_params - PR
    • Fixed frequency_penalty to repeat_penalty parameter mapping - PR
    • Fix for embedding cache hits on string input - PR
  • General
    • OIDC provider improvements and audience bug fix - PR
    • Removed AzureCredentialType restriction on AZURE_CREDENTIAL - PR
    • Prevention of sensitive key leakage to Langfuse - PR
    • Fixed healthcheck test using curl when curl not in image - PR

New Contributors​

Demo Instance​

Here's a Demo Instance to test changes:

Git Diff​

Krrish Dholakia
Ishaan Jaffer

Deploy this version​

docker run litellm
docker run
-e STORE_MODEL_IN_DB=True
-p 4000:4000
ghcr.io/berriai/litellm:main-v1.71.1-stable

Key Highlights​

LiteLLM v1.71.1-stable is live now. Here are the key highlights of this release:

  • Performance improvements: LiteLLM can now scale to 200 RPS per instance with a 74ms median response time.
  • File Permissions: Control file access across OpenAI, Azure, VertexAI.
  • MCP x OpenAI: Use MCP servers with OpenAI Responses API.

Performance Improvements​


This release brings aiohttp support for all LLM api providers. This means that LiteLLM can now scale to 200 RPS per instance with a 40ms median latency overhead.

This change doubles the RPS LiteLLM can scale to at this latency overhead.

You can opt into this by enabling the flag below. (We expect to make this the default in 1 week.)

Flag to enable​

On LiteLLM Proxy

Set the USE_AIOHTTP_TRANSPORT=True in the environment variables.

Environment Variable
export USE_AIOHTTP_TRANSPORT="True"

On LiteLLM Python SDK

Set the use_aiohttp_transport=True to enable aiohttp transport.

Python SDK
import litellm

litellm.use_aiohttp_transport = True # default is False, enable this to use aiohttp transport
result = litellm.completion(
    model="openai/gpt-4o",
    messages=[{"role": "user", "content": "Hello, world!"}],
)
print(result)

File Permissions​


This release brings support for File Permissions and Finetuning APIs to LiteLLM Managed Files. This is great for:

  • Proxy Admins: as users can only view/edit/delete files they’ve created - even when using shared OpenAI/Azure/Vertex deployments.
  • Developers: get a standard interface to use Files across Chat/Finetuning/Batch APIs.

New Models / Updated Models​

  • Gemini VertexAI, Google AI Studio
    • New gemini models - PR 1, PR 2
      • gemini-2.5-flash-preview-tts
      • gemini-2.0-flash-preview-image-generation
      • gemini/gemini-2.5-flash-preview-05-20
      • gemini-2.5-flash-preview-05-20
  • Anthropic
    • Claude-4 model family support - PR
  • Bedrock
    • Claude-4 model family support - PR
    • Support for reasoning_effort and thinking parameters for Claude-4 - PR
  • VertexAI
    • Claude-4 model family support - PR
    • Global endpoints support - PR
    • authorized_user credentials type support - PR
  • xAI
    • xai/grok-3 pricing information - PR
  • LM Studio
    • Structured JSON schema outputs support - PR
  • SambaNova
    • Updated models and parameters - PR
  • Databricks
    • Llama 4 Maverick model cost - PR
    • Claude 3.7 Sonnet output token cost correction - PR
  • Azure
    • Mistral Medium 25.05 support - PR
    • Certificate-based authentication support - PR
  • Mistral
    • devstral-small-2505 model pricing and context window - PR
  • Ollama
    • Wildcard model support - PR
  • CustomLLM
    • Embeddings support added - PR
  • Featherless AI
    • Access to 4200+ models - PR

LLM API Endpoints​

  • Image Edits
    • /v1/images/edits - Support for /images/edits endpoint - PR PR
    • Content policy violation error mapping - PR
  • Responses API
    • MCP support for Responses API - PR
  • Files API
    • LiteLLM Managed Files support for finetuning - PR PR
    • Validation for file operations (retrieve/list/delete) - PR

Management Endpoints / UI​

  • Teams
    • Key and member count display - PR
    • Spend rounded to 4 decimal points - PR
    • Organization and team create buttons repositioned - PR
  • Keys
    • Key reassignment and 'updated at' column - PR
    • Show model access groups during creation - PR
  • Logs
    • Model filter on logs - PR
    • Passthrough endpoint error logs support - PR
  • Guardrails
    • Config.yaml guardrails display - PR
  • Organizations/Users
    • Spend rounded to 4 decimal points - PR
    • Show clear error when adding a user to a team - PR
  • Audit Logs
    • /list and /info endpoints for Audit Logs - PR

Logging / Alerting Integrations​

Authentication & Security​

  • JWT Authentication
    • Support for applying default internal user parameters when upserting a user via JWT authentication - PR
    • Map a user to a team when upserting a user via JWT authentication - PR
  • Custom Auth
    • Support for switching between custom auth and API key auth - PR

Performance / Reliability Improvements​

  • aiohttp Transport
    • 97% lower median latency (feature flagged) - PR PR
  • Background Health Checks
    • Improved reliability - PR
  • Response Handling
    • Better streaming status code detection - PR
    • Response ID propagation improvements - PR
  • Thread Management
    • Removed error-creating threads for reliability - PR

General Proxy Improvements​

  • Proxy CLI
    • Skip server startup flag - PR
    • Avoid DATABASE_URL override when provided - PR
  • Model Management
    • Clear cache and reload after model updates - PR
    • Computer use support tracking - PR
  • Helm Chart
    • LoadBalancer class support - PR

Bug Fixes​

This release includes numerous bug fixes to improve stability and reliability:

  • LLM Provider Fixes

    • VertexAI:
      • Fixed quota_project_id parameter issue - PR
      • Fixed credential refresh exceptions - PR
    • Cohere: Fixes for adding Cohere models through LiteLLM UI - PR
    • Anthropic:
      • Fixed streaming dict object handling for /v1/messages - PR
    • OpenRouter:
      • Fixed stream usage ID issues - PR

  • Authentication & Users

    • Fixed invitation email link generation - PR
    • Fixed JWT authentication default role - PR
    • Fixed user budget reset functionality - PR
    • Fixed SSO user compatibility and email validation - PR

  • Database & Infrastructure

    • Fixed DB connection parameter handling - PR
    • Fixed email invitation link - PR

  • UI & Display

    • Fixed MCP tool rendering when no arguments required - PR
    • Fixed team model alias deletion - PR
    • Fixed team viewer permissions - PR

  • Model & Routing

    • Fixed team model mapping in route requests - PR
    • Fixed standard optional parameter passing - PR

New Contributors​

Demo Instance​

Here's a Demo Instance to test changes:

Git Diff​

Krrish Dholakia
Ishaan Jaffer

Deploy this version​

docker run litellm
docker run
-e STORE_MODEL_IN_DB=True
-p 4000:4000
ghcr.io/berriai/litellm:main-v1.70.1-stable

Key Highlights​

LiteLLM v1.70.1-stable is live now. Here are the key highlights of this release:

  • Gemini Realtime API: You can now call Gemini's Live API via the OpenAI /v1/realtime API
  • Spend Logs Retention Period: Enable deleting spend logs older than a certain period.
  • PII Masking 2.0: Easily configure masking or blocking specific PII/PHI entities on the UI

Gemini Realtime API​

This release brings support for calling Gemini's realtime models (e.g. gemini-2.0-flash-live) via OpenAI's /v1/realtime API. This is great for developers as it lets them easily switch from OpenAI to Gemini by just changing the model name.

Key Highlights:

  • Support for text + audio input/output
  • Support for setting session configurations (modality, instructions, activity detection) in the OpenAI format
  • Support for logging + usage tracking for realtime sessions

This is currently supported via Google AI Studio. We plan to release VertexAI support over the coming week.

Read more

Spend Logs Retention Period​

This release enables deleting LiteLLM Spend Logs older than a certain period. Since we now enable storing the raw request/response in the logs, deleting old logs ensures the database remains performant in production.

Read more

PII Masking 2.0​

This release brings improvements to our Presidio PII Integration. As a Proxy Admin, you now have the ability to:

  • Mask or block specific entities (e.g., block medical licenses while masking other entities like emails).
  • Monitor guardrails in production. LiteLLM Logs will now show you the guardrail run, the entities it detected, and its confidence score for each entity.

Read more

New Models / Updated Models​

  • Gemini (VertexAI + Google AI Studio)
    • /chat/completion
      • Handle audio input - PR
      • Fixes maximum recursion depth issue when using deeply nested response schemas with Vertex AI by Increasing DEFAULT_MAX_RECURSE_DEPTH from 10 to 100 in constants. PR
      • Capture reasoning tokens in streaming mode - PR
  • Google AI Studio
    • /realtime
      • Gemini Multimodal Live API support
      • Audio input/output support, optional param mapping, accurate usage calculation - PR
  • VertexAI
    • /chat/completion
      • Fix llama streaming error - where model response was nested in returned streaming chunk - PR
  • Ollama
    • /chat/completion
      • structure responses fix - PR
  • Bedrock
    • /chat/completion
      • Handle thinking_blocks when assistant.content is None - PR
      • Fixes to only allow accepted fields for tool json schema - PR
      • Add bedrock sonnet prompt caching cost information
      • Mistral Pixtral support - PR
      • Tool caching support - PR
    • /messages
      • allow using dynamic AWS Params - PR
  • Nvidia NIM
  • Novita AI
    • New Provider added for /chat/completion routes - PR
  • Azure
  • Cohere
    • /embeddings
      • Migrate embedding to use /v2/embed - adds support for output_dimensions param - PR
  • Anthropic
  • VLLM
  • OpenAI

LLM API Endpoints​

  • Responses API
    • Fix delete API support - PR
  • Rerank API
    • /v2/rerank now registered as ‘llm_api_route’ - enabling non-admins to call it - PR

Spend Tracking Improvements​

  • /chat/completion, /messages
    • Anthropic - web search tool cost tracking - PR
    • Groq - update model max tokens + cost information - PR
  • /audio/transcription
    • Azure - Add gpt-4o-mini-tts pricing - PR
    • Proxy - Fix tracking spend by tag - PR
  • /embeddings
    • Azure AI - Add cohere embed v4 pricing - PR

Management Endpoints / UI​

Logging / Alerting Integrations​

Guardrails​

  • Guardrails
    • New /apply_guardrail endpoint for directly testing a guardrail - PR
  • Lakera
    • /v2 endpoints support - PR
  • Presidio
    • Fixes handling of message content on presidio guardrail integration - PR
    • Allow specifying PII Entities Config - PR
  • Aim Security
    • Support for anonymization in AIM Guardrails - PR

Performance / Loadbalancing / Reliability improvements​

General Proxy Improvements​

  • Authentication
    • Handle Bearer $LITELLM_API_KEY in x-litellm-api-key custom header PR
  • New Enterprise pip package - litellm-enterprise - fixes issue where enterprise folder was not found when using pip package
  • Proxy CLI
    • Add models import command - PR
  • OpenWebUI
    • Configure LiteLLM to Parse User Headers from Open Web UI
  • LiteLLM Proxy w/ LiteLLM SDK
    • Option to force/always use the litellm proxy when calling via LiteLLM SDK

New Contributors​

Demo Instance​

Here's a Demo Instance to test changes:

Git Diff​

Krrish Dholakia
Ishaan Jaffer

Deploy this version​

docker run litellm
docker run
-e STORE_MODEL_IN_DB=True
-p 4000:4000
ghcr.io/berriai/litellm:main-v1.69.0-stable

Key Highlights​

LiteLLM v1.69.0-stable brings the following key improvements:

  • Loadbalance Batch API Models: Easily loadbalance across multiple azure batch deployments using LiteLLM Managed Files
  • Email Invites 2.0: Send new users onboarded to LiteLLM an email invite.
  • Nscale: LLM API for compliance with European regulations.
  • Bedrock /v1/messages: Use Bedrock Anthropic models with Anthropic's /v1/messages.

Batch API Load Balancing​

This release brings LiteLLM Managed File support to Batches. This is great for:

  • Proxy Admins: You can now control which Batch models users can call.
  • Developers: You no longer need to know the Azure deployment name when creating your batch .jsonl files - just specify the model your LiteLLM key has access to.

Over time, we expect LiteLLM Managed Files to be the way most teams use Files across /chat/completions, /batch, /fine_tuning endpoints.

Read more here

Email Invites​

This release brings the following improvements to our email invite integration:

  • New templates for user invited and key created events.
  • Fixes for using SMTP email providers.
  • Native support for Resend API.
  • Ability for Proxy Admins to control email events.

For LiteLLM Cloud Users, please reach out to us if you want this enabled for your instance.

Read more here

New Models / Updated Models​

  • Gemini (VertexAI + Google AI Studio)
    • Added gemini-2.5-pro-preview-05-06 models with pricing and context window info - PR
    • Set correct context window length for all Gemini 2.5 variants - PR
  • Perplexity:
    • Added new Perplexity models - PR
    • Added sonar-deep-research model pricing - PR
  • Azure OpenAI:
    • Fixed passing through of azure_ad_token_provider parameter - PR
  • OpenAI:
    • Added support for pdf url's in 'file' parameter - PR
  • Sagemaker:
    • Fix content length for sagemaker_chat provider - PR
  • Azure AI Foundry:
    • Added cost tracking for the following models PR
      • DeepSeek V3 0324
      • Llama 4 Scout
      • Llama 4 Maverick
  • Bedrock:
    • Added cost tracking for Bedrock Llama 4 models - PR
    • Fixed template conversion for Llama 4 models in Bedrock - PR
    • Added support for using Bedrock Anthropic models with /v1/messages format - PR
    • Added streaming support for Bedrock Anthropic models with /v1/messages format - PR
  • OpenAI: Added reasoning_effort support for o3 models - PR
  • Databricks:
    • Fixed issue when Databricks uses external model and delta could be empty - PR
  • Cerebras: Fixed Llama-3.1-70b model pricing and context window - PR
  • Ollama:
    • Fixed custom price cost tracking and added 'max_completion_token' support - PR
    • Fixed KeyError when using JSON response format - PR
  • 🆕 Nscale:
    • Added support for chat, image generation endpoints - PR

LLM API Endpoints​

  • Messages API:
    • 🆕 Added support for using Bedrock Anthropic models with /v1/messages format - PR and streaming support - PR
  • Moderations API:
    • Fixed bug to allow using LiteLLM UI credentials for /moderations API - PR
  • Realtime API:
    • Fixed setting 'headers' in scope for websocket auth requests and infinite loop issues - PR
  • Files API:
    • Unified File ID output support - PR
    • Support for writing files to all deployments - PR
    • Added target model name validation - PR
  • Batches API:
    • Complete unified batch ID support - replacing model in jsonl to be deployment model name - PR
    • Beta support for unified file ID (managed files) for batches - PR

Spend Tracking / Budget Improvements​

  • Bug Fix - PostgreSQL Integer Overflow Error in DB Spend Tracking - PR

Management Endpoints / UI​

  • Models
    • Fixed model info overwriting when editing a model on UI - PR
    • Fixed team admin model updates and organization creation with specific models - PR
  • Logs:
    • Bug Fix - copying Request/Response on Logs Page - PR
    • Bug Fix - log did not remain in focus on QA Logs page + text overflow on error logs - PR
    • Added index for session_id on LiteLLM_SpendLogs for better query performance - PR
  • User Management:
    • Added user management functionality to Python client library & CLI - PR
    • Bug Fix - Fixed SCIM token creation on Admin UI - PR
    • Bug Fix - Added 404 response when trying to delete verification tokens that don't exist - PR

Logging / Guardrail Integrations​

  • Custom Logger API: v2 Custom Callback API (send llm logs to custom api) - PR, Get Started
  • OpenTelemetry:
    • Fixed OpenTelemetry to follow genai semantic conventions + support for 'instructions' param for TTS - PR
  • Bedrock PII:
    • Add support for PII Masking with bedrock guardrails - Get Started, PR
  • Documentation:
    • Added documentation for StandardLoggingVectorStoreRequest - PR

Performance / Reliability Improvements​

  • Python Compatibility:
    • Added support for Python 3.11- (fixed datetime UTC handling) - PR
    • Fixed UnicodeDecodeError: 'charmap' on Windows during litellm import - PR
  • Caching:
    • Fixed embedding string caching result - PR
    • Fixed cache miss for Gemini models with response_format - PR

General Proxy Improvements​

  • Proxy CLI:
    • Added --version flag to litellm-proxy CLI - PR
    • Added dedicated litellm-proxy CLI - PR
  • Alerting:
    • Fixed Slack alerting not working when using a DB - PR
  • Email Invites:
    • Added V2 Emails with fixes for sending emails when creating keys + Resend API support - PR
    • Added user invitation emails - PR
    • Added endpoints to manage email settings - PR
  • General:
    • Fixed bug where duplicate JSON logs were getting emitted - PR

New Contributors​

Krrish Dholakia
Ishaan Jaffer

Deploy this version​

docker run litellm
docker run
-e STORE_MODEL_IN_DB=True
-p 4000:4000
ghcr.io/berriai/litellm:main-v1.68.0-stable

Key Highlights​

LiteLLM v1.68.0-stable will be live soon. Here are the key highlights of this release:

  • Bedrock Knowledge Base: You can now call query your Bedrock Knowledge Base with all LiteLLM models via /chat/completion or /responses API.
  • Rate Limits: This release brings accurate rate limiting across multiple instances, reducing spillover to at most 10 additional requests in high traffic.
  • Meta Llama API: Added support for Meta Llama API Get Started
  • LlamaFile: Added support for LlamaFile Get Started

Bedrock Knowledge Base (Vector Store)​


This release adds support for Bedrock vector stores (knowledge bases) in LiteLLM. With this update, you can:

  • Use Bedrock vector stores in the OpenAI /chat/completions spec with all LiteLLM supported models.
  • View all available vector stores through the LiteLLM UI or API.
  • Configure vector stores to be always active for specific models.
  • Track vector store usage in LiteLLM Logs.

For the next release we plan on allowing you to set key, user, team, org permissions for vector stores.

Read more here

Rate Limiting​


This release brings accurate multi-instance rate limiting across keys/users/teams. Outlining key engineering changes below:

  • Change: Instances now increment cache value instead of setting it. To avoid calling Redis on each request, this is synced every 0.01s.
  • Accuracy: In testing, we saw a maximum spill over from expected of 10 requests, in high traffic (100 RPS, 3 instances), vs. current 189 request spillover
  • Performance: Our load tests show this to reduce median response time by 100ms in high traffic 

This is currently behind a feature flag, and we plan to have this be the default by next week. To enable this today, just add this environment variable:

export LITELLM_RATE_LIMIT_ACCURACY=true

Read more here

New Models / Updated Models​

  • Gemini (VertexAI + Google AI Studio)
    • Handle more json schema - openapi schema conversion edge cases PR
    • Tool calls - return ‘finish_reason=“tool_calls”’ on gemini tool calling response PR
  • VertexAI
    • Meta/llama-4 model support PR
    • Meta/llama3 - handle tool call result in content PR
    • Meta/* - return ‘finish_reason=“tool_calls”’ on tool calling response PR
  • Bedrock
  • OpenAI
    • Support OPENAI_BASE_URL in addition to OPENAI_API_BASE PR
    • Correctly re-raise 504 timeout errors PR
    • Native Gpt-4o-mini-tts support PR
  • 🆕 Meta Llama API provider PR
  • 🆕 LlamaFile provider PR

LLM API Endpoints​

  • Response API
    • Fix for handling multi turn sessions PR
  • Embeddings
    • Caching fixes - PR
      • handle str -> list cache
      • Return usage tokens for cache hit
      • Combine usage tokens on partial cache hits
  • 🆕 Vector Stores
    • Allow defining Vector Store Configs - PR
    • New StandardLoggingPayload field for requests made when a vector store is used - PR
    • Show Vector Store / KB Request on LiteLLM Logs Page - PR
    • Allow using vector store in OpenAI API spec with tools - PR
  • MCP

    • Ensure Non-Admin virtual keys can access /mcp routes - PR

      Note: Currently, all Virtual Keys are able to access the MCP endpoints. We are working on a feature to allow restricting MCP access by keys/teams/users/orgs. Follow here for updates.

  • Moderations
    • Add logging callback support for /moderations API - PR

Spend Tracking / Budget Improvements​

Management Endpoints / UI​

  • Virtual Keys
    • Fix filtering on key alias - PR
    • Support global filtering on keys - PR
    • Pagination - fix clicking on next/back buttons on table - PR
  • Models
    • Triton - Support adding model/provider on UI - PR
    • VertexAI - Fix adding vertex models with reusable credentials - PR
    • LLM Credentials - show existing credentials for easy editing - PR
  • Teams
    • Allow reassigning team to other org - PR
  • Organizations
    • Fix showing org budget on table - PR

Logging / Guardrail Integrations​

Performance / Loadbalancing / Reliability improvements​

General Proxy Improvements​

Krrish Dholakia
Ishaan Jaffer

Deploy this version​

docker run litellm
docker run
-e STORE_MODEL_IN_DB=True
-p 4000:4000
ghcr.io/berriai/litellm:main-v1.67.4-stable

Key Highlights​

  • Improved User Management: This release enables search and filtering across users, keys, teams, and models.
  • Responses API Load Balancing: Route requests across provider regions and ensure session continuity.
  • UI Session Logs: Group several requests to LiteLLM into a session.

Improved User Management​


This release makes it easier to manage users and keys on LiteLLM. You can now search and filter across users, keys, teams, and models, and control user settings more easily.

New features include:

  • Search for users by email, ID, role, or team.
  • See all of a user's models, teams, and keys in one place.
  • Change user roles and model access right from the Users Tab.

These changes help you spend less time on user setup and management on LiteLLM.

Responses API Load Balancing​


This release introduces load balancing for the Responses API, allowing you to route requests across provider regions and ensure session continuity. It works as follows:

  • If a previous_response_id is provided, LiteLLM will route the request to the original deployment that generated the prior response — ensuring session continuity.
  • If no previous_response_id is provided, LiteLLM will load-balance requests across your available deployments.

Read more

UI Session Logs​


This release allow you to group requests to LiteLLM proxy into a session. If you specify a litellm_session_id in your request LiteLLM will automatically group all logs in the same session. This allows you to easily track usage and request content per session.

Read more

New Models / Updated Models​

  • OpenAI
    1. Added gpt-image-1 cost tracking Get Started
    2. Bug fix: added cost tracking for gpt-image-1 when quality is unspecified PR
  • Azure
    1. Fixed timestamp granularities passing to whisper in Azure Get Started
    2. Added azure/gpt-image-1 pricing Get Started, PR
    3. Added cost tracking for azure/computer-use-preview, azure/gpt-4o-audio-preview-2024-12-17, azure/gpt-4o-mini-audio-preview-2024-12-17 PR
  • Bedrock
    1. Added support for all compatible Bedrock parameters when model="arn:.." (Bedrock application inference profile models) Get started, PR
    2. Fixed wrong system prompt transformation PR
  • VertexAI / Google AI Studio
    1. Allow setting budget_tokens=0 for gemini-2.5-flash Get Started,PR
    2. Ensure returned usage includes thinking token usage PR
    3. Added cost tracking for gemini-2.5-pro-preview-03-25 PR
  • Cohere
    1. Added support for cohere command-a-03-2025 Get Started, PR
  • SageMaker
    1. Added support for max_completion_tokens parameter Get Started, PR
  • Responses API
    1. Added support for GET and DELETE operations - /v1/responses/{response_id} Get Started
    2. Added session management support for non-OpenAI models PR
    3. Added routing affinity to maintain model consistency within sessions Get Started, PR

Spend Tracking Improvements​

  • Bug Fix: Fixed spend tracking bug, ensuring default litellm params aren't modified in memory PR
  • Deprecation Dates: Added deprecation dates for Azure, VertexAI models PR

Management Endpoints / UI​

Users​

  • Filtering and Searching:

    • Filter users by user_id, role, team, sso_id
    • Search users by email

  • User Info Panel: Added a new user information pane PR

    • View teams, keys, models associated with User
    • Edit user role, model permissions

Teams​

  • Filtering and Searching:

    • Filter teams by Organization, Team ID PR
    • Search teams by Team Name PR

Keys​

  • Key Management:
    • Support for cross-filtering and filtering by key hash PR
    • Fixed key alias reset when resetting filters PR
    • Fixed table rendering on key creation PR

UI Logs Page​

UI Authentication & Security​

  • Required Authentication: Authentication now required for all dashboard pages PR
  • SSO Fixes: Fixed SSO user login invalid token error PR
  • [BETA] Encrypted Tokens: Moved UI to encrypted token usage PR
  • Token Expiry: Support token refresh by re-routing to login page (fixes issue where expired token would show a blank page) PR

UI General fixes​

  • Fixed UI Flicker: Addressed UI flickering issues in Dashboard PR
  • Improved Terminology: Better loading and no-data states on Keys and Tools pages PR
  • Azure Model Support: Fixed editing Azure public model names and changing model names after creation PR
  • Team Model Selector: Bug fix for team model selection PR

Logging / Guardrail Integrations​

  • Datadog:
    1. Fixed Datadog LLM observability logging Get Started, PR
  • Prometheus / Grafana:
    1. Enable datasource selection on LiteLLM Grafana Template Get Started, PR
  • AgentOps:
    1. Added AgentOps Integration Get Started, PR
  • Arize:
    1. Added missing attributes for Arize & Phoenix Integration Get Started, PR

General Proxy Improvements​

  • Caching: Fixed caching to account for thinking or reasoning_effort when calculating cache key PR
  • Model Groups: Fixed handling for cases where user sets model_group inside model_info PR
  • Passthrough Endpoints: Ensured PassthroughStandardLoggingPayload is logged with method, URL, request/response body PR
  • Fix SQL Injection: Fixed potential SQL injection vulnerability in spend_management_endpoints.py PR

Helm​

  • Fixed serviceAccountName on migration job PR

Full Changelog​

The complete list of changes can be found in the GitHub release notes.

Krrish Dholakia
Ishaan Jaffer

Key Highlights​

  • SCIM Integration: Enables identity providers (Okta, Azure AD, OneLogin, etc.) to automate user and team (group) provisioning, updates, and deprovisioning
  • Team and Tag based usage tracking: You can now see usage and spend by team and tag at 1M+ spend logs.
  • Unified Responses API: Support for calling Anthropic, Gemini, Groq, etc. via OpenAI's new Responses API.

Let's dive in.

SCIM Integration​

This release adds SCIM support to LiteLLM. This allows your SSO provider (Okta, Azure AD, etc) to automatically create/delete users, teams, and memberships on LiteLLM. This means that when you remove a team on your SSO provider, your SSO provider will automatically delete the corresponding team on LiteLLM.

Read more

Team and Tag based usage tracking​

This release improves team and tag based usage tracking at 1m+ spend logs, making it easy to monitor your LLM API Spend in production. This covers:

  • View daily spend by teams + tags
  • View usage / spend by key, within teams
  • View spend by multiple tags
  • Allow internal users to view spend of teams they're a member of

Read more

Unified Responses API​

This release allows you to call Azure OpenAI, Anthropic, AWS Bedrock, and Google Vertex AI models via the POST /v1/responses endpoint on LiteLLM. This means you can now use popular tools like OpenAI Codex with your own models.

Read more

New Models / Updated Models​

  • OpenAI
    1. gpt-4.1, gpt-4.1-mini, gpt-4.1-nano, o3, o3-mini, o4-mini pricing - Get Started, PR
    2. o4 - correctly map o4 to openai o_series model
  • Azure AI
    1. Phi-4 output cost per token fix - PR
    2. Responses API support Get Started,PR
  • Anthropic
    1. redacted message thinking support - Get Started,PR
  • Cohere
    1. /v2/chat Passthrough endpoint support w/ cost tracking - Get Started, PR
  • Azure
    1. Support azure tenant_id/client_id env vars - Get Started, PR
    2. Fix response_format check for 2025+ api versions - PR
    3. Add gpt-4.1, gpt-4.1-mini, gpt-4.1-nano, o3, o3-mini, o4-mini pricing
  • VLLM
    1. Files - Support 'file' message type for VLLM video url's - Get Started, PR
    2. Passthrough - new /vllm/ passthrough endpoint support Get Started, PR
  • Mistral
    1. new /mistral passthrough endpoint support Get Started, PR
  • AWS
    1. New mapped bedrock regions - PR
  • VertexAI / Google AI Studio
    1. Gemini - Response format - Retain schema field ordering for google gemini and vertex by specifying propertyOrdering - Get Started, PR
    2. Gemini-2.5-flash - return reasoning content Google AI Studio, Vertex AI
    3. Gemini-2.5-flash - pricing + model information PR
    4. Passthrough - new /vertex_ai/discovery route - enables calling AgentBuilder API routes Get Started, PR
  • Fireworks AI
    1. return tool calling responses in tool_calls field (fireworks incorrectly returns this as a json str in content) PR
  • Triton
    1. Remove fixed remove bad_words / stop words from /generate call - Get Started, PR
  • Other
    1. Support for all litellm providers on Responses API (works with Codex) - Get Started, PR
    2. Fix combining multiple tool calls in streaming response - Get Started, PR

Spend Tracking Improvements​

  • Cost Control - inject cache control points in prompt for cost reduction Get Started, PR
  • Spend Tags - spend tags in headers - support x-litellm-tags even if tag based routing not enabled Get Started, PR
  • Gemini-2.5-flash - support cost calculation for reasoning tokens PR

Management Endpoints / UI​

  • Users

    1. Show created_at and updated_at on users page - PR

  • Virtual Keys

    1. Filter by key alias - https://github.com/BerriAI/litellm/pull/10085

  • Usage Tab

    1. Team based usage

      • New LiteLLM_DailyTeamSpend Table for aggregate team based usage logging - PR

      • New Team based usage dashboard + new /team/daily/activity API - PR

      • Return team alias on /team/daily/activity API - PR

      • allow internal user view spend for teams they belong to - PR

      • allow viewing top keys by team - PR

    2. Tag Based Usage

      • New LiteLLM_DailyTagSpend Table for aggregate tag based usage logging - PR
      • Restrict to only Proxy Admins - PR
      • allow viewing top keys by tag
      • Return tags passed in request (i.e. dynamic tags) on /tag/list API - PR

    3. Track prompt caching metrics in daily user, team, tag tables - PR

    4. Show usage by key (on all up, team, and tag usage dashboards) - PR

    5. swap old usage with new usage tab

  • Models

    1. Make columns resizable/hideable - PR

  • API Playground

    1. Allow internal user to call api playground - PR

  • SCIM

    1. Add LiteLLM SCIM Integration for Team and User management - Get Started, PR

Logging / Guardrail Integrations​

  • GCS
    1. Fix gcs pub sub logging with env var GCS_PROJECT_ID - Get Started, PR
  • AIM
    1. Add litellm call id passing to Aim guardrails on pre and post-hooks calls - Get Started, PR
  • Azure blob storage
    1. Ensure logging works in high throughput scenarios - Get Started, PR

General Proxy Improvements​

  • Support setting litellm.modify_params via env var PR
  • Model Discovery - Check provider’s /models endpoints when calling proxy’s /v1/models endpoint - Get Started, PR
  • /utils/token_counter - fix retrieving custom tokenizer for db models - Get Started, PR
  • Prisma migrate - handle existing columns in db table - PR

Krrish Dholakia
Ishaan Jaffer

Deploy this version​

docker run litellm
docker run
-e STORE_MODEL_IN_DB=True
-p 4000:4000
ghcr.io/berriai/litellm:main-v1.66.0-stable

v1.66.0-stable is live now, here are the key highlights of this release

Key Highlights​

  • Realtime API Cost Tracking: Track cost of realtime API calls
  • Microsoft SSO Auto-sync: Auto-sync groups and group members from Azure Entra ID to LiteLLM
  • xAI grok-3: Added support for xai/grok-3 models
  • Security Fixes: Fixed CVE-2025-0330 and CVE-2024-6825 vulnerabilities

Let's dive in.

Realtime API Cost Tracking​

This release adds Realtime API logging + cost tracking.

  • Logging: LiteLLM now logs the complete response from realtime calls to all logging integrations (DB, S3, Langfuse, etc.)
  • Cost Tracking: You can now set 'base_model' and custom pricing for realtime models. Custom Pricing
  • Budgets: Your key/user/team budgets now work for realtime models as well.

Start here

Microsoft SSO Auto-sync​

Auto-sync groups and members from Azure Entra ID to LiteLLM

This release adds support for auto-syncing groups and members on Microsoft Entra ID with LiteLLM. This means that LiteLLM proxy administrators can spend less time managing teams and members and LiteLLM handles the following:

  • Auto-create teams that exist on Microsoft Entra ID
  • Sync team members on Microsoft Entra ID with LiteLLM teams

Get started with this here

New Models / Updated Models​

  • xAI

    1. Added reasoning_effort support for xai/grok-3-mini-beta Get Started
    2. Added cost tracking for xai/grok-3 models PR

  • Hugging Face

    1. Added inference providers support Get Started

  • Azure

    1. Added azure/gpt-4o-realtime-audio cost tracking PR

  • VertexAI

    1. Added enterpriseWebSearch tool support Get Started
    2. Moved to only passing keys accepted by the Vertex AI response schema PR

  • Google AI Studio

    1. Added cost tracking for gemini-2.5-pro PR
    2. Fixed pricing for 'gemini/gemini-2.5-pro-preview-03-25' PR
    3. Fixed handling file_data being passed in PR

  • Azure

    1. Updated Azure Phi-4 pricing PR
    2. Added azure/gpt-4o-realtime-audio cost tracking PR

  • Databricks

    1. Removed reasoning_effort from parameters PR
    2. Fixed custom endpoint check for Databricks PR

  • General

    1. Added litellm.supports_reasoning() util to track if an llm supports reasoning Get Started
    2. Function Calling - Handle pydantic base model in message tool calls, handle tools = [], and support fake streaming on tool calls for meta.llama3-3-70b-instruct-v1:0 PR
    3. LiteLLM Proxy - Allow passing thinking param to litellm proxy via client sdk PR
    4. Fixed correctly translating 'thinking' param for litellm PR

Spend Tracking Improvements​

  • OpenAI, Azure
    1. Realtime API Cost tracking with token usage metrics in spend logs Get Started
  • Anthropic
    1. Fixed Claude Haiku cache read pricing per token PR
    2. Added cost tracking for Claude responses with base_model PR
    3. Fixed Anthropic prompt caching cost calculation and trimmed logged message in db PR
  • General
    1. Added token tracking and log usage object in spend logs PR
    2. Handle custom pricing at deployment level PR

Management Endpoints / UI​

  • Test Key Tab

    1. Added rendering of Reasoning content, ttft, usage metrics on test key page PR

      View input, output, reasoning tokens, ttft metrics.

  • Tag / Policy Management

    1. Added Tag/Policy Management. Create routing rules based on request metadata. This allows you to enforce that requests with tags="private" only go to specific models. Get Started


      Create and manage tags.

  • Redesigned Login Screen

    1. Polished login screen PR

  • Microsoft SSO Auto-Sync

    1. Added debug route to allow admins to debug SSO JWT fields PR
    2. Added ability to use MSFT Graph API to assign users to teams PR
    3. Connected litellm to Azure Entra ID Enterprise Application PR
    4. Added ability for admins to set default_team_params for when litellm SSO creates default teams PR
    5. Fixed MSFT SSO to use correct field for user email PR
    6. Added UI support for setting Default Team setting when litellm SSO auto creates teams PR

  • UI Bug Fixes

    1. Prevented team, key, org, model numerical values changing on scrolling PR
    2. Instantly reflect key and team updates in UI PR

Logging / Guardrail Improvements​

  • Prometheus
    1. Emit Key and Team Budget metrics on a cron job schedule Get Started

Security Fixes​

Helm​

  • Added service annotations to litellm-helm chart PR
  • Added extraEnvVars to the helm deployment PR

Demo​

Try this on the demo instance today

Complete Git Diff​

See the complete git diff since v1.65.4-stable, here

Krrish Dholakia
Ishaan Jaffer

Deploy this version​

docker run litellm
docker run
-e STORE_MODEL_IN_DB=True
-p 4000:4000
ghcr.io/berriai/litellm:main-v1.65.4-stable

v1.65.4-stable is live. Here are the improvements since v1.65.0-stable.

Key Highlights​

  • Preventing DB Deadlocks: Fixes a high-traffic issue when multiple instances were writing to the DB at the same time.
  • New Usage Tab: Enables viewing spend by model and customizing date range

Let's dive in.

Preventing DB Deadlocks​

This release fixes the DB deadlocking issue that users faced in high traffic (10K+ RPS). This is great because it enables user/key/team spend tracking works at that scale.

Read more about the new architecture here

New Usage Tab​

The new Usage tab now brings the ability to track daily spend by model. This makes it easier to catch any spend tracking or token counting errors, when combined with the ability to view successful requests, and token usage.

To test this out, just go to Experimental > New Usage > Activity.

New Models / Updated Models​

  1. Databricks - claude-3-7-sonnet cost tracking PR
  2. VertexAI - gemini-2.5-pro-exp-03-25 cost tracking PR
  3. VertexAI - gemini-2.0-flash cost tracking PR
  4. Groq - add whisper ASR models to model cost map PR
  5. IBM - Add watsonx/ibm/granite-3-8b-instruct to model cost map PR
  6. Google AI Studio - add gemini/gemini-2.5-pro-preview-03-25 to model cost map PR

LLM Translation​

  1. Vertex AI - Support anyOf param for OpenAI json schema translation Get Started
  2. Anthropic- response_format + thinking param support (works across Anthropic API, Bedrock, Vertex) Get Started
  3. Anthropic - if thinking token is specified and max tokens is not - ensure max token to anthropic is higher than thinking tokens (works across Anthropic API, Bedrock, Vertex) PR
  4. Bedrock - latency optimized inference support Get Started
  5. Sagemaker - handle special tokens + multibyte character code in response Get Started
  6. MCP - add support for using SSE MCP servers Get Started
  7. Anthropic - new litellm.messages.create interface for calling Anthropic /v1/messages via passthrough Get Started
  8. Anthropic - support ‘file’ content type in message param (works across Anthropic API, Bedrock, Vertex) Get Started
  9. Anthropic - map openai 'reasoning_effort' to anthropic 'thinking' param (works across Anthropic API, Bedrock, Vertex) Get Started
  10. Google AI Studio (Gemini) - [BETA] /v1/files upload support Get Started
  11. Azure - fix o-series tool calling Get Started
  12. Unified file id - [ALPHA] allow calling multiple providers with same file id PR
    • This is experimental, and not recommended for production use.
    • We plan to have a production-ready implementation by next week.
  13. Google AI Studio (Gemini) - return logprobs PR
  14. Anthropic - Support prompt caching for Anthropic tool calls Get Started
  15. OpenRouter - unwrap extra body on open router calls PR
  16. VertexAI - fix credential caching issue PR
  17. XAI - filter out 'name' param for XAI PR
  18. Gemini - image generation output support Get Started
  19. Databricks - support claude-3-7-sonnet w/ thinking + response_format Get Started

Spend Tracking Improvements​

  1. Reliability fix - Check sent and received model for cost calculation PR
  2. Vertex AI - Multimodal embedding cost tracking Get Started, PR

Management Endpoints / UI​

  1. New Usage Tab
    • Report 'total_tokens' + report success/failure calls
    • Remove double bars on scroll
    • Ensure ‘daily spend’ chart ordered from earliest to latest date
    • showing spend per model per day
    • show key alias on usage tab
    • Allow non-admins to view their activity
    • Add date picker to new usage tab
  2. Virtual Keys Tab
    • remove 'default key' on user signup
    • fix showing user models available for personal key creation
  3. Test Key Tab
    • Allow testing image generation models
  4. Models Tab
    • Fix bulk adding models
    • support reusable credentials for passthrough endpoints
    • Allow team members to see team models
  5. Teams Tab
    • Fix json serialization error on update team metadata
  6. Request Logs Tab
    • Add reasoning_content token tracking across all providers on streaming
  7. API
  8. SSO
    • Allow assigning SSO users to teams on MSFT SSO PR

Logging / Guardrail Integrations​

  1. Console Logs - Add json formatting for uncaught exceptions PR
  2. Guardrails - AIM Guardrails support for virtual key based policies Get Started
  3. Logging - fix completion start time tracking PR
  4. Prometheus
    • Allow adding authentication on Prometheus /metrics endpoints PR
    • Distinguish LLM Provider Exception vs. LiteLLM Exception in metric naming PR
    • Emit operational metrics for new DB Transaction architecture PR

Performance / Loadbalancing / Reliability improvements​

  1. Preventing Deadlocks
    • Reduce DB Deadlocks by storing spend updates in Redis and then committing to DB PR
    • Ensure no deadlocks occur when updating DailyUserSpendTransaction PR
    • High Traffic fix - ensure new DB + Redis architecture accurately tracks spend PR
    • Use Redis for PodLock Manager instead of PG (ensures no deadlocks occur) PR
    • v2 DB Deadlock Reduction Architecture – Add Max Size for In-Memory Queue + Backpressure Mechanism PR
  2. Prisma Migrations Get Started
    • connects litellm proxy to litellm's prisma migration files
    • Handle db schema updates from new litellm-proxy-extras sdk
  3. Redis - support password for sync sentinel clients PR
  4. Fix "Circular reference detected" error when max_parallel_requests = 0 PR
  5. Code QA - Ban hardcoded numbers PR

Helm​

  1. fix: wrong indentation of ttlSecondsAfterFinished in chart PR

General Proxy Improvements​

  1. Fix - only apply service_account_settings.enforced_params on service accounts PR
  2. Fix - handle metadata null on /chat/completion PR
  3. Fix - Move daily user transaction logging outside of 'disable_spend_logs' flag, as they’re unrelated PR

Demo​

Try this on the demo instance today

Complete Git Diff​

See the complete git diff since v1.65.0-stable, here

Krrish Dholakia
Ishaan Jaffer

v1.65.0-stable is live now. Here are the key highlights of this release:

  • MCP Support: Support for adding and using MCP servers on the LiteLLM proxy.
  • UI view total usage after 1M+ logs: You can now view usage analytics after crossing 1M+ logs in DB.

Model Context Protocol (MCP)​

This release introduces support for centrally adding MCP servers on LiteLLM. This allows you to add MCP server endpoints and your developers can list and call MCP tools through LiteLLM.

Read more about MCP here.

Expose and use MCP servers through LiteLLM

UI view total usage after 1M+ logs​

This release brings the ability to view total usage analytics even after exceeding 1M+ logs in your database. We've implemented a scalable architecture that stores only aggregate usage data, resulting in significantly more efficient queries and reduced database CPU utilization.

View total usage after 1M+ logs

  • How this works:

    • We now aggregate usage data into a dedicated DailyUserSpend table, significantly reducing query load and CPU usage even beyond 1M+ logs.

  • Daily Spend Breakdown API:

    • Retrieve granular daily usage data (by model, provider, and API key) with a single endpoint. Example Request:

      Daily Spend Breakdown API
      curl -L -X GET 'http://localhost:4000/user/daily/activity?start_date=2025-03-20&end_date=2025-03-27' \
      -H 'Authorization: Bearer sk-...'
      Daily Spend Breakdown API Response
      {
          "results": [
              {
                  "date": "2025-03-27",
                  "metrics": {
                      "spend": 0.0177072,
                      "prompt_tokens": 111,
                      "completion_tokens": 1711,
                      "total_tokens": 1822,
                      "api_requests": 11
                  },
                  "breakdown": {
                      "models": {
                          "gpt-4o-mini": {
                              "spend": 1.095e-05,
                              "prompt_tokens": 37,
                              "completion_tokens": 9,
                              "total_tokens": 46,
                              "api_requests": 1
                      },
                      "providers": { "openai": { ... }, "azure_ai": { ... } },
                      "api_keys": { "3126b6eaf1...": { ... } }
                  }
              }
          ],
          "metadata": {
              "total_spend": 0.7274667,
              "total_prompt_tokens": 280990,
              "total_completion_tokens": 376674,
              "total_api_requests": 14
          }
      }

New Models / Updated Models​

  • Support for Vertex AI gemini-2.0-flash-lite & Google AI Studio gemini-2.0-flash-lite PR
  • Support for Vertex AI Fine-Tuned LLMs PR
  • Nova Canvas image generation support PR
  • OpenAI gpt-4o-transcribe support PR
  • Added new Vertex AI text embedding model PR

LLM Translation​

  • OpenAI Web Search Tool Call Support PR
  • Vertex AI topLogprobs support PR
  • Support for sending images and video to Vertex AI multimodal embedding Doc
  • Support litellm.api_base for Vertex AI + Gemini across completion, embedding, image_generation PR
  • Bug fix for returning response_cost when using litellm python SDK with LiteLLM Proxy PR
  • Support for max_completion_tokens on Mistral API PR
  • Refactored Vertex AI passthrough routes - fixes unpredictable behaviour with auto-setting default_vertex_region on router model add PR

Spend Tracking Improvements​

  • Log 'api_base' on spend logs PR
  • Support for Gemini audio token cost tracking PR
  • Fixed OpenAI audio input token cost tracking PR

UI​

Model Management​

  • Allowed team admins to add/update/delete models on UI PR
  • Added render supports_web_search on model hub PR

Request Logs​

  • Show API base and model ID on request logs PR
  • Allow viewing keyinfo on request logs PR

Usage Tab​

  • Added Daily User Spend Aggregate view - allows UI Usage tab to work > 1m rows PR
  • Connected UI to "LiteLLM_DailyUserSpend" spend table PR

Logging Integrations​

  • Fixed StandardLoggingPayload for GCS Pub Sub Logging Integration PR
  • Track litellm_model_name on StandardLoggingPayload Docs

Performance / Reliability Improvements​

  • LiteLLM Redis semantic caching implementation PR
  • Gracefully handle exceptions when DB is having an outage PR
  • Allow Pods to startup + passing /health/readiness when allow_requests_on_db_unavailable: True and DB is down PR

General Improvements​

  • Support for exposing MCP tools on litellm proxy PR
  • Support discovering Gemini, Anthropic, xAI models by calling their /v1/model endpoint PR
  • Fixed route check for non-proxy admins on JWT auth PR
  • Added baseline Prisma database migrations PR
  • View all wildcard models on /model/info PR

Security​

  • Bumped next from 14.2.21 to 14.2.25 in UI dashboard PR

Complete Git Diff​

Here's the complete git diff

Krrish Dholakia
Ishaan Jaffer

v1.65.0 updates the /model/new endpoint to prevent non-team admins from creating team models.

This means that only proxy admins or team admins can create team models.

Additional Changes​

  • Allows team admins to call /model/update to update team models.
  • Allows team admins to call /model/delete to delete team models.
  • Introduces new user_models_only param to /v2/model/info - only return models added by this user.

These changes enable team admins to add and manage models for their team on the LiteLLM UI + API.

Krrish Dholakia
Ishaan Jaffer

These are the changes since v1.63.11-stable.

This release brings:

  • LLM Translation Improvements (MCP Support and Bedrock Application Profiles)
  • Perf improvements for Usage-based Routing
  • Streaming guardrail support via websockets
  • Azure OpenAI client perf fix (from previous release)

Docker Run LiteLLM Proxy​

docker run
-e STORE_MODEL_IN_DB=True
-p 4000:4000
ghcr.io/berriai/litellm:main-v1.63.14-stable.patch1

Demo Instance​

Here's a Demo Instance to test changes:

New Models / Updated Models​

  • Azure gpt-4o - fixed pricing to latest global pricing - PR
  • O1-Pro - add pricing + model information - PR
  • Azure AI - mistral 3.1 small pricing added - PR
  • Azure - gpt-4.5-preview pricing added - PR

LLM Translation​

  1. New LLM Features
  • Bedrock: Support bedrock application inference profiles Docs
    • Infer aws region from bedrock application profile id - (arn:aws:bedrock:us-east-1:...)
  • Ollama - support calling via /v1/completions Get Started
  • Bedrock - support us.deepseek.r1-v1:0 model name Docs
  • OpenRouter - OPENROUTER_API_BASE env var support Docs
  • Azure - add audio model parameter support - Docs
  • OpenAI - PDF File support Docs
  • OpenAI - o1-pro Responses API streaming support Docs
  • [BETA] MCP - Use MCP Tools with LiteLLM SDK Docs
  1. Bug Fixes
  • Voyage: prompt token on embedding tracking fix - PR
  • Sagemaker - Fix ‘Too little data for declared Content-Length’ error - PR
  • OpenAI-compatible models - fix issue when calling openai-compatible models w/ custom_llm_provider set - PR
  • VertexAI - Embedding ‘outputDimensionality’ support - PR
  • Anthropic - return consistent json response format on streaming/non-streaming - PR

Spend Tracking Improvements​

  • litellm_proxy/ - support reading litellm response cost header from proxy, when using client sdk
  • Reset Budget Job - fix budget reset error on keys/teams/users PR
  • Streaming - Prevents final chunk w/ usage from being ignored (impacted bedrock streaming + cost tracking) PR

UI​

  1. Users Page
    • Feature: Control default internal user settings PR
  2. Icons:
    • Feature: Replace external "artificialanalysis.ai" icons by local svg PR
  3. Sign In/Sign Out
    • Fix: Default login when default_user_id user does not exist in DB PR

Logging Integrations​

  • Support post-call guardrails for streaming responses Get Started
  • Arize Get Started
    • fix invalid package import PR
    • migrate to using standardloggingpayload for metadata, ensures spans land successfully PR
    • fix logging to just log the LLM I/O PR
    • Dynamic API Key/Space param support Get Started
  • StandardLoggingPayload - Log litellm_model_name in payload. Allows knowing what the model sent to API provider was Get Started
  • Prompt Management - Allow building custom prompt management integration Get Started

Performance / Reliability improvements​

  • Redis Caching - add 5s default timeout, prevents hanging redis connection from impacting llm calls PR
  • Allow disabling all spend updates / writes to DB - patch to allow disabling all spend updates to DB with a flag PR
  • Azure OpenAI - correctly re-use azure openai client, fixes perf issue from previous Stable release PR
  • Azure OpenAI - uses litellm.ssl_verify on Azure/OpenAI clients PR
  • Usage-based routing - Wildcard model support Get Started
  • Usage-based routing - Support batch writing increments to redis - reduces latency to same as ‘simple-shuffle’ PR
  • Router - show reason for model cooldown on ‘no healthy deployments available error’ PR
  • Caching - add max value limit to an item in in-memory cache (1MB) - prevents OOM errors on large image url’s being sent through proxy PR

General Improvements​

  • Passthrough Endpoints - support returning api-base on pass-through endpoints Response Headers Docs
  • SSL - support reading ssl security level from env var - Allows user to specify lower security settings Get Started
  • Credentials - only poll Credentials table when STORE_MODEL_IN_DB is True PR
  • Image URL Handling - new architecture doc on image url handling Docs
  • OpenAI - bump to pip install "openai==1.68.2" PR
  • Gunicorn - security fix - bump gunicorn==23.0.0 PR

Complete Git Diff​

Here's the complete git diff

Krrish Dholakia
Ishaan Jaffer

These are the changes since v1.63.2-stable.

This release is primarily focused on:

  • [Beta] Responses API Support
  • Snowflake Cortex Support, Amazon Nova Image Generation
  • UI - Credential Management, re-use credentials when adding new models
  • UI - Test Connection to LLM Provider before adding a model

Known Issues​

  • 🚨 Known issue on Azure OpenAI - We don't recommend upgrading if you use Azure OpenAI. This version failed our Azure OpenAI load test

Docker Run LiteLLM Proxy​

docker run
-e STORE_MODEL_IN_DB=True
-p 4000:4000
ghcr.io/berriai/litellm:main-v1.63.11-stable

Demo Instance​

Here's a Demo Instance to test changes:

New Models / Updated Models​

  • Image Generation support for Amazon Nova Canvas Getting Started
  • Add pricing for Jamba new models PR
  • Add pricing for Amazon EU models PR
  • Add Bedrock Deepseek R1 model pricing PR
  • Update Gemini pricing: Gemma 3, Flash 2 thinking update, LearnLM PR
  • Mark Cohere Embedding 3 models as Multimodal PR
  • Add Azure Data Zone pricing PR
    • LiteLLM Tracks cost for azure/eu and azure/us models

LLM Translation​

  1. New Endpoints
  1. New LLM Providers
  1. New LLM Features
  1. Bug Fixes
  • OpenAI: Return code, param and type on bad request error More information on litellm exceptions
  • Bedrock: Fix converse chunk parsing to only return empty dict on tool use PR
  • Bedrock: Support extra_headers PR
  • Azure: Fix Function Calling Bug & Update Default API Version to 2025-02-01-preview PR
  • Azure: Fix AI services URL PR
  • Vertex AI: Handle HTTP 201 status code in response PR
  • Perplexity: Fix incorrect streaming response PR
  • Triton: Fix streaming completions bug PR
  • Deepgram: Support bytes.IO when handling audio files for transcription PR
  • Ollama: Fix "system" role has become unacceptable PR
  • All Providers (Streaming): Fix String data: stripped from entire content in streamed responses PR

Spend Tracking Improvements​

  1. Support Bedrock converse cache token tracking Getting Started
  2. Cost Tracking for Responses API Getting Started
  3. Fix Azure Whisper cost tracking Getting Started

UI​

Re-Use Credentials on UI​

You can now onboard LLM provider credentials on LiteLLM UI. Once these credentials are added you can re-use them when adding new models Getting Started

Test Connections before adding models​

Before adding a model you can test the connection to the LLM provider to verify you have setup your API Base + API Key correctly

General UI Improvements​

  1. Add Models Page
    • Allow adding Cerebras, Sambanova, Perplexity, Fireworks, Openrouter, TogetherAI Models, Text-Completion OpenAI on Admin UI
    • Allow adding EU OpenAI models
    • Fix: Instantly show edit + deletes to models
  2. Keys Page
    • Fix: Instantly show newly created keys on Admin UI (don't require refresh)
    • Fix: Allow clicking into Top Keys when showing users Top API Key
    • Fix: Allow Filter Keys by Team Alias, Key Alias and Org
    • UI Improvements: Show 100 Keys Per Page, Use full height, increase width of key alias
  3. Users Page
    • Fix: Show correct count of internal user keys on Users Page
    • Fix: Metadata not updating in Team UI
  4. Logs Page
    • UI Improvements: Keep expanded log in focus on LiteLLM UI
    • UI Improvements: Minor improvements to logs page
    • Fix: Allow internal user to query their own logs
    • Allow switching off storing Error Logs in DB Getting Started
  5. Sign In/Sign Out

Security​

  1. Support for Rotating Master Keys Getting Started
  2. Fix: Internal User Viewer Permissions, don't allow internal_user_viewer role to see Test Key Page or Create Key Button More information on role based access controls
  3. Emit audit logs on All user + model Create/Update/Delete endpoints Getting Started
  4. JWT
    • Support multiple JWT OIDC providers Getting Started
    • Fix JWT access with Groups not working when team is assigned All Proxy Models access
  5. Using K/V pairs in 1 AWS Secret Getting Started

Logging Integrations​

  1. Prometheus: Track Azure LLM API latency metric Getting Started
  2. Athina: Added tags, user_feedback and model_options to additional_keys which can be sent to Athina Getting Started

Performance / Reliability improvements​

  1. Redis + litellm router - Fix Redis cluster mode for litellm router PR

General Improvements​

  1. OpenWebUI Integration - display thinking tokens

Complete Git Diff​

Here's the complete git diff

Krrish Dholakia
Ishaan Jaffer

These are the changes since v1.61.20-stable.

This release is primarily focused on:

  • LLM Translation improvements (more thinking content improvements)
  • UI improvements (Error logs now shown on UI)
info

This release will be live on 03/09/2025

Demo Instance​

Here's a Demo Instance to test changes:

New Models / Updated Models​

  1. Add supports_pdf_input for specific Bedrock Claude models PR
  2. Add pricing for amazon eu models PR
  3. Fix Azure O1 mini pricing PR

LLM Translation​

  1. Support /openai/ passthrough for Assistant endpoints. Get Started
  2. Bedrock Claude - fix tool calling transformation on invoke route. Get Started
  3. Bedrock Claude - response_format support for claude on invoke route. Get Started
  4. Bedrock - pass description if set in response_format. Get Started
  5. Bedrock - Fix passing response_format: {"type": "text"}. PR
  6. OpenAI - Handle sending image_url as str to openai. Get Started
  7. Deepseek - return 'reasoning_content' missing on streaming. Get Started
  8. Caching - Support caching on reasoning content. Get Started
  9. Bedrock - handle thinking blocks in assistant message. Get Started
  10. Anthropic - Return signature on streaming. Get Started
  • Note: We've also migrated from signature_delta to signature. Read more
  1. Support format param for specifying image type. Get Started
  2. Anthropic - /v1/messages endpoint - thinking param support. Get Started
  • Note: this refactors the [BETA] unified /v1/messages endpoint, to just work for the Anthropic API.
  1. Vertex AI - handle $id in response schema when calling vertex ai. Get Started

Spend Tracking Improvements​

  1. Batches API - Fix cost calculation to run on retrieve_batch. Get Started
  2. Batches API - Log batch models in spend logs / standard logging payload. Get Started

Management Endpoints / UI​

  1. Virtual Keys Page
    • Allow team/org filters to be searchable on the Create Key Page
    • Add created_by and updated_by fields to Keys table
    • Show 'user_email' on key table
    • Show 100 Keys Per Page, Use full height, increase width of key alias
  2. Logs Page
    • Show Error Logs on LiteLLM UI
    • Allow Internal Users to View their own logs
  3. Internal Users Page
    • Allow admin to control default model access for internal users
  4. Fix session handling with cookies

Logging / Guardrail Integrations​

  1. Fix prometheus metrics w/ custom metrics, when keys containing team_id make requests. PR

Performance / Loadbalancing / Reliability improvements​

  1. Cooldowns - Support cooldowns on models called with client side credentials. Get Started
  2. Tag-based Routing - ensures tag-based routing across all endpoints (/embeddings, /image_generation, etc.). Get Started

General Proxy Improvements​

  1. Raise BadRequestError when unknown model passed in request
  2. Enforce model access restrictions on Azure OpenAI proxy route
  3. Reliability fix - Handle emoji’s in text - fix orjson error
  4. Model Access Patch - don't overwrite litellm.anthropic_models when running auth checks
  5. Enable setting timezone information in docker image

Complete Git Diff​

Here's the complete git diff

Krrish Dholakia
Ishaan Jaffer

v1.63.0 fixes Anthropic 'thinking' response on streaming to return the signature block. Github Issue

It also moves the response structure from signature_delta to signature to be the same as Anthropic. Anthropic Docs

Diff​

"message": {
    ...
    "reasoning_content": "The capital of France is Paris.",
    "thinking_blocks": [
        {
            "type": "thinking",
            "thinking": "The capital of France is Paris.",
-            "signature_delta": "EqoBCkgIARABGAIiQL2UoU0b1OHYi+..." # 👈 OLD FORMAT
+            "signature": "EqoBCkgIARABGAIiQL2UoU0b1OHYi+..." # 👈 KEY CHANGE
        }
    ]
}

Krrish Dholakia
Ishaan Jaffer

These are the changes since v1.61.13-stable.

This release is primarily focused on:

  • LLM Translation improvements (claude-3-7-sonnet + 'thinking'/'reasoning_content' support)
  • UI improvements (add model flow, user management, etc)

Demo Instance​

Here's a Demo Instance to test changes:

New Models / Updated Models​

  1. Anthropic 3-7 sonnet support + cost tracking (Anthropic API + Bedrock + Vertex AI + OpenRouter)
    1. Anthropic API Start here
    2. Bedrock API Start here
    3. Vertex AI API See here
    4. OpenRouter See here
  2. Gpt-4.5-preview support + cost tracking See here
  3. Azure AI - Phi-4 cost tracking See here
  4. Claude-3.5-sonnet - vision support updated on Anthropic API See here
  5. Bedrock llama vision support See here
  6. Cerebras llama3.3-70b pricing See here

LLM Translation​

  1. Infinity Rerank - support returning documents when return_documents=True Start here
  2. Amazon Deepseek - <think> param extraction into ‘reasoning_content’ Start here
  3. Amazon Titan Embeddings - filter out ‘aws_’ params from request body Start here
  4. Anthropic ‘thinking’ + ‘reasoning_content’ translation support (Anthropic API, Bedrock, Vertex AI) Start here
  5. VLLM - support ‘video_url’ Start here
  6. Call proxy via litellm SDK: Support litellm_proxy/ for embedding, image_generation, transcription, speech, rerank Start here
  7. OpenAI Pass-through - allow using Assistants GET, DELETE on /openai pass through routes Start here
  8. Message Translation - fix openai message for assistant msg if role is missing - openai allows this
  9. O1/O3 - support ‘drop_params’ for o3-mini and o1 parallel_tool_calls param (not supported currently) See here

Spend Tracking Improvements​

  1. Cost tracking for rerank via Bedrock See PR
  2. Anthropic pass-through - fix race condition causing cost to not be tracked See PR
  3. Anthropic pass-through: Ensure accurate token counting See PR

Management Endpoints / UI​

  1. Models Page - Allow sorting models by ‘created at’
  2. Models Page - Edit Model Flow Improvements
  3. Models Page - Fix Adding Azure, Azure AI Studio models on UI
  4. Internal Users Page - Allow Bulk Adding Internal Users on UI
  5. Internal Users Page - Allow sorting users by ‘created at’
  6. Virtual Keys Page - Allow searching for UserIDs on the dropdown when assigning a user to a team See PR
  7. Virtual Keys Page - allow creating a user when assigning keys to users See PR
  8. Model Hub Page - fix text overflow issue See PR
  9. Admin Settings Page - Allow adding MSFT SSO on UI
  10. Backend - don't allow creating duplicate internal users in DB

Helm​

  1. support ttlSecondsAfterFinished on the migration job - See PR
  2. enhance migrations job with additional configurable properties - See PR

Logging / Guardrail Integrations​

  1. Arize Phoenix support
  2. ‘No-log’ - fix ‘no-log’ param support on embedding calls

Performance / Loadbalancing / Reliability improvements​

  1. Single Deployment Cooldown logic - Use allowed_fails or allowed_fail_policy if set Start here

General Proxy Improvements​

  1. Hypercorn - fix reading / parsing request body
  2. Windows - fix running proxy in windows
  3. DD-Trace - fix dd-trace enablement on proxy

Complete Git Diff​

View the complete git diff here.

Krrish Dholakia
Ishaan Jaffer
info

Get a 7 day free trial for LiteLLM Enterprise here.

no call needed

New Models / Updated Models​

  1. New OpenAI /image/variations endpoint BETA support Docs
  2. Topaz API support on OpenAI /image/variations BETA endpoint Docs
  3. Deepseek - r1 support w/ reasoning_content (Deepseek API, Vertex AI, Bedrock)
  4. Azure - Add azure o1 pricing See Here
  5. Anthropic - handle -latest tag in model for cost calculation
  6. Gemini-2.0-flash-thinking - add model pricing (it’s 0.0) See Here
  7. Bedrock - add stability sd3 model pricing See Here (s/o Marty Sullivan)
  8. Bedrock - add us.amazon.nova-lite-v1:0 to model cost map See Here
  9. TogetherAI - add new together_ai llama3.3 models See Here

LLM Translation​

  1. LM Studio -> fix async embedding call
  2. Gpt 4o models - fix response_format translation
  3. Bedrock nova - expand supported document types to include .md, .csv, etc. Start Here
  4. Bedrock - docs on IAM role based access for bedrock - Start Here
  5. Bedrock - cache IAM role credentials when used
  6. Google AI Studio (gemini/) - support gemini 'frequency_penalty' and 'presence_penalty'
  7. Azure O1 - fix model name check
  8. WatsonX - ZenAPIKey support for WatsonX Docs
  9. Ollama Chat - support json schema response format Start Here
  10. Bedrock - return correct bedrock status code and error message if error during streaming
  11. Anthropic - Supported nested json schema on anthropic calls
  12. OpenAI - metadata param preview support
    1. SDK - enable via litellm.enable_preview_features = True
    2. PROXY - enable via litellm_settings::enable_preview_features: true
  13. Replicate - retry completion response on status=processing

Spend Tracking Improvements​

  1. Bedrock - QA asserts all bedrock regional models have same supported_ as base model
  2. Bedrock - fix bedrock converse cost tracking w/ region name specified
  3. Spend Logs reliability fix - when user passed in request body is int instead of string
  4. Ensure ‘base_model’ cost tracking works across all endpoints
  5. Fixes for Image generation cost tracking
  6. Anthropic - fix anthropic end user cost tracking
  7. JWT / OIDC Auth - add end user id tracking from jwt auth

Management Endpoints / UI​

  1. allows team member to become admin post-add (ui + endpoints)
  2. New edit/delete button for updating team membership on UI
  3. If team admin - show all team keys
  4. Model Hub - clarify cost of models is per 1m tokens
  5. Invitation Links - fix invalid url generated
  6. New - SpendLogs Table Viewer - allows proxy admin to view spend logs on UI
    1. New spend logs - allow proxy admin to ‘opt in’ to logging request/response in spend logs table - enables easier abuse detection
    2. Show country of origin in spend logs
    3. Add pagination + filtering by key name/team name
  7. /key/delete - allow team admin to delete team keys
  8. Internal User ‘view’ - fix spend calculation when team selected
  9. Model Analytics is now on Free
  10. Usage page - shows days when spend = 0, and round spend on charts to 2 sig figs
  11. Public Teams - allow admins to expose teams for new users to ‘join’ on UI - Start Here
  12. Guardrails
    1. set/edit guardrails on a virtual key
    2. Allow setting guardrails on a team
    3. Set guardrails on team create + edit page
  13. Support temporary budget increases on /key/update - new temp_budget_increase and temp_budget_expiry fields - Start Here
  14. Support writing new key alias to AWS Secret Manager - on key rotation Start Here

Helm​

  1. add securityContext and pull policy values to migration job (s/o https://github.com/Hexoplon)
  2. allow specifying envVars on values.yaml
  3. new helm lint test

Logging / Guardrail Integrations​

  1. Log the used prompt when prompt management used. Start Here
  2. Support s3 logging with team alias prefixes - Start Here
  3. Prometheus Start Here
    1. fix litellm_llm_api_time_to_first_token_metric not populating for bedrock models
    2. emit remaining team budget metric on regular basis (even when call isn’t made) - allows for more stable metrics on Grafana/etc.
    3. add key and team level budget metrics
    4. emit litellm_overhead_latency_metric
    5. Emit litellm_team_budget_reset_at_metric and litellm_api_key_budget_remaining_hours_metric
  4. Datadog - support logging spend tags to Datadog. Start Here
  5. Langfuse - fix logging request tags, read from standard logging payload
  6. GCS - don’t truncate payload on logging
  7. New GCS Pub/Sub logging support Start Here
  8. Add AIM Guardrails support Start Here

Security​

  1. New Enterprise SLA for patching security vulnerabilities. See Here
  2. Hashicorp - support using vault namespace for TLS auth. Start Here
  3. Azure - DefaultAzureCredential support

Health Checks​

  1. Cleanup pricing-only model names from wildcard route list - prevent bad health checks
  2. Allow specifying a health check model for wildcard routes - https://docs.litellm.ai/docs/proxy/health#wildcard-routes
  3. New ‘health_check_timeout ‘ param with default 1min upperbound to prevent bad model from health check to hang and cause pod restarts. Start Here
  4. Datadog - add data dog service health check + expose new /health/services endpoint. Start Here

Performance / Reliability improvements​

  1. 3x increase in RPS - moving to orjson for reading request body
  2. LLM Routing speedup - using cached get model group info
  3. SDK speedup - using cached get model info helper - reduces CPU work to get model info
  4. Proxy speedup - only read request body 1 time per request
  5. Infinite loop detection scripts added to codebase
  6. Bedrock - pure async image transformation requests
  7. Cooldowns - single deployment model group if 100% calls fail in high traffic - prevents an o1 outage from impacting other calls
  8. Response Headers - return
    1. x-litellm-timeout
    2. x-litellm-attempted-retries
    3. x-litellm-overhead-duration-ms
    4. x-litellm-response-duration-ms
  9. ensure duplicate callbacks are not added to proxy
  10. Requirements.txt - bump certifi version

General Proxy Improvements​

  1. JWT / OIDC Auth - new enforce_rbac param,allows proxy admin to prevent any unmapped yet authenticated jwt tokens from calling proxy. Start Here
  2. fix custom openapi schema generation for customized swagger’s
  3. Request Headers - support reading x-litellm-timeout param from request headers. Enables model timeout control when using Vercel’s AI SDK + LiteLLM Proxy. Start Here
  4. JWT / OIDC Auth - new role based permissions for model authentication. See Here

Complete Git Diff​

This is the diff between v1.57.8-stable and v1.59.8-stable.

Use this to see the changes in the codebase.

Git Diff

Krrish Dholakia
Ishaan Jaffer
info

Get a 7 day free trial for LiteLLM Enterprise here.

no call needed

UI Improvements​

[Opt In] Admin UI - view messages / responses​

You can now view messages and response logs on Admin UI.

How to enable it - add store_prompts_in_spend_logs: true to your proxy_config.yaml

Once this flag is enabled, your messages and responses will be stored in the LiteLLM_Spend_Logs table.

general_settings:
  store_prompts_in_spend_logs: true

DB Schema Change​

Added messages and responses to the LiteLLM_Spend_Logs table.

By default this is not logged. If you want messages and responses to be logged, you need to opt in with this setting 

general_settings:
  store_prompts_in_spend_logs: true

Krrish Dholakia
Ishaan Jaffer

alerting, prometheus, secret management, management endpoints, ui, prompt management, finetuning, batch

New / Updated Models​

  1. Mistral large pricing - https://github.com/BerriAI/litellm/pull/7452
  2. Cohere command-r7b-12-2024 pricing - https://github.com/BerriAI/litellm/pull/7553/files
  3. Voyage - new models, prices and context window information - https://github.com/BerriAI/litellm/pull/7472
  4. Anthropic - bump Bedrock claude-3-5-haiku max_output_tokens to 8192

General Proxy Improvements​

  1. Health check support for realtime models
  2. Support calling Azure realtime routes via virtual keys
  3. Support custom tokenizer on /utils/token_counter - useful when checking token count for self-hosted models
  4. Request Prioritization - support on /v1/completion endpoint as well

LLM Translation Improvements​

  1. Deepgram STT support. Start Here
  2. OpenAI Moderations - omni-moderation-latest support. Start Here
  3. Azure O1 - fake streaming support. This ensures if a stream=true is passed, the response is streamed. Start Here
  4. Anthropic - non-whitespace char stop sequence handling - PR
  5. Azure OpenAI - support Entra ID username + password based auth. Start Here
  6. LM Studio - embedding route support. Start Here
  7. WatsonX - ZenAPIKeyAuth support. Start Here

Prompt Management Improvements​

  1. Langfuse integration
  2. HumanLoop integration
  3. Support for using load balanced models
  4. Support for loading optional params from prompt manager

Start Here

Finetuning + Batch APIs Improvements​

  1. Improved unified endpoint support for Vertex AI finetuning - PR
  2. Add support for retrieving vertex api batch jobs - PR

NEW Alerting Integration​

PagerDuty Alerting Integration.

Handles two types of alerts:

  • High LLM API Failure Rate. Configure X fails in Y seconds to trigger an alert.
  • High Number of Hanging LLM Requests. Configure X hangs in Y seconds to trigger an alert.

Start Here

Prometheus Improvements​

Added support for tracking latency/spend/tokens based on custom metrics. Start Here

NEW Hashicorp Secret Manager Support​

Support for reading credentials + writing LLM API keys. Start Here

Management Endpoints / UI Improvements​

  1. Create and view organizations + assign org admins on the Proxy UI
  2. Support deleting keys by key_alias
  3. Allow assigning teams to org on UI
  4. Disable using ui session token for 'test key' pane
  5. Show model used in 'test key' pane
  6. Support markdown output in 'test key' pane

Helm Improvements​

  1. Prevent istio injection for db migrations cron job
  2. allow using migrationJob.enabled variable within job

Logging Improvements​

  1. braintrust logging: respect project_id, add more metrics - https://github.com/BerriAI/litellm/pull/7613
  2. Athina - support base url - ATHINA_BASE_URL
  3. Lunary - Allow passing custom parent run id to LLM Calls

Git Diff​

This is the diff between v1.56.3-stable and v1.57.8-stable.

Use this to see the changes in the codebase.

Git Diff

Krrish Dholakia
Ishaan Jaffer

langfuse, management endpoints, ui, prometheus, secret management

Langfuse Prompt Management​

Langfuse Prompt Management is being labelled as BETA. This allows us to iterate quickly on the feedback we're receiving, and making the status clearer to users. We expect to make this feature to be stable by next month (February 2025).

Changes:

  • Include the client message in the LLM API Request. (Previously only the prompt template was sent, and the client message was ignored).
  • Log the prompt template in the logged request (e.g. to s3/langfuse).
  • Log the 'prompt_id' and 'prompt_variables' in the logged request (e.g. to s3/langfuse).

Start Here

Team/Organization Management + UI Improvements​

Managing teams and organizations on the UI is now easier.

Changes:

  • Support for editing user role within team on UI.
  • Support updating team member role to admin via api - /team/member_update
  • Show team admins all keys for their team.
  • Add organizations with budgets
  • Assign teams to orgs on the UI
  • Auto-assign SSO users to teams

Start Here

Hashicorp Vault Support​

We now support writing LiteLLM Virtual API keys to Hashicorp Vault.

Start Here

Custom Prometheus Metrics​

Define custom prometheus metrics, and track usage/latency/no. of requests against them

This allows for more fine-grained tracking - e.g. on prompt template passed in request metadata

Start Here

Krrish Dholakia
Ishaan Jaffer

docker image, security, vulnerability

0 Critical/High Vulnerabilities

What changed?​

  • LiteLLMBase image now uses cgr.dev/chainguard/python:latest-dev

Why the change?​

To ensure there are 0 critical/high vulnerabilities on LiteLLM Docker Image

Migration Guide​

  • If you use a custom dockerfile with litellm as a base image + apt-get

Instead of apt-get use apk, the base litellm image will no longer have apt-get installed.

You are only impacted if you use apt-get in your Dockerfile

# Use the provided base image
FROM ghcr.io/berriai/litellm:main-latest

# Set the working directory
WORKDIR /app

# Install dependencies - CHANGE THIS to `apk`
RUN apt-get update && apt-get install -y dumb-init

Before Change

RUN apt-get update && apt-get install -y dumb-init

After Change

RUN apk update && apk add --no-cache dumb-init

Krrish Dholakia
Ishaan Jaffer

deepgram, fireworks ai, vision, admin ui, dependency upgrades

New Models​

Deepgram Speech to Text​

New Speech to Text support for Deepgram models. Start Here

from litellm import transcription
import os 

# set api keys 
os.environ["DEEPGRAM_API_KEY"] = ""
audio_file = open("/path/to/audio.mp3", "rb")

response = transcription(model="deepgram/nova-2", file=audio_file)

print(f"response: {response}")

Fireworks AI - Vision support for all models​

LiteLLM supports document inlining for Fireworks AI models. This is useful for models that are not vision models, but still need to parse documents/images/etc. LiteLLM will add #transform=inline to the url of the image_url, if the model is not a vision model See Code

Proxy Admin UI​

  • Test Key Tab displays model used in response
  • Test Key Tab renders content in .md, .py (any code/markdown format)

Dependency Upgrades​

Bug Fixes​

Krrish Dholakia
Ishaan Jaffer

guardrails, logging, virtual key management, new models

info

Get a 7 day free trial for LiteLLM Enterprise here.

no call needed

New Features​

✨ Log Guardrail Traces​

Track guardrail failure rate and if a guardrail is going rogue and failing requests. Start here

Traced Guardrail Success​

Traced Guardrail Failure​

/guardrails/list​

/guardrails/list allows clients to view available guardrails + supported guardrail params

curl -X GET 'http://0.0.0.0:4000/guardrails/list'

Expected response

{
    "guardrails": [
        {
        "guardrail_name": "aporia-post-guard",
        "guardrail_info": {
            "params": [
            {
                "name": "toxicity_score",
                "type": "float",
                "description": "Score between 0-1 indicating content toxicity level"
            },
            {
                "name": "pii_detection",
                "type": "boolean"
            }
            ]
        }
        }
    ]
}

✨ Guardrails with Mock LLM​

Send mock_response to test guardrails without making an LLM call. More info on mock_response here

curl -i http://localhost:4000/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer sk-npnwjPQciVRok5yNZgKmFQ" \
  -d '{
    "model": "gpt-3.5-turbo",
    "messages": [
      {"role": "user", "content": "hi my email is ishaan@berri.ai"}
    ],
    "mock_response": "This is a mock response",
    "guardrails": ["aporia-pre-guard", "aporia-post-guard"]
  }'

Assign Keys to Users​

You can now assign keys to users via Proxy UI

New Models​

  • openrouter/openai/o1
  • vertex_ai/mistral-large@2411

Fixes​

Krrish Dholakia
Ishaan Jaffer

key management, budgets/rate limits, logging, guardrails

info

Get a 7 day free trial for LiteLLM Enterprise here.

no call needed

✨ Budget / Rate Limit Tiers​

Define tiers with rate limits. Assign them to keys.

Use this to control access and budgets across a lot of keys.

Start here

curl -L -X POST 'http://0.0.0.0:4000/budget/new' \
-H 'Authorization: Bearer sk-1234' \
-H 'Content-Type: application/json' \
-d '{
    "budget_id": "high-usage-tier",
    "model_max_budget": {
        "gpt-4o": {"rpm_limit": 1000000}
    }
}'

OTEL Bug Fix​

LiteLLM was double logging litellm_request span. This is now fixed.

Relevant PR

Logging for Finetuning Endpoints​

Logs for finetuning requests are now available on all logging providers (e.g. Datadog).

What's logged per request:

  • file_id
  • finetuning_job_id
  • any key/team metadata

Start Here:

Dynamic Params for Guardrails​

You can now set custom parameters (like success threshold) for your guardrails in each request.

See guardrails spec for more details

Krrish Dholakia
Ishaan Jaffer

batches, guardrails, team management, custom auth


info

Get a free 7-day LiteLLM Enterprise trial here. Start here

No call needed

✨ Cost Tracking, Logging for Batches API (/batches)​

Track cost, usage for Batch Creation Jobs. Start here

✨ /guardrails/list endpoint​

Show available guardrails to users. Start here

✨ Allow teams to add models​

This enables team admins to call their own finetuned models via litellm proxy. Start here

✨ Common checks for custom auth​

Calling the internal common_checks function in custom auth is now enforced as an enterprise feature. This allows admins to use litellm's default budget/auth checks within their custom auth implementation. Start here

✨ Assigning team admins​

Team admins is graduating from beta and moving to our enterprise tier. This allows proxy admins to allow others to manage keys/models for their own teams (useful for projects in production). Start here

Krrish Dholakia
Ishaan Jaffer

A new LiteLLM Stable release just went out. Here are 5 updates since v1.52.2-stable.

langfuse, fallbacks, new models, azure_storage

Langfuse Prompt Management​

This makes it easy to run experiments or change the specific models gpt-4o to gpt-4o-mini on Langfuse, instead of making changes in your applications. Start here

Control fallback prompts client-side​

Claude prompts are different than OpenAI

Pass in prompts specific to model when doing fallbacks. Start here

New Providers / Models​

✨ Azure Data Lake Storage Support​

Send LLM usage (spend, tokens) data to Azure Data Lake. This makes it easy to consume usage data on other services (eg. Databricks) Start here

Docker Run LiteLLM​

docker run \
-e STORE_MODEL_IN_DB=True \
-p 4000:4000 \
ghcr.io/berriai/litellm:litellm_stable_release_branch-v1.55.8-stable

Get Daily Updates​

LiteLLM ships new releases every day. Follow us on LinkedIn to get daily updates.