Add Model Pricing & Context Window

To add pricing or context window information for a model, simply make a PR to this file:

model_prices_and_context_window.json

Sample Spec

Here's the full specification with all available fields:

{
    "sample_spec": {
        "aliases": ["optional list of alternate names for this model, e.g. dated versions like sample_spec-20250101"],
        "code_interpreter_cost_per_session": 0.0,
        "computer_use_input_cost_per_1k_tokens": 0.0,
        "computer_use_output_cost_per_1k_tokens": 0.0,
        "deprecation_date": "date when the model becomes deprecated in the format YYYY-MM-DD",
        "file_search_cost_per_1k_calls": 0.0,
        "file_search_cost_per_gb_per_day": 0.0,
        "input_cost_per_audio_token": 0.0,
        "input_cost_per_token": 0.0,
        "litellm_provider": "one of https://docs.litellm.ai/docs/providers",
        "max_input_tokens": "max input tokens, if the provider specifies it. if not default to max_tokens",
        "max_output_tokens": "max output tokens, if the provider specifies it. if not default to max_tokens",
        "max_tokens": "LEGACY parameter. set to max_output_tokens if provider specifies it. IF not set to max_input_tokens, if provider specifies it.",
        "mode": "one of: chat, embedding, completion, image_generation, audio_transcription, audio_speech, image_generation, moderation, rerank, search",
        "output_cost_per_reasoning_token": 0.0,
        "output_cost_per_token": 0.0,
        "search_context_cost_per_query": {
            "search_context_size_high": 0.0,
            "search_context_size_low": 0.0,
            "search_context_size_medium": 0.0
        },
        "supported_regions": [
            "global",
            "us-west-2",
            "eu-west-1",
            "ap-southeast-1",
            "ap-northeast-1"
        ],
        "supports_audio_input": true,
        "supports_audio_output": true,
        "supports_function_calling": true,
        "supports_parallel_function_calling": true,
        "supports_prompt_caching": true,
        "supports_reasoning": true,
        "supports_response_schema": true,
        "supports_system_messages": true,
        "supports_vision": true,
        "supports_web_search": true,
        "vector_store_cost_per_gb_per_day": 0.0
    }
}

Examples

Anthropic Claude

{
    "claude-3-5-haiku-20241022": {
        "cache_creation_input_token_cost": 1e-06,
        "cache_creation_input_token_cost_above_1hr": 6e-06,
        "cache_read_input_token_cost": 8e-08,
        "deprecation_date": "2025-10-01",
        "input_cost_per_token": 8e-07,
        "litellm_provider": "anthropic",
        "max_input_tokens": 200000,
        "max_output_tokens": 8192,
        "max_tokens": 8192,
        "mode": "chat",
        "output_cost_per_token": 4e-06,
        "search_context_cost_per_query": {
            "search_context_size_high": 0.01,
            "search_context_size_low": 0.01,
            "search_context_size_medium": 0.01
        },
        "supports_assistant_prefill": true,
        "supports_function_calling": true,
        "supports_pdf_input": true,
        "supports_prompt_caching": true,
        "supports_vision": true
    }
}

Vertex AI Gemini

{
    "vertex_ai/gemini-3-pro-preview": {
        "cache_read_input_token_cost": 2e-07,
        "cache_read_input_token_cost_above_200k_tokens": 4e-07,
        "cache_creation_input_token_cost_above_200k_tokens": 2.5e-07,
        "input_cost_per_token": 2e-06,
        "input_cost_per_token_above_200k_tokens": 4e-06,
        "input_cost_per_token_batches": 1e-06,
        "litellm_provider": "vertex_ai",
        "max_audio_length_hours": 8.4,
        "max_audio_per_prompt": 1,
        "max_images_per_prompt": 3000,
        "max_input_tokens": 1048576,
        "max_output_tokens": 65535,
        "max_pdf_size_mb": 30,
        "max_tokens": 65535,
        "max_video_length": 1,
        "max_videos_per_prompt": 10,
        "mode": "chat",
        "output_cost_per_token": 1.2e-05,
        "output_cost_per_token_above_200k_tokens": 1.8e-05,
        "output_cost_per_token_batches": 6e-06,
        "supports_function_calling": true,
        "supports_parallel_function_calling": true,
        "supports_prompt_caching": true,
        "supports_system_messages": true,
        "supports_vision": true
    }
}

Using Aliases

Many providers release the same model under multiple names, for example a latest tag and a dated version like claude-sonnet-4-5-20250929. Instead of duplicating the entire entry, you can use the aliases field:

{
    "claude-sonnet-4-5": {
        "aliases": ["claude-sonnet-4-5-20250929"],
        "input_cost_per_token": 3e-06,
        "output_cost_per_token": 1.5e-05,
        "litellm_provider": "anthropic",
        "max_input_tokens": 200000,
        "max_output_tokens": 64000,
        "mode": "chat",
        "supports_function_calling": true,
        "supports_tool_choice": true
    }
}

At load time, each alias is expanded into a top-level entry sharing the same data as the canonical entry. The example above makes both claude-sonnet-4-5 and claude-sonnet-4-5-20250929 resolve with the same pricing and capabilities.

info

This is different from model_alias_map, which is a runtime SDK/proxy feature for mapping user-facing model names to LiteLLM model identifiers. The aliases field here is for the model cost JSON only, and it avoids duplicate entries for models that share identical pricing and capabilities.