llm-costs 0.1.1

LLM cost calculator for major providers

llm-costs

LLM cost calculator for major providers. Calculates API costs from token usage data.

Installation

pip install llm-costs

Or with uv:

uv add llm-costs

Usage

from llm_costs import calculate_cost, get_model_pricing

# Calculate cost from LangChain UsageMetadata structure
result = calculate_cost(
    provider="anthropic",
    model="claude-sonnet-4-20250514",
    usage={
        "input_tokens": 1000,
        "output_tokens": 500,
        "total_tokens": 1500,
    },
)

print(f"Cost: ${result['cost']:.6f}")  # Cost: $0.010500
print(f"Input: ${result['breakdown']['input_cost']:.6f}")
print(f"Output: ${result['breakdown']['output_cost']:.6f}")

With Prompt Caching

result = calculate_cost(
    provider="anthropic",
    model="claude-sonnet-4-20250514",
    usage={
        "input_tokens": 1000,
        "output_tokens": 500,
        "total_tokens": 1500,
        "input_token_details": {
            "cache_read": 5000,
            "cache_creation": 0,
        },
    },
)

Batch Pricing

result = calculate_cost(
    provider="anthropic",
    model="claude-sonnet-4-20250514",
    usage={"input_tokens": 1000, "output_tokens": 500, "total_tokens": 1500},
    batch=True,  # 50% discount
)

Get Model Pricing Info

pricing = get_model_pricing("anthropic", "claude-sonnet-4-20250514")
print(f"Input: ${pricing['input']}/MTok")   # Input: $3.0/MTok
print(f"Output: ${pricing['output']}/MTok") # Output: $15.0/MTok

List Available Models

from llm_costs.calculator import list_models, list_providers

providers = list_providers()  # ['anthropic', 'openai', 'google']
models = list_models("anthropic")  # ['claude-opus-4-5-20251101', ...]

Supported Providers

Anthropic

Model	Input	Output	Cache Read
claude-opus-4-5-20251101	$5.00	$25.00	$0.50
claude-opus-4-1-20250414	$15.00	$75.00	$1.50
claude-opus-4-20250514	$15.00	$75.00	$1.50
claude-sonnet-4-5-20250514	$3.00	$15.00	$0.30
claude-sonnet-4-20250514	$3.00	$15.00	$0.30
claude-3-7-sonnet-20250219	$3.00	$15.00	$0.30
claude-haiku-4-5-20250514	$1.00	$5.00	$0.10
claude-3-5-haiku-20241022	$0.80	$4.00	$0.08
claude-3-opus-20240229	$15.00	$75.00	$1.50
claude-3-haiku-20240307	$0.25	$1.25	$0.03

Prices per million tokens. Long context pricing (>200K tokens) applies to Sonnet models.

OpenAI

Model	Input	Output	Cache Read
gpt-5.2	$1.75	$14.00	$0.175
gpt-5.1	$1.25	$10.00	$0.125
gpt-5	$1.25	$10.00	$0.125
gpt-5-mini	$0.25	$2.00	$0.025
gpt-5-nano	$0.05	$0.40	$0.005
gpt-5.2-pro	$21.00	$168.00	-
gpt-5-pro	$15.00	$120.00	-
gpt-4.1	$2.00	$8.00	$0.50
gpt-4.1-mini	$0.40	$1.60	$0.10
gpt-4.1-nano	$0.10	$0.40	$0.025
gpt-4o	$2.50	$10.00	$1.25
gpt-4o-mini	$0.15	$0.60	$0.075
o1	$15.00	$60.00	$7.50
o1-pro	$150.00	$600.00	-
o1-mini	$1.10	$4.40	$0.55
o3	$2.00	$8.00	$0.50
o3-pro	$20.00	$80.00	-
o3-mini	$1.10	$4.40	$0.55
o3-deep-research	$10.00	$40.00	$2.50
o4-mini	$1.10	$4.40	$0.275
o4-mini-deep-research	$2.00	$8.00	$0.50
computer-use-preview	$3.00	$12.00	-

Prices per million tokens (Standard tier).

Google

Model	Input	Output	Cache Read
gemini-3-pro-preview	$2.00	$12.00	$0.20
gemini-2.5-pro	$1.25	$10.00	$0.125
gemini-2.5-flash	$0.30	$2.50	$0.03
gemini-2.5-flash-lite	$0.10	$0.40	$0.01
gemini-2.0-flash	$0.10	$0.40	$0.025
gemini-2.0-flash-lite	$0.075	$0.30	-

Prices per million tokens (Paid tier). Long context pricing (>200K tokens) applies to Pro models.

Usage Schema

The library accepts token usage in LangChain's UsageMetadata format:

{
    "input_tokens": int,
    "output_tokens": int,
    "total_tokens": int,
    "input_token_details": {
        "cache_read": int,      # Cached tokens read
        "cache_creation": int,  # Tokens written to cache
    },
    "output_token_details": {
        "reasoning": int,       # Reasoning tokens (o1/thinking models)
    },
}

Return Value

calculate_cost() returns a CostResult:

{
    "cost": 0.0105,           # Total cost in USD
    "currency": "USD",
    "breakdown": {
        "input_cost": 0.003,
        "output_cost": 0.0075,
        "cache_read_cost": 0.0,      # If applicable
        "cache_creation_cost": 0.0,  # If applicable
    },
    "pricing_used": {
        "input_per_mtok": 3.0,
        "output_per_mtok": 15.0,
        "batch_applied": False,
        "long_context_applied": False,
    },
}

License

MIT