llmcalc 0.1.1

Calculate LLM token costs from llmlite pricing data

llmcalc

llmcalc is a typed Python library and CLI for estimating LLM token costs.

Install

pip install llmcalc

What It Does

• Resolves model pricing from an upstream pricing source.
• Calculates input, output, and total costs with deterministic decimal rounding.
• Provides a small Python API and a CLI.
• Caches pricing data locally (default TTL: 43200 seconds).

Cost Formula

total = (input_tokens * input_price_per_token) + (output_tokens * output_price_per_token)

Pricing is pulled from llmlite model pricing data and cached locally.

Python Quickstart

from llmcalc import cost

result = cost(
    model="gpt-5.1",
    input_tokens=1200,
    output_tokens=800,
)
if result is not None:
    print(result.total_cost, result.currency)

You can also calculate from usage-style objects via usage(...). Async variants are available as cost_async(...) and usage_async(...).

CLI Quickstart

# cost quote from token counts
llmcalc quote --model gpt-5.1 --input 1200 --output 800

# inspect per-token pricing for one model
llmcalc model --model gpt-5.1 --json

# clear local cache
llmcalc cache clear

# show version
llmcalc --version
llmcalc -v

Configuration

• LLMCALC_CACHE_TIMEOUT: cache TTL in seconds (default 43200)
• LLMCALC_PRICING_URL: override pricing source URL
• LLMCALC_CURRENCY: fallback currency label if upstream omits currency

Maintainers

Contributor workflows and release validation live in AGENTS.md.