LLM API Prices

Up-to-date list prices for the OpenAI, Anthropic and Google Gemini APIs. Every price is a machine-readable record copied from the provider's own pricing page, with its source and the date it was checked.

• One dataset, four ways to use it: an MCP server for AI assistants (mcp/), plus data/prices.json (with a JSON Schema), data/prices.csv, and a dependency-free Python package.
• Everything that changes the bill: standard, cached-input and batch rates, cache-write prices, long-context surcharges and announced future price changes.
• History: a dated snapshot for every check in data/snapshots/, and a sourced price change log.

Maintained by AiGanak. The same data powers the free LLM API pricing calculator and the LLM price change log.

Current prices

USD per million tokens, standard tier, text. Checked 2026-11-02.

¹ Announced price change: Gemini 4 Argon: $4 input / $20 output from 2026-12-01; Gemini 3.8 Flash: $1.50 input / $7.50 output from 2027-01-01.

Per-model detail, worked examples and head-to-head comparisons: aiganak.com/llm-api-pricing.

Language token tax

The same text costs a different number of tokens in each language, and every model family tokenizes differently. data/token-tax/ holds a 12-message business corpus in English and 22 other languages, the official token counts per model, and the counting script. Selected results (tokens as a multiple of English on the same model, measured 4 November 2026):

Full index for 23 languages, with a free checker for your own text: aiganak.com/language-token-tax.

Quick start

Use the JSON directly

No install needed. Fetch the latest file from GitHub or the jsDelivr CDN:

curl -s https://raw.githubusercontent.com/AiGanak/llm-prices/main/data/prices.json
curl -s https://cdn.jsdelivr.net/gh/AiGanak/llm-prices@main/data/prices.json

const res = await fetch("https://cdn.jsdelivr.net/gh/AiGanak/llm-prices@main/data/prices.json");
const { models } = await res.json();
const terra = models.find((m) => m.id === "gpt-6.1-terra");
console.log(terra.pricing.standard); // { input: 1, cached_input: 0.05, output: 5 }

Pin a dated version for reproducible results: .../llm-prices@v2026.11.02/data/prices.json.

Python

pip install "git+https://github.com/AiGanak/llm-prices"

import llm_prices

# Cost of one request: 6,000 prompt tokens (4,000 read from cache) and a 500-token answer
llm_prices.cost("claude-sonnet-5-5", input_tokens=6_000, output_tokens=500, cached_tokens=4_000)
# 0.0094

# Half price for work that can wait
llm_prices.cost("gpt-6.1-sol", 20_000, 800, batch=True)

# Prices on a future date, including announced changes
llm_prices.cost("gemini-4-argon", 2_000, 300, on="2026-12-01")

# The same request on every model, cheapest first
for model, usd in llm_prices.compare(input_tokens=2_000, output_tokens=300)[:5]:
    print(f"{model.name:28} ${usd:.5f}")

The package has no dependencies and works offline: the data ships inside it. llm_prices.CHECKED tells you when the prices were last checked.

Command line

$ llm-prices list --provider anthropic
$ llm-prices cost claude-opus-5-5 --input 20000 --output 800 --requests 100000
$ llm-prices compare --input 2000 --output 300 --cached 1500

In your AI assistant (MCP server)

Ask Claude, Cursor or any MCP client what a workload costs, which model is cheapest, or what the token tax is for a language. See mcp/ for the server and setup:

{ "mcpServers": { "aiganak-llm-cost": { "command": "npx", "args": ["-y", "@aiganak/llm-cost-mcp"] } } }

Data format

Each model record in data/prices.json:

{
  "id": "gpt-6-astra",
  "provider": "OpenAI",
  "name": "GPT-6 Astra",
  "tier": "flagship",
  "status": "active",
  "pricing": {
    "standard": { "input": 10, "cached_input": 1, "output": 50 },
    "batch": { "input": 5, "cached_input": 0.5, "output": 25 },
    "cache_write": 12.5,
    "long_context": {
      "threshold_tokens": 272000,
      "standard": { "input": 20, "cached_input": 2, "output": 75 },
      "note": "Prompts over 272K input tokens cost 2x input and cache rates and 1.5x output for the whole request."
    }
  },
  "scheduled_changes": [],
  "source_url": "https://developers.openai.com/api/docs/models/gpt-6-astra",
  "checked": "2026-11-02"
}

The full contract is schema/prices.schema.json (JSON Schema 2020-12). Breaking changes to the format bump schema_version and are announced in the changelog.

Methodology

1. Primary sources only. Every price is copied by hand from the provider's own pricing or model page, never from third-party aggregators. Each record links to its source.
2. Checked weekly, and the same day a provider announces a change. Each check updates checked, adds a snapshot in data/snapshots/, and tags a release (vYYYY.MM.DD).
3. Validated in CI. Every change must pass the JSON Schema, unit tests for the cost calculator, and a check that the CSV, package data and this README were regenerated from the JSON.
4. Scope. Text tokens on the standard (pay-as-you-go) tier. Regional endpoints, priority tiers, enterprise discounts, image, audio and tool fees (such as web search) are not included. Cache storage fees (Gemini) are noted in the change log but not modelled.

Prices can change at any time. Always confirm on the provider's page before making a purchasing decision.

Get notified when prices change

• Watch this repository (Custom → Releases) to get an email for every new dated release.
• Or sign up for free LLM price change alerts: one email when a provider changes a price, nothing else.

Contributing

Spotted a price that has changed? Open an issue with a link to the provider's page. Pull requests should edit data/prices.json (and data/changes.json), then run:

python scripts/build.py
python -m pytest

See CONTRIBUTING.md for details.

Citation

If you use this dataset in research or a publication, please cite it (GitHub's Cite this repository button uses CITATION.cff):

@misc{aiganak_llm_prices,
  title  = {LLM API Prices: list prices for OpenAI, Anthropic and Google models},
  author = {{AiGanak}},
  year   = {2026},
  url    = {https://github.com/AiGanak/llm-prices}
}

License

• Data (data/, schema/): Creative Commons Attribution 4.0. Use it anywhere, including commercially, with a link back to this repository or aiganak.com/llm-api-pricing.
• Code (src/, scripts/, tests/): MIT.

Model and company names are trademarks of their owners. This project is independent and not affiliated with OpenAI, Anthropic or Google.

About AiGanak

AiGanak is an AI systems studio. We help teams cut LLM spend without losing quality: free tools like the LLM Bill Analyzer and self-host vs API calculator, a fixed-price LLM Cost Report, and hands-on cost audits. We also build custom small language models for private deployment.