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OpenAI API

OpenAI's developer API for calling its language models, billed per million tokens with separate input, cached-input and output rates.

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Overview

The OpenAI API lets developers call OpenAI models from their own applications and is billed by token usage. Each model has separate rates for input and output tokens, plus a lower rate for cached input on most models.

The pricing page lists several model families; the rates recorded here are the Standard tier at short context (up to 272K tokens). Long-context requests are priced higher.

Pricing

Usage-based pricing

Usage-based rates

Usage-based rates as listed by the vendor. Each rate shows its currency, unit and billing basis.
ItemRateDetailsSource and check date
gpt-6-astra, inputUSD 10 per 1M input tokensCached input shown as $1.00 per 1M tokens. Standard tier, up to 272K context.Source for gpt-6-astra, input (opens in a new tab)Checked October 24, 2026
gpt-6-astra, outputUSD 50 per 1M output tokensStandard tier, up to 272K context.Source for gpt-6-astra, output (opens in a new tab)Checked October 24, 2026
gpt-6.1-sol, inputUSD 2 per 1M input tokensCached input shown as $0.10 per 1M tokens. Standard tier, up to 272K context.Source for gpt-6.1-sol, input (opens in a new tab)Checked October 24, 2026
gpt-6.1-sol, outputUSD 10 per 1M output tokensStandard tier, up to 272K context.Source for gpt-6.1-sol, output (opens in a new tab)Checked October 24, 2026
gpt-6-luna, inputUSD 0.10 per 1M input tokensCached input shown as $0.01 per 1M tokens. Standard tier, up to 272K context.Source for gpt-6-luna, input (opens in a new tab)Checked October 24, 2026
gpt-6-luna, outputUSD 0.50 per 1M output tokensStandard tier, up to 272K context.Source for gpt-6-luna, output (opens in a new tab)Checked October 24, 2026

Prices checked on October 24, 2026 from the vendor's official page. Vendors change prices; confirm before buying. How we check prices. Official pricing page (opens in a new tab)

Who it's for

Developers and companies building applications on large language models.

Pros and limitations

Limitations

  • Long-context (>272K) requests cost more than the rates recorded here
  • Output tokens cost several times more than input tokens

Tags

How this page was researched

This page is based on desk research of the vendor's public pages and documentation. SIDAN Stack has not tested this product hands-on. How we research. Last verified: October 24, 2026.

Sources

Alternatives to OpenAI API

Anthropic Claude API logo

Anthropic Claude API

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Anthropic's developer API for the Claude model family, billed per million tokens with separate input, output and prompt-caching rates.

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Hugging Face Hub is a platform for hosting and sharing machine learning models, datasets and demo apps (Spaces) in Git-based repositories. It offers model and dataset cards, a dataset viewer, Inference Providers for serverless model calls, Inference Endpoints for dedicated deployments, Spaces hardware including ZeroGPU, and organization features such as SSO, audit logs and storage regions on Team and Enterprise plans.

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Mistral AI API logo

Mistral AI API

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Mistral AI's developer API (Studio) for its language, OCR, speech, embedding and moderation models, billed per token, per page or per minute depending on the service, with batch and cached-input discounts.

Usage-based pricing

Pinecone logo

Pinecone

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Pinecone is a managed vector database for AI applications. Serverless indexes support dense, sparse, full-text and hybrid search with metadata filtering, namespaces for multi-tenancy, integrated embedding and reranking models, backups and dedicated read nodes. Pinecone Assistant adds a managed RAG service. A free Starter plan is available; paid plans bill on storage, read and write units.

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Guides and reviews mentioning OpenAI API

Tutorial

How to Compare AI API Pricing: Tokens, Units and Hidden Costs

To compare AI API pricing, estimate input, output and cached-input tokens per request, copy each model's per-million-token rates with their tier and context band, multiply by monthly volume, apply only documented batch and caching discounts, and check the result against the provider's rate limits and spend caps. This tutorial walks through the method with verified OpenAI and Anthropic rates as listed on 24 October 2026 and an illustrative worked example.

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