OpenAI API
Verified Oct 2, 2026 ActivePay-per-token developer API for OpenAI's text, reasoning, image, speech and embedding models, with tools, batch jobs and fine-tuning.
Listed on EffectHub ·
Pricing
- Pricing model
- Paid
Pay as you go, priced per million tokens and varying by model, input versus output, cached input and processing tier (standard, batch, flex, fast). Batch usage is discounted around half for many models and regional data-residency endpoints add a 10% uplift. No single starting price: it depends entirely on the model.
Use tool ↗About OpenAI API
The OpenAI API is the developer platform for calling OpenAI models from your own software. Through the Responses API you get text and reasoning models with streaming, structured outputs and tools such as function calling, web search, file search, computer use and MCP connections. Other endpoints cover embeddings, image generation and editing, speech-to-text and text-to-speech, a realtime voice interface, a batch API and model fine-tuning. Billing is per token, with separate rates per model, cached input, batch and service tier.
- Platforms
- API · Web
- API
- Yes
- Last verified
- Oct 2, 2026
Verified sources
- API capabilities: Responses API, tools, realtime, images, embeddings, fine-tuning, batchdevelopers.openai.com ↗
- Token-based pricing with batch discounts, caching and a 10% regional upliftdevelopers.openai.com ↗
- OpenAI API announced June 2020openai.com ↗
- Developer platform entry point (blocks automated fetches with a JavaScript challenge)platform.openai.com ↗
Is OpenAI API legit?
We don’t label tools safe or unsafe. Below are the records we checked ourselves, each with the date we read it.
- Last checked
- Oct 2, 2026The site answered
- On the market since
- 2020The vendor's own material, read by us
- Operated by
- OpenAI, United StatesOur research, card verified Oct 2, 2026
Pros & cons of OpenAI API
The OpenAI API is a common entry point for building on hosted frontier models, with a broad set of endpoints under one account. Costs scale with tokens and model choice, so budget by measuring real traffic rather than by headline rates.
Pros
- One platform covers text, reasoning, images, audio, embeddings and fine-tuning
- Built-in tools such as web search, file search, computer use and MCP connections
- Batch processing and prompt caching are listed as ways to lower token costs
- Data-residency endpoints are available for regional compliance needs
Cons
- Per-token billing makes monthly cost hard to predict without usage monitoring
- Rates differ across many models, tiers and context lengths, which complicates comparison
- No flat-rate plan exists, so the bill is open-ended unless you set limits yourself
Best for
- Developers building chat, agent, voice or retrieval features on hosted models
- Teams that want text, images, speech and embeddings from one provider
- Products that can use batch processing to cut the cost of offline jobs
Not for
- Teams that must run models entirely on their own hardware
- Buyers who want a flat monthly fee, since billing is metered by token
Watch out: Long-context requests above 272K tokens, faster processing tiers and regional endpoints are priced differently from the base rate, so a prototype's cost estimate may not carry over to production. Set spend limits and monitor usage in the dashboard.
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