OpenAI
Usage BasedThe API behind GPT-6, from flagship reasoning to low-cost models.
Published 29 May 2026 · Last updated 2 October 2026
Scores
Popularity5/5
The most-used LLM API in the world by developer count, third-party integrations, and mindshare. ChatGPT's cultural reach directly drives API adoption. Virtually every developer tool, no-code platform, and enterprise software suite lists OpenAI as a primary integration.
Learning Curve2/5
The Chat Completions API is one of the most beginner-friendly interfaces in software — a single POST request with a messages array returns a completion. Official SDKs for Python and Node ship with comprehensive docs and hundreds of cookbook examples. The main learning curve is choosing the right model family and managing costs rather than the API mechanics themselves.
Flexibility3/5
OpenAI offers genuine breadth — five model families, fine-tuning (supervised + reinforcement), function calling, structured outputs, and real-time audio. However, all inference is cloud-only and proprietary; you cannot swap the underlying model weights, run locally, or choose your hardware. Compared to open-weight alternatives, customisation stops at fine-tuning.
Performance5/5
Leads or co-leads industry benchmarks across coding (SWE-bench), reasoning (MATH, GPQA), and instruction-following. o3 and GPT-5 are best-in-class for their respective task types as of 2026.
Portability2/5
Entirely cloud-bound; no self-hosted option. The API is proprietary — migrating to a different provider requires rewriting prompt logic, tool schemas, and API call structure. Azure and Bedrock availability reduces cloud lock-in but not provider lock-in.
About OpenAI
The OpenAI API gives developers the models behind ChatGPT and is the most widely used LLM API. The current generation is GPT-6, split into three tiers that share a 1.05M-token context window and 128K-token output: Astra, the flagship for the most demanding work; GPT-6.1 Sol, which gets close to Astra on complex coding, computer use, and professional work at a much lower price; and Luna for focused, high-volume tasks. The original GPT-6 Sol and the GPT-5 generations stay callable for existing integrations, while GPT-5.3-Codex, the former dedicated coding model, and older GPT-4 and o-series snapshots are being retired on a published schedule.
Astra was the first OpenAI model rated at the "Critical" cybersecurity capability level under the company's Preparedness Framework, and GPT-6.1 Sol carries the same rating and safeguards. The public versions refuse advanced offensive security tasks, such as generating working exploits, unless an organization is vetted through OpenAI's Trusted Access for Cyber program.
Beyond text generation, the platform covers the Responses API with built-in tools (web search, file search, code interpreter, hosted shell, and computer use), realtime and full-duplex voice models for speech-to-speech agents, image generation, transcription, embeddings, and structured outputs, plus the Agents SDK and a hosted Agents API for multi-step agents. Fine-tuning is limited to older GPT-4.1 and GPT-4o models.
Pricing is per token, with separate input, cached-input, and output rates for each model and higher rates for prompts above 272K input tokens. The Batch API and flex processing halve costs for asynchronous or latency-tolerant work, fast modes trade a higher rate for speed, prompt caching discounts repeated prefixes automatically, and the models are also offered through Microsoft Foundry and Amazon Bedrock for teams that want to stay inside one cloud.
Key Features
- GPT-6 Astra flagship: 1.05M-token context, 128K max output
- GPT-6.1 Sol: near-Astra results on coding and computer use at a lower price
- GPT-6 Luna for low-cost, high-volume workloads
- Responses API with built-in web search, file search, code interpreter, hosted shell, and computer use
- Realtime and GPT-Live voice models for low-latency speech-to-speech agents
- Image generation, transcription, embeddings, and structured outputs
- Batch API and flex processing at 50% off, plus automatic prompt caching
- Available directly, through Microsoft Foundry, and on Amazon Bedrock
Pros
- Broadest model selection of any single LLM provider, from flagship to very low cost
- Largest developer ecosystem: libraries, tutorials, integrations, and community knowledge
- 1M-token context across the GPT-6 lineup handles whole codebases and long documents in one call
- Realtime API makes production voice agents practical
- Prompt caching and the Batch API cut costs sharply for agent loops and bulk jobs
- Multi-cloud availability through Microsoft Foundry and Amazon Bedrock
Cons
- Fully proprietary: models cannot be self-hosted or audited
- Pricing is complex, with separate input, cached, output, long-context, batch, and fast-mode rates per model
- Frequent model turnover and retirement schedules require ongoing migration work
- Cybersecurity safeguards on Astra and GPT-6.1 Sol refuse some legitimate security work without vetted access
- The API surface keeps changing: the Assistants API has been removed in favour of the Responses API
- Output quality can degrade on very long contexts, so retrieval is often still needed
OpenAI Pricing
Usage Based- · $10/M input, $50/M output; cached input $1/M
- · Above 272K input tokens: $20/M input, $75/M output
- · 1.05M context, 128K max output
- · $0.10/M input, $0.50/M output; cached input $0.01/M
- · Low-cost tier for focused, high-volume tasks
- · 1.05M context, 128K max output
- · $2/M input, $10/M output; cached input $0.10/M
- · Above 272K input tokens: $4/M input, $15/M output
- · Near-Astra results on complex coding and professional work; 1.05M context
- · $2/M input, $10/M output; cached input $0.20/M
- · Earlier GPT-6 mid-tier model, still callable
- · $1.75/M input (cached $0.175/M), $14/M output
- · Agentic coding model, deprecated: removed from the API on April 1, 2027
- · Replacement: GPT-6 Sol
- · 50% off input and output tokens for asynchronous jobs
- · Applies across the current lineup, including GPT-6 Astra
- · Flex processing bills latency-tolerant requests at the same rates
- · GPT-5.6 (Sol, Terra, Luna), GPT-5.5, GPT-5.4, and GPT-5.2 stay callable for existing integrations
- · Superseded by GPT-6.1 Sol and GPT-6 Luna
- · GPT-5.1 and GPT-5.4-nano shut down April 1, 2027; original GPT-5 snapshots December 11, 2026
- · o1, o1-pro, o3-mini, o4-mini, GPT-4 Turbo, and GPT-4.1-nano snapshots shut down October 23, 2026
- · The o3 snapshot shuts down December 11, 2026
- · Migration target: the GPT-5.6 family
Tech Stacks with OpenAI
Python Dashboard Starter
ProjectEverything a beginner data scientist needs: Python + pandas for analysis, Streamlit (or Panel or Dash) for interactive apps, and PostgreSQL for structured data storage.
React + Django
ProjectReact frontend with a Django REST API backend, a popular Python full-stack combination.
Vue + FastAPI
ProjectVue.js frontend paired with FastAPI, a fast, async-ready Python API backend.
Tools Related to OpenAI
Integrates with OpenAI(17)
OpenAI's own coding agent, built and shipped by OpenAI to run its models.
OpenAI models are one of the model families Devin offers on paid plans; Devin supplies the IDE, Devin Local agent, and Agent Command Center around them.
Cursor offers OpenAI's GPT models, including the Codex-tuned variants, in its model picker for Agent and chat. Picking one manually draws on the usage included with the Cursor plan.
OpenAI is one of Zapier's most popular integrations for AI-powered automation.
n8n's first-party OpenAI node covers text generation through the Responses API, image generation and analysis, audio transcription and speech, video generation, and file handling, and OpenAI chat models plug into n8n's AI agent nodes.
OpenAI is one of Make's most used AI modules for automation scenarios.
Alternatives to OpenAI(6)
OpenAI and Google Gemini both offer tiered model families with roughly 1M-token context. Gemini accepts audio and video input natively, has a free tier in AI Studio, and ties into Google Cloud and Workspace; OpenAI has the larger developer ecosystem and third-party integration base.
Claude and OpenAI are the two leading proprietary LLM APIs, each with a tiered lineup and 1M-token context on its main models. OpenAI's platform also covers image generation, realtime voice, transcription, and embeddings; Claude outputs text only and is the model family behind Claude Code and Anthropic's computer-use tools.
DeepSeek publishes MIT-licensed open weights and runs one of the cheapest frontier-class APIs, priced at a small fraction of OpenAI's rates. OpenAI offers the broader platform, with built-in tools, voice, and image generation, and its API is not hosted in China, which matters for data-residency rules.
Muse Spark's Meta Model API follows the OpenAI chat-completions format, so trying it is a base-URL change. OpenAI has the more mature developer platform and worldwide availability; Muse Spark adds video input and a Contributor tier that trades prompts for a lower price.
Grok's API is OpenAI SDK-compatible, so switching is a base-URL change, and it adds real-time X search and Grok Imagine image and video generation. OpenAI has the larger developer ecosystem and more third-party integrations.
Meta Llama's open weights can be self-hosted, fine-tuned, and run with no per-token cost on your own hardware. OpenAI is a managed proprietary API with stronger frontier models and a wider platform (built-in tools, voice, image generation), but no self-hosting.
