OpenAI Agents API
BetaOpenAI's managed Codex harness, exposed as an API for long-running agents
OpenAI's Agents API is the runtime OpenAI itself rates lowest in integration effort of the three it compares: it exposes the managed Codex harness with durable sessions, context compaction, subagents and hosted or partner sandboxes, and charges no fee beyond tokens, tools and container time. Conditional because it is a public beta that currently offers US-only data residency and no Zero Data Retention. Right for product teams already building on the OpenAI API; wrong for workloads that require ZDR or data residency outside the US.
OpenAI runs the agent loop on its infrastructure: a managed Codex harness drives model calls, tools and sandbox commands in durable sessions
Ist es das Richtige für dich?
Gut für
- Long-running tasks where OpenAI manages the agent and saves its progress, which is the use OpenAI's runtime comparison assigns to the Agents API
- Shipping an agent without building the loop: OpenAI handles session orchestration, context compaction and recovery on its own infrastructure
- Code execution and file work in an OpenAI-hosted sandbox, in your own infrastructure, or with a partner sandbox such as E2B, Modal, Daytona or Vercel
- Extending agents with your own tools and MCP servers, plus skills loaded from the environment
- Splitting complex work across subagents, which OpenAI's docs describe as breaking work into subtasks and delegating to subagents
- Teams already on OpenAI API billing, since OpenAI says there are no additional fees beyond the tokens and tools agents use
Nicht geeignet für
- Workloads that require Zero Data Retention, which the Agents API currently does not support
- Data that must stay outside the United States, since data residency is currently supported only in the US
- Production systems that cannot absorb beta changes: it launched as a public beta and every request requires the OpenAI-Beta: agents=v1 header
- Keeping the agent loop inside your own application, a use OpenAI's runtime comparison assigns to the Agents SDK, which runs inside your application
- Budgeting from token prices alone, since OpenAI-hosted sandboxes bill separately at standard container rates
Unsere Erfahrung
Preise
Kostenpflichtig- Model usage billed at the selected model's API rates
- OpenAI tools billed at their standard rates
- OpenAI-hosted sandboxes billed at standard container rates
- Self-hosted and partner sandboxes supported
Workflow-Rezepte
Run a first agent session
Start one agent session in an OpenAI-hosted sandbox following OpenAI's quickstart
- Create an application API key in your OpenAI Platform project with api.agents.read, api.agents.write and api.responses.write
- Keep the key outside the agent's sandbox and export it as an environment variable
- Install the SDK with pip install --upgrade openai or npm install openai
- Create a session with an agent configuration, environment type openai_hosted and your input instructions, sending the OpenAI-Beta: agents=v1 header
- Stream session events, wait for agent.session.turn.completed, then check the agent's reported execution result
- Save the session_id to continue the work, or delete the session when finished
Noch keine Urteilsänderungen
Die Uhr läuft ab dem ersten Tag — Änderungen erscheinen hier, sobald sich unser Urteil weiterentwickelt.
Quellen
- OpenAI Developer Community, Introducing the Agents API and hosted sandboxes (official)Sept. 2026
- OpenAI API changelog (official)Sept. 2026
- OpenAI API docs, agents runtime comparison (official)Sept. 2026
- OpenAI Developer Pricing DocsSept. 2026
- OpenAI API docs, Agents API overview (official)Sept. 2026
- OpenAI API docs, Agents API quickstart (official)Sept. 2026
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