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OpenAI Responses API vs Chat Completions

OpenAI recommends the Responses API for new projects while continuing to support Chat Completions.

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In questa pagina3 minuti di lettura
  1. Panoramica
  2. Immersione profonda
  3. Impatto strategico
  4. The Future of OpenAI Responses API vs Chat Completions
  5. Implementazione nel mondo reale
  6. Rischi e guardrail
  7. Tabella di marcia per l'implementazione
  8. Continua a esplorare
  9. Domande frequenti

Panoramica

Their request, response, tool, and conversation-state interfaces differ, so developers should choose by model support and product needs and check the official documentation as of September 26, 2026.

Immersione profonda

OpenAI’s Responses API is its recommended interface for new projects as of September 26, 2026; Chat Completions remains supported. Responses accepts input and returns a typed output list that can contain messages and tool-related items. Chat Completions accepts a role-tagged messages array and returns choices containing messages. Both APIs support text generation, and OpenAI documents function calling and structured outputs for each, but request and response schemas differ. Responses offers platform tools such as web search and file search, and its multi-turn options include previous_response_id and the Conversations API. Chat Completions does not automatically provide the same conversation history; the application generally resends the messages it wants the model to consider. State and storage are configurable, so stateful does not mean the service automatically remembers every user across calls. Check current data controls and model compatibility before relying on a feature. For a simple existing integration, Chat Completions may remain a reasonable fit when its capabilities meet the need. A new agentic workflow that needs built-in platform tools may benefit from Responses. Migration involves more than changing an endpoint: update input fields, parse output items, adapt function/tool flow, and test streaming, structured outputs, errors, and storage settings. OpenAI’s documentation should be treated as the authority for the current feature matrix. Endpoint and tool availability can vary by model, so confirm support for the exact model and project before relying on a capability.

Impatto strategico

Costo e budget

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The Future of OpenAI Responses API vs Chat Completions

OpenAI’s current documentation recommends Responses for new projects and says Chat Completions remains supported. New tools and model features can change the comparison, while legacy integrations may prioritize compatibility and a simpler message format. Recheck the migration guide, model-specific support, data controls, and SDK behavior before making an implementation choice; avoid assuming that every feature or parameter is interchangeable. Maintain a small regression set for the request and response paths your product actually uses, and clearly date any compatibility claims.

Implementazione nel mondo reale

An app using Chat Completions resends the entire conversation array on every request, while the same app on the Responses API can pass just a previous_response_id to continue a thread without resending history.

A developer wanting built-in web search adds it as a tool in the Responses API call rather than writing custom code to call a search API and manually inserting results into the message array.

A team migrating a support bot swaps their loop that manually manages message arrays for one that stores OpenAI's returned response ID and passes it back on the next turn.

A legacy integration that already has robust custom message-history logic keeps using Chat Completions rather than rewriting its state management around a new API shape.

Rischi e guardrail

  • L'ottimizzazione di un benchmark può nascondere debolezze di sistema più ampie.

  • I costi delle infrastrutture e della manutenzione sono spesso sottostimati.

  • Le lacune in termini di sicurezza e osservabilità possono aumentare man mano che i sistemi diventano più complessi.

Tabella di marcia per l'implementazione

  1. Definire obiettivi di latenza, qualità e costi prima dell'implementazione.

  2. Benchmark in condizioni di carico e dati realistiche.

  3. Monitoraggio dello strumento per errori, deriva e impatto sull'utente.

  4. Preparare percorsi di rollback e risposta agli incidenti prima della scalabilità.

Continua a esplorare

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Domande frequenti

What is OpenAI Responses API vs Chat Completions?

OpenAI recommends the Responses API for new projects while continuing to support Chat Completions. Their request, response, tool, and conversation-state interfaces differ, so developers should choose by model support and product needs and check the official documentation as of September 26, 2026.

As of the cited OpenAI documentation, how can Responses preserve conversation context across turns?

OpenAI documents explicit continuation with previous_response_id and persistent Conversation objects; state does not automatically span every arbitrary request.

What built-in capability does the Responses API offer that previously required custom implementation in Chat Completions?

The Responses API can execute tools like web search or file search server-side, which previously required developers to call an external API and manually insert results.

How does the output shape of the Responses API differ from Chat Completions?

The Responses API response object can contain multiple output items, unlike the single choices[0].message shape of Chat Completions.

What does OpenAI currently say about Chat Completions?

OpenAI’s current migration guide recommends Responses for new projects and states that Chat Completions remains supported.

What should a developer check before assuming an API feature will work with a particular model?

Endpoint availability and feature support can vary by model; current documentation is the source for compatibility.