Why Are Response Times So Slow When Using the Assistants API?

Performance Considerations with the Assistants API

The behavior you're observing isn’t necessarily an indication that the API is broken. There are a few factors that can contribute to response delays:

• Streaming Response Duration:
  The API supports streaming responses and sets a maximum duration (for instance, a 30‑second cap is commonly used). This means that even for simple prompts, there might be inherent waiting times as the API processes and streams back the result.

• Complexity of Processing:
  More involved queries typically trigger additional internal processing (like tool executions or multiple message steps), which can naturally extend the response time to around 30 seconds.

• Underlying Processing Latency:
  The use of conversation threads and streaming, as shown in the backend integration (for example, via the /app/api/assistant/route.ts endpoint), inherently introduces some latency. This is especially true when actions like handling “requires_action” statuses and submitting tool outputs are part of the conversation flow.

It is recommended to review your integration setup and logs to ensure there isn’t any additional delay or unexpected behavior from your side. However, the described response times are consistent with how the streaming and threaded processing are designed to work with the Vercel AI SDK.

If you have further detailed concerns or if the delays seem to exceed these operational parameters consistently, checking for updates or reaching out through the official support channels might help clarify whether any changes on the API side could have an impact.