Streaming vs Non-Streaming

In text generation APIs, streaming delivers tokens incrementally over an open HTTP or WebSocket connection, whereas non-streaming waits until the full completion is ready before sending a single response.

  Latency Comparison

  Benefits of Streaming

1. Faster perceived responsiveness (chat UX).
2. Enables cancellation mid-generation, saving cost.
3. Allows progressive rendering on front-end.

  Downsides of Streaming

• More complex client code to handle partial messages.
• HTTP/2 or WebSocket required; serverless edge functions may not support upgrades.
• Harder to calculate exact token usage upfront for billing.

  Design Trade-offs

• Streaming benefits long outputs; for short <100-token replies, gap is minimal.
• Non-streaming simplifies retry logic; streaming reconnections may duplicate text.
• Output-format constraints (JSON) risk partial invalid structures when streamed.

  Current Trends (2025)

• gRPC bidirectional streaming adopted for mobile SDKs with built-in flow-control.
• Server push compression (Brotli) cuts bandwidth 30 % for large multi-modal streams.
• Estimation headers (X-Projected-Tokens) give early cost hints before stream ends¹.

  Implementation Tips

1. Flush tokens every ~40 ms to match typing speed but avoid network overhead.
2. Send an explicit done flag in the final frame.
3. Buffer last two tokens on client side to ensure sentence boundaries before vocalization.

  References

1. OpenAI Engineering Blog, Streaming LLM Responses at Scale, 2025. ↩