How to fix: LLM responses are too slow / high latency
Last verified: June 2026· Production AI features
Where this shows up
Production AI features
The fix
- 1Stream responses so users see output immediately instead of waiting for the full completion.
- 2Right-size the model and reasoning effort per route — frontier models and high effort cost latency you may not need.
- 3Reduce input size with retrieval and caching; smaller prompts process faster.
- 4Cache repeated prompts and prewarm caches for hot paths.
- 5Parallelize independent calls instead of chaining them sequentially.
Prevent it
Measure latency by route and set per-route model/effort budgets, the same way you manage cost.
Common variations and related errors
You'll usually hit this same root cause under a few different names. Same fix.
- "high LLM latency"
- "time to first token too high"
- "p99 latency spike"
- "streaming is slow"
- "TTFT regression"
Frequently asked questions
What causes “LLM responses are too slow / high latency”?
Latency is driven by model choice, large input/output, high reasoning effort, and lack of streaming.
How do I prevent “LLM responses are too slow / high latency” from recurring?
Measure latency by route and set per-route model/effort budgets, the same way you manage cost.