API Response Time Comparison
Compare API latency and response times across different LLM providers and models.
| Rank | Model | Provider | First Token | Per Token | Total Time | Tokens/Second |
|---|---|---|---|---|---|---|
| #1 | Gemini 3 Flash | 170ms | 16ms | 8,170ms 8.17s | 61.2 tok/s | |
| #2 | Grok 4 Fast | xAI | 190ms | 19ms | 9,690ms 9.69s | 51.6 tok/s |
| #3 | Claude Haiku 4.5 | Anthropic | 200ms | 20ms | 10,200ms 10.20s | 49.0 tok/s |
| #4 | GPT-5 mini | OpenAI | 230ms | 22ms | 11,230ms 11.23s | 44.5 tok/s |
| #5 | Claude Sonnet 4.6 | Anthropic | 380ms | 40ms | 20,380ms 20.38s | 24.5 tok/s |
| #6 | GPT-5.1 | OpenAI | 400ms | 45ms | 22,900ms 22.90s | 21.8 tok/s |
| #7 | Gemini 3 Pro | 440ms | 50ms | 25,440ms 25.44s | 19.7 tok/s | |
| #8 | GPT-5.5 | OpenAI | 450ms | 50ms | 25,450ms 25.45s | 19.6 tok/s |
| #9 | Claude Opus 4.8 | Anthropic | 480ms | 55ms | 27,980ms 27.98s | 17.9 tok/s |
Latency Optimization Tips
- Use streaming mode to show partial results faster and improve perceived performance
- Choose models with lower latency for real-time/interactive applications
- Consider using faster models (like Gemini 3 Flash or Claude Haiku 4.5) for non-critical tasks
- Implement caching for common queries to bypass API calls entirely
- Deploy in the same region as your API provider for lower network latency
Comparing LLM latency
For anything interactive — chat, autocomplete, voice — latency matters as much as price. Two numbers drive the experience: time to first token (how long before the response starts streaming) and per-token speed (how fast the rest arrives). Smaller models are dramatically faster on both, which is why they're often the right choice for user-facing features even when a larger model is slightly more accurate.
This tool estimates the total response time for a given output length across models, so you can see the speed-versus-capability trade-off in concrete terms. Latency varies with region, server load, prompt size, and reasoning effort, so treat these as representative benchmarks rather than guarantees — but the relative ordering between models is a reliable planning guide.
How to use this tool
- Enter how many output tokens you expect the response to contain.
- Compare first-token latency, per-token speed, and total time across models.
- Favor a faster model for real-time, user-facing features; reserve slower frontier models for background reasoning.
Frequently asked questions
What is time to first token?+
The delay between sending your request and receiving the first piece of the response. It's the number users feel most in chat interfaces, because it's how long the screen sits empty before text starts appearing.
How can I make responses feel faster?+
Stream the output so text appears as it's generated, use a smaller or faster model for interactive paths, and keep prompts and outputs concise. Streaming alone makes a big perceived-speed difference.