API Response Time Comparison
Compare API latency and response times across different LLM providers and models.
Note: These are approximate values based on typical performance. Actual latency varies by region, load, and network conditions. Values represent streaming mode performance.
How many tokens you expect in the response
| Rank | Model | Provider | First Token | Per Token | Total Time | Tokens/Second |
|---|---|---|---|---|---|---|
| #1 | Gemini 1.5 Flash | 180ms | 18ms | 9,180ms 9.18s | 54.5 tok/s | |
| #2 | GPT-3.5 Turbo | OpenAI | 200ms | 20ms | 10,200ms 10.20s | 49.0 tok/s |
| #3 | Claude 3 Haiku | Anthropic | 220ms | 22ms | 11,220ms 11.22s | 44.6 tok/s |
| #4 | GPT-4o mini | OpenAI | 250ms | 25ms | 12,750ms 12.75s | 39.2 tok/s |
| #5 | GPT-4o | OpenAI | 400ms | 45ms | 22,900ms 22.90s | 21.8 tok/s |
| #6 | Claude 3.5 Sonnet | Anthropic | 450ms | 50ms | 25,450ms 25.45s | 19.6 tok/s |
| #7 | Gemini 1.5 Pro | 480ms | 55ms | 27,980ms 27.98s | 17.9 tok/s | |
| #8 | GPT-4 Turbo | OpenAI | 500ms | 60ms | 30,500ms 30.50s | 16.4 tok/s |
Fastest Model
Gemini 1.5 Flash
9,180ms total
Avg Response Time
18773ms
Across all models
Output Tokens
500
Expected generation
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 GPT-4o mini) 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