Free LLM Performance Tool
Compare response times between OpenAI, Anthropic, Google, and other LLM APIs. Enter your measured TTFT (time to first token) values and benchmark against industry standards. Identify which chat API performs fastest for your use case. No login required.
Large Language Model (LLM) APIs have fundamentally different latency profiles than traditional REST APIs. The key metric is Time to First Token (TTFT) — the time before the first character of the response starts streaming. For real-time chat applications, TTFT determines perceived responsiveness far more than total generation time.
A TTFT under 500ms feels fast to users even if total generation takes 8-10 seconds, because streaming creates the perception of immediate response. These are typical latency values for each major provider measured from US regions with normal load conditions:
| Provider / Model | Typical TTFT | TTFT Range | Streaming | Notes |
|---|---|---|---|---|
| OpenAI GPT-4o | 300–600ms | 150ms–2s | ✓ Yes | Varies significantly with load |
| OpenAI GPT-4 Turbo | 500–1200ms | 300ms–3s | ✓ Yes | Larger model, higher latency |
| Anthropic Claude 3.5 Sonnet | 250–500ms | 150ms–1.5s | ✓ Yes | Generally fast TTFT |
| Anthropic Claude 3 Opus | 400–900ms | 200ms–2s | ✓ Yes | Highest quality, higher latency |
| Google Gemini 1.5 Pro | 400–800ms | 200ms–2s | ✓ Yes | Strong on long context |
| Google Gemini 1.5 Flash | 200–400ms | 100ms–1s | ✓ Yes | Optimized for speed |
| Mistral Large | 300–700ms | 150ms–1.5s | ✓ Yes | European hosting option |
| Meta Llama 3 (self-hosted) | 50–500ms | Varies widely | ✓ Yes | Depends entirely on hardware |
Use the comparison tool above to enter your actual measured TTFT values and see how your chat API performance compares to industry averages.
Chat API latency is the total time elapsed from when you send a prompt to when the API returns a complete response. For LLM APIs that support streaming, TTFT (Time to First Token) is the critical metric — this is the time before the first character appears in the response stream.
TTFT is what users perceive as "responsiveness." A chat application with 300ms TTFT feels snappy even if the full response takes 30 seconds, because the first word appears immediately. This is why all major LLM providers optimize for low TTFT rather than total response time.
Chat API latency includes several components: network propagation (10-50ms depending on region), DNS lookup and connection setup (5-20ms), API server routing and request queuing (variable), model inference time (the bulk of latency, 200-700ms), and response streaming transfer (typically negligible due to streaming).
Unlike REST APIs which target under 100ms, Chat API TTFT thresholds are much higher because language model inference is computationally intensive. These industry benchmarks reflect what's acceptable for real-time chat applications:
Excellent (under 300ms TTFT)
Feels instant to users. State-of-the-art performance. Users perceive no lag between sending a prompt and seeing the first response token. Target for high-end chat applications.
Good (300–800ms TTFT)
Acceptable for most chat applications. Users notice a slight pause but don't find it frustrating. Good balance between latency and model quality.
Acceptable (800ms–2s TTFT)
Noticeable delay but workable for non-realtime applications. Consider for cost optimization where latency isn't critical.
Slow (2–5s TTFT)
Frustrating delay. Users expect a response to start arriving sooner. Should trigger optimization — either model switching or architecture changes.
Critical (over 5s TTFT)
Unacceptable for interactive chat. Requires immediate investigation and remediation. Usually indicates API overload, wrong region selection, or misconfiguration.
GPT-4o, Claude, and Gemini have different latency profiles. Compare TTFT to pick the fastest for your use case.
Faster models (Gemini Flash, GPT-4o Mini) have lower TTFT. Compare to find the speed vs quality tradeoff.
Measure actual TTFT and compare to provider benchmarks. If you're slower than normal, investigate network or caching.
Track TTFT monthly to catch provider degradation or identify usage-based slowdowns as load increases.
API latency is the time it takes for an API to send a request and receive a response from a server. Low API latency is essential for fast, reliable applications, improving user experience and system performance. Factors such as network speed, server processing, and API optimization directly affect latency in web applications, cloud services, and real-time platforms.