LLM Latency Estimator

TTFB
810ms
Time to first byte
Generation
833ms
Token generation
Total Latency
1.6s
End-to-end
Speed
120
tokens/sec
UX Recommendation
Show spinner or skeleton
Streaming first byte at 810ms, complete at 1.6s

Model Comparison

Model ▴▾Provider ▴▾TTFB ▴▾Generation ▴▾Total ▴tok/s ▴▾UX Hint
gemini-2.0-flashGoogle130ms400ms530ms250Spinner
gemini-2.5-flashGoogle160ms500ms660ms200Spinner
gpt-4.1-miniOpenAI210ms588ms798ms170Spinner
claude-haiku-3.5Anthropic310ms556ms866ms180Spinner
gpt-4o-miniOpenAI260ms667ms927ms150Spinner
gpt-4.1OpenAI510ms909ms1.4s110Spinner
gemini-2.5-proGoogle710ms769ms1.5s130Spinner
mistral-largeMistral510ms1.0s1.5s100Spinner
llama-3.3-70bMeta410ms1.1s1.5s90Spinner
gpt-4oOpenAI610ms1.0s1.6s100Spinner
claude-sonnet-4Anthropic810ms833ms1.6s120Spinner
deepseek-v3DeepSeek810ms1.7s2.5s60Stream
deepseek-r1DeepSeek1.5s2.0s3.5s50Stream
claude-opus-4Anthropic2.5s1.4s3.9s70Stream

Estimates based on typical API latencies. Actual performance varies by load, region, prompt complexity, and provider infrastructure. TTFB includes additional 10ms for 500 input token processing overhead.

What This Tool Does

LLM Latency Estimator is built for deterministic developer and agent workflows.

Estimate time-to-first-token, generation time, and total latency for any AI model. Get UX recommendations for spinners, streaming, and background jobs.

Use How to Use for execution steps and FAQ for constraints, policies, and edge cases.

Last updated:

This tool is provided as-is for convenience. Output should be verified before use in any production or critical context.

Agent Invocation

Best Path For Builders

Browser workflow

Runs instantly in the browser with private local processing and copy/export-ready output.

Browser Workflow

This tool is optimized for instant in-browser execution with local data handling. Run it here and copy/export the output directly.

/llm-latency-estimator/

For automation planning, fetch the canonical contract at /api/tool/llm-latency-estimator.json.

How to Use LLM Latency Estimator

  1. 1

    Select a model

    Choose from 14+ models across OpenAI, Anthropic, Google, Meta, DeepSeek, and Mistral. Each has different speed characteristics.

  2. 2

    Enter token counts

    Set the expected input token count (your prompt) and output token count (the model's response). Use the quick presets for common scenarios.

  3. 3

    Read the latency estimate

    See the estimated time-to-first-token (TTFB), generation time, and total latency. The UX recommendation badge tells you whether to stream, show a spinner, or use a background job.

  4. 4

    Compare across models

    The model comparison table shows how all models perform for your specific input and output sizes, sorted by total latency from fastest to slowest.

Frequently Asked Questions

What is LLM Latency Estimator?
LLM Latency Estimator predicts time-to-first-token, generation time, and total response latency for AI models based on input and output token counts. It includes UX recommendations for how to handle the wait time.
How accurate are the latency estimates?
Estimates are based on published benchmark data and typical API performance. Actual latency varies with server load, network conditions, and prompt complexity, but estimates are useful for UX planning.
Is LLM Latency Estimator free?
Yes. Completely free with no account or sign-up required.
Does it send data to a server?
No. All calculations use static benchmark data in your browser.
What UX recommendations does it provide?
Based on estimated latency: under 500ms suggests no loading indicator needed, 500ms-2s suggests a spinner, 2-10s suggests streaming the response, and over 10s suggests a background job with notification.