Interactive Visualizer

Fast inference doesn't just make AI faster.
It changes what is possible to build.

Numbers like 40 vs 2000 tokens per second sound abstract until you watch them side by side. This page lets you feel the difference — then budget it for real agent chains.

40 tok/s — typical hosted model

2000 tok/s — fast inference stack

Feel the Speed

Same answer, two throughputs

Pick a sample completion, set each pane's speed on a log scale from 10 to 5000 tokens/sec, and press Play. Timing is simulated per token, client-side, with real elapsed clocks.

60 tok/s
elapsed 0.0stokens 0
2000 tok/s
elapsed 0.0stokens 0

Latency Budget Calculator

How long does your agent chain really take?

Agent latency multiplies: steps times tokens per step divided by throughput, plus per-step overhead. Watch each step fill on the timeline below.

real-time <1sconversational <5stolerable <30sbatch >30s

What It Unlocks

Speed tiers map to product patterns

10–100 tok/s

Single streamed chat reply. Users watch text arrive; anything multi-step feels like waiting for a build.

100–500 tok/s

Responsive copilots and inline rewrite. One tool call per turn stays conversational.

500–2000 tok/s

Instant multi-draft UI: generate five variants and let users pick. Speculative tool use — run likely branches in parallel and discard the losers.

2000+ tok/s

Whole-app regeneration on every keystroke, real-time agent swarms, and generation-as-rendering where the model output is the interface itself.

Check Your Intuition

Four quick questions

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