Optimize prefill and speed up TTFT 10x with KV cache transfer tech. Integrated with your dedicated endpoints or GPUs to speed up inference.

Small prefill. Large-model decode.

Faster speed, higher quality.

Explore benchmarks ↗
12.6×

peak speedup

32K context · measured

Time to first token · linear scale · lower is faster

Solid: measured · Dashed: timing estimatesContext length (tokens) →
View latency values
Time to first token in seconds
ContextNativeOneTriangle
8K3.30 s0.36 s
16K7.46 s0.64 s
32K18.22 s1.45 s
64K49.82 s4.01 s
128K152.61 s12.90 s
256K517.76 s45.76 s
512K1885.73 s171.76 s
1M7172.25 s664.95 s

Measured 2026-10-24 on 4×H100 (HF forwards, bf16/FP8, p50 of 2 reps). Solid-border bars = measured transfer components; dashed border = projected (prefill quadratic, map/move linear, first-token affine fits). The projected 64K total (4,010 ms) matches an independently measured 64K run (4,013 ms). Black tick = native 128B TTFT (measured through 64K). At 1M projected: native ≈2h, transfer ≈11min.

OneTriangle prefill

Novel prefill optimizations.

Transfer KV cache from a small model to a larger one and start answering sooner. Bring it to your dedicated endpoints or GPUs.

  • Qwen
  • Mistral
  • Gemma
  • GLM
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