Vol. I · No. 1Edition: MorningEst. 2026AboutSearchRSS

The Sand Paper

Finding grains of sand with grains of sand.
A Journal of Intelligence Transfer
Models & Hardware

TensorFold Beats SGLang on DeepSeek-1017 Across Three Sparks

108.6 against 68.3 tok/s at four sessions, with 95.2% on a 133-task German benchmark.

One cluster, one quant family, two engines: a rare like-for-like on three Sparks.

@HandwerkAiLab ran DeepSeek-V4.1-Flash-1017 on three DGX Sparks at tensor-parallel 3, comparing TensorFold by @ashxhart with SGLang. The TensorFold side used @easthambuilds’ 3.5 bpw EXL3 quant.

MeasureTensorFoldSGLang
Four sessions, tok/s108.668.3
16K agent wait11.8 sAbout 20 s
Source: @HandwerkAiLab, Oct. 24. He gives TensorFold up to 242.9 tok/s across four streams.

On quality, the build scored 95.2% on his 133-task DACH-Bench, a German and EU benchmark, and 97.5% with thinking on. In an earlier reply the same day he gave the TensorFold build 74.7 tok/s, and 229.8 tok/s across four streams.

He did not post the SGLang build’s quant or a recipe, so the comparison rests on his post.

Sources

  1. @HandwerkAiLab on X · Oct 24, 4:15 AM PT
  2. @HandwerkAiLab on X · Oct 24, 1:48 AM PT
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