Local AI · Recipe · 3× DGX Spark

Kimi-K3 UD-IQ1_S with SparkInfer on 3× DGX Spark

Kimi-K3 UD-IQ1_S with SparkInfer on 3× DGX Spark: 6.59 tok/s according to github.com (dataset as of Nov 3, 2026).

by vcruz305

6.59tok/sEveryday

1 request, prose prompt, no speculative decoding

Source: github.com
Intelligence (original model) · Artificial Analysis44with thinkingOriginal model's value. Heavily compressed (~0.95 bit), intelligence is likely much lower.

≤ 3 bit: quantization may cost quality

Engine

Engine
SparkInfer sparkinfer-k3 + Patches 0001–0026
Quantization
GGUF UD-IQ1_S (330 GB)
Model family
Kimi-K3
Context
—
Parameters
2.78T (HF-Card vcruz305/Kimi-K3-GGUF; HF-API moonshotai/Kimi-K3 safetensors total 2 779 931 837 184)
Creator
vcruz305
GitHub stars
9
Repo updated
Sep 13, 2026

Measurements

Every sourced value of this recipe, each with its condition and source. Bars relative to the largest value in the group.

Decode · 1 request

  • Everyday (decode)6.59 tok/scontext kurz (--max-ctx 4096, n-predict 64) · Freie Prosa, Kontrolle ohne Drafts; Mittel aus 2 Läufen (K=8/P8-Profil) Source 
  • Mixed (decode)9.79 tok/scontext kurz (--max-ctx 4096, n-predict 64) · Arithmetisches Mittel aus 4 Einzelanfragen nacheinander (gemischtes Prompt-Set), ein Prozess Source 
  • Peak (decode)12.5 tok/scontext kurz (--max-ctx 4096, n-predict 64) · Strukturiert/repetitiv (structured generation), K=8/P8; laut Autor keine Aussage für Chat/Prosa Source 

What you need

Hardware
3 × NVIDIA DGX Spark (GB10)
Weights
Engine
SparkInfer sparkinfer-k3 + Patches 0001–0026

Notes

What matters before you rebuild it.

  • ≤ 3 bit: quantization may cost qualityAt 3 bit and below the model may answer noticeably worse than the original. The intelligence number refers to the original.
  • Experimental
  • Very heavy quantization
  • Multiple nodes
  • License unclear

Sources

Related recipes

3× DGX Spark
31.3tok/sEveryday

1 request, prose prompt, with DSpark (per recipe) Source 

Intelligence45with thinking
  • Custom kernel required
  • License unclear

EXL3 2,75 bpw Ø (Experten 2–4 bit), 4-bit dense, BF16 sonst, FP4 KV (Default CP=1)TensorFold v0.6.0 + 110 Patches, Image ghcr.io/miaai-lab/glm-5.3-exl3-3x-dgx-sparks-tensorfold:v0.6.0-4f3223245926, DSpark + Copy-Drafts, Context Parallelism, RoCEWeights Repo Updated Oct 4, 2026

Details

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