Local AI · Recipe · 1× DGX Spark

DeepSeek-V4.1-Flash on 1× DGX Spark

DeepSeek-V4.1-Flash on 1× DGX Spark: 17.1 tok/s according to github.com (dataset as of Nov 3, 2026).

by 0xBakeer

17.1tok/sEveryday

1 request, story prompt, with DSpark (per recipe)

Source: github.com
Intelligence (original model) · Artificial Analysis40with thinkingno thinking 25

≤ 3 bit: quantization may cost quality

Engine

Engine
eigene PyTorch-Engine + Triton-Kernel v0.5.0-wip
Quantization
FP4-Experts (Checkpoint) bzw. CB3 3-bit Codebook für resident set
Model family
DeepSeek-V4.1-Flash
Context
262,144
Parameters
510 GB on disk, 384 Experts/Layer, 6 aktiv
Creator
0xBakeer
GitHub stars
120
Repo updated
Sep 24, 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)17.1 tok/sLong story temp 0.7 Source 
  • Peak (decode)36.6 tok/sHTML-Game, v0.4.0-wip; README markiert 44-%-Arena als nicht zuverlässig Source 

Prefill by context

What you need

Hardware
1 × NVIDIA DGX Spark (GB10)
Engine
eigene PyTorch-Engine + Triton-Kernel v0.5.0-wip
Context
262,144 tokens

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
  • Work in progress

Sources

Related recipes

8× DGX Spark
74tok/sEveryday

1 request, generation at 32K context (speed table, ring of eight), thinking on, high, with DSpark (per recipe); experimental profile Source 

  • Custom kernel required
  • Experimental

Stock-Checkpoint FP8/MXFP4 (DeepSeek)vLLM (local-inference-lab Fork) via SparkRing (SIRCL-Collectives, switchless RDMA ueber ConnectX-7), Image Release 2026.10.2Weights Repo Updated Nov 2, 2026

Details

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