4× DGX Spark
87.7tok/sEveryday
1 request, prose prompt, with DSpark (per recipe) Source
Intelligence40with thinkingno thinking 25
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
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
Prefill by context
What you need
- Hardware
- 1 × NVIDIA DGX Spark (GB10)
- Weights
- Main weightsdeepseek-ai/DeepSeek-V4.1-Flash MIT
- 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
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