4× RTX PRO 6000
235tok/sEveryday
1 request, prose prompt, context 19, with DSpark (per recipe) Source
Intelligence34with thinking
- Custom kernel required
Local AI · Recipe · 2× DGX Spark
DeepSeek-V4-Flash with vLLM on 2× DGX Spark (1500k context)
DeepSeek-V4-Flash with vLLM on 2× DGX Spark (1500k context): 51 tok/s according to github.com (dataset as of Nov 3, 2026).
by drowzeys
Intelligence (original model) · Artificial Analysisno independent value
Engine
- Engine
- vLLM
- Quantization
- Release-nativ + nvfp4_ds_mla KV
- Model family
- DeepSeek-V4-Flash
- Context
- 1,500,000
- Creator
- drowzeys
- GitHub stars
- 21
- Repo updated
- Aug 17, 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
What you need
- Hardware
- 2 × NVIDIA DGX Spark (GB10)
- Weights
- Main weightsdeepseek-ai/DeepSeek-V4-Flash-DSpark MIT
- otherdrowzeys/DeepSeek-V4-Flash-DSpark-NVFP4-KV-1.5M-CTX-2xDGX-Spark Apache-2.0Access on request
- Engine
- vLLM
- Context
- 1,500,000 tokens
Related recipes
4× DGX Spark
46tok/sEveryday
1 request, prose prompt, with DSpark Source
Intelligenceno independent value
4× DGX Spark
42tok/sEveryday
1 request, prose prompt, with DSpark (per recipe) Source
Intelligenceno independent value
- Custom kernel required
3× DGX Spark
41.9tok/sEveryday
1 request, prose prompt, with DSpark (per recipe) Source
Intelligenceno independent value
- Custom kernel required
2× DGX Spark
33.2tok/sEveryday
1 request, prose prompt, with DSpark (per recipe) Source
Intelligenceno independent value
- Custom kernel required
1× DGX Spark
30.2tok/sEveryday
1 request, story prompt, prompt 18 tokens, with MTP (per recipe) Source
Intelligence34with thinking
- ≤ 3 bit: quantization may cost quality
Local AI in your company?
In a workshop we work out which models and which hardware fit your tasks, and build the first agent on your infrastructure.