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 · 4× RTX 3090
DeepSeek-V4-Flash 284B UD-IQ2_M with llama.cpp on 4× RTX 3090
DeepSeek-V4-Flash 284B UD-IQ2_M with llama.cpp on 4× RTX 3090: 39.3 tok/s according to github.com (dataset as of Nov 3, 2026).
by alesha-pro
Intelligence (original model) · Artificial Analysis34with thinking
≤ 3 bit: quantization may cost quality
Engine
- Engine
- llama.cpp ds4-longctx @b001c8cd73 (2026-08-07)
- Quantization
- Unsloth UD-IQ2_M GGUF (2.56 bpw, 91 GB), fp8-KV-Kernel
- Model family
- DeepSeek-V4-Flash
- Context
- 131,072
- Parameters
- 284B MoE
- Creator
- alesha-pro
- GitHub stars
- 56
- Repo updated
- Aug 8, 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
- 4 × NVIDIA RTX 3090
- Weights
- Main weightsunsloth/DeepSeek-V4-Flash-0731-GGUF MIT
- Engine
- llama.cpp ds4-longctx @b001c8cd73 (2026-08-07)
- Context
- 131,072 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
- Custom kernel required
Sources
- github.com/alesha-pro/llama.cpp/blob/ds4-longctx/README.md
- github.com/alesha-pro/llama.cpp/blob/ds4-longctx/README.md#2026-08-06-decode-night--393--445-ts-13-prefill-untouched
- github.com/alesha-pro/llama.cpp/blob/ds4-longctx/DS4HANDOFF.md
- github.com/alesha-pro/llama.cpp/blob/ds4-longctx/scripts/ds4-prod-serve.sh
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