Local AI · Recipe · 1× DGX Spark

Qwen3.8-27B NVFP4 with SGLang on 1× DGX Spark (Weschera)

Qwen3.8-27B NVFP4 with SGLang on 1× DGX Spark (Weschera): 25.2 tok/s according to github.com (dataset as of Sep 29, 2026).

by Weschera

25.2tok/sMixed

1 request, mixed prompt set, with DFlash2 (per recipe)

Source: github.com

Intelligence (original model) · Artificial Analysisno independent value

Instructions in the README Repo

Engine: SGLang
Quantization: NVFP4 (RadixArk) + BF16-Draft; quantized lm_head-Adapter (TP=1, 256-token selector chunks, FP32 top-k — r0b0tlab-Ansatz)
Model family: Qwen3.8-27B
Context: 262,144
Parameters: 27B (dicht, hybrid Gated-DeltaNet VLM lt. Schwester-Repo)
Creator: Weschera
GitHub stars: 29
Repo updated: Aug 21, 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

Mixed (decode)25.2 tok/scontext 1024 in / 256 out · Ladder C1, Median aus 3 Source
Peak (decode)42 tok/scontext 512 in / 2048 out · Dedicated C1, Median aus 5 Runs, gate-qualified boot (Boot-Lottery-Gate MIN_TPS=39); synthetic random tokens ~ worst case für den Drafter; Block-8-Vorgänger 34.08, r0b0tlab 28.38 Source

What you need

Hardware: 1 × NVIDIA DGX Spark (GB10)
Weights: Main weightsRadixArk/Qwen3.8-27B-NVFP4 Apache-2.0
Draft modelz-lab/Qwen3.8-27B-DFlash2 Apache-2.0
Engine: SGLang
Context: 262,144 tokens

Notes

What matters before you rebuild it.

Custom kernel required

Sources

github.com/Weschera/Qwen3.8-27B-NVFP4-DFlash2-DGX-Spark/blob/main/README.md

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