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Qwen3.8-Flash-Next 176.9B UD-Q4_K_XL with llama.cpp on 1× DGX Spark

Qwen3.8-Flash-Next 176.9B UD-Q4_K_XL with llama.cpp on 1× DGX Spark: 32 tok/s according to github.com (dataset as of Nov 3, 2026).

by 0xBakeer

32tok/sEveryday

1 request, prose prompt, with Drafting aus dem Prompt (Edit-Setup, lt. README 'drafts its guesses from your prompt') (per recipe)

Source: github.com
Intelligence (original model) · Artificial Analysis40with thinking
Instructions in the README Repo

Engine

Engine
llama.cpp (PR #27742 @035e227) / vLLM (blazux-Container)
Quantization
GGUF UD-Q4_K_XL (edit) / nicht spezifiziert im README (longctx)
Model family
Qwen3.8-Flash-Next
Context
262,144
Parameters
176.9B (51.2B n-gram-Tabelle)
Creator
0xBakeer
GitHub stars
124
Repo updated
Sep 20, 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)32 tok/sLongctx-Setup, Prosa Source 
  • Peak (decode)88 tok/sEditing-Setup, Datei-Rewrite Source 

Time to first token

Shorter is better.

  • Prompt not stated300 mscontext short · Longctx ~0.3 s Source 

What you need

Hardware
1 × NVIDIA DGX Spark (GB10)
Engine
llama.cpp (PR #27742 @035e227) / vLLM (blazux-Container)
Context
262,144 tokens

Sources

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89.3tok/sEveryday

1 request, prose prompt, with MTP (per recipe) Source 

Intelligenceno independent value
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Details
2× DGX Spark

Qwen3.8-Flash-Next INT4-AutoRound (v5.2) with vLLM on 2× DGX Spark

by myllmbox

74tok/sEveryday

1 request, prose prompt (long story), thinking off, with MTP Source 

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Details

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