Local AI · Recipe · 1× RTX 5090

Qwen3.8-Flash-Next 125B-A10B UD-Q2_K_XL with llama.cpp on 1× RTX 5090

Qwen3.8-Flash-Next 125B-A10B UD-Q2_K_XL with llama.cpp on 1× RTX 5090: 59.7 tok/s according to huggingface.co (dataset as of Nov 3, 2026).

by notwitcheer

59.7tok/sPeak

1 request, synthetic prompt

Source: huggingface.co
Intelligence (original model) · Artificial Analysis40with thinking

≤ 3 bit: quantization may cost quality

Engine

Engine
llama.cpp
Quantization
GGUF UD-Q2_K_XL (78.9 GB), Experten teilw. im RAM
Model family
Qwen3.8-Flash-Next
Context
—
Parameters
125B MoE / 10B active
Creator
notwitcheer
GitHub stars
46
Repo updated
Nov 1, 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

  • Peak (decode)59.7 tok/scontext tg128 · --n-cpu-moe 22, 28.5 GiB VRAM Source 

Prefill by context

What you need

Hardware
1 × NVIDIA RTX 5090
Weights
Engine
llama.cpp

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.
  • Partly in system RAM
  • License unclear

Sources

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Details

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