Reddit 用户分享 Qwen 3.8 Flash Next 移植评测任务
AI 总结
r/LocalLLaMA 的一名 Reddit 用户分享了用于评估 Qwen 3.8 Flash Next 的任务：把一个旧屏保移植到 Python OpenGL，同时保持完整视觉一致性。该配置以 Claude Code 作为工具框架，通过 gufo 在 Strix Halo 和 Ubuntu 26.04 上服务 Q4_K_XL 模型，并加载共享 MTP 与多模态投影模型。作者称，任务的部分内容对 128K 上下文窗口颇具挑战，图形相关任务也可能产生不一致结果，但帖子没有给出量化评分。
深度见解
该帖子提供了一个可供开发者查看或复现的具体本地推理评测配置，但单一用户来源和缺少量化报告限制了结果的解读范围。
Just want to share a task I used to evaluate the capability of Qwen 3.8 FN. The goal is to port a old screensaver (can find it on Wayback Machine) to Python OpenGL, maintaining full visual fidelity.
Tooling: Claude Code (harness) + Qwen 3.8 FN Q4_K_XL via gufo + Strix Halo + Ubuntu 26.04
Run command:
export MODEL=Qwen3.8-Flash-Next-UD-Q4_K_XL-00001-of-00004.gguf
export MTP=/run/media/user/DATA/models/huggingface/mtp-Qwen3.8-Flash-Next-shared-Q8_0.gguf
export MMPROJ=/run/media/user/DATA/models/huggingface/mmproj-Qwen3.8-Flash-Next-BF16.gguf
#./result/bin/gufo chat --model "$MODEL"
./result/bin/gufo serve llm --model "$MODEL" --speculative mtp \
--mtp-model "$MTP" \
--mmproj "$MMPROJ" \
--sessions 1 \
--context 133760 \
--max-tokens 32768 \
--prefill-chunk 4096 \
--served-model-name qwen3.8-flash-next \
--max-pending-per-client 2
Assessment:
Some parts are quite challenging with the 128K context window. Also, be mindful that graphics-related tasks (apart from running the model) may produce inconsistent results, and thus require specific measures, To keep this benchmark useful for others, I won't go into the details of the approach adopted by the AI, except to share that the task is tractable given a comparable setup. But feel free to ask by PM. submitted by /u/prusswan
[link] [comments] |
#Qwen 3.8 Flash Next#Claude Code#gufo#Strix Halo#Ubuntu 26.04#Python OpenGL