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capy-flash v0.7.4扩展本地Qwen3.8推理

AI 总结

capy-flash v0.7.4是面向Qwen3.8-27B和Qwen3.8-Flash-Next的独立本地推理引擎,围绕NVIDIA NVFP4量化和多GPU张量并行设计。作者称新版扩大了单GPU支持范围,加入持久化上下文缓存和更快的长提示处理,并兼容Claude Code、Codex CLI与OpenCode;文中还公布了本地吞吐基准,但尚未经过独立验证。

深度见解

该版本为RTX 50系列硬件上的Qwen3.8本地推理提供了持久化长上下文会话和智能体客户端集成选项。

It's been a few releases since my last post, so here is where capy-flash is now. It's my own engine for two models, Qwen3.8-27B and Qwen3.8-Flash-Next. It started as my ninfer-tp2 fork of NInfer, which added tensor parallel over PCIe, but at this point it's an engine of its own and very little of the original is left.

What it's for

Two RTX 50 cards on Linux. Tensor parallel across both, and for Flash-Next a VRAM expert cache shared by the two cards, with the misses computed on the CPU. Everything is tuned on one box: 2× RTX 5070 Ti 16 GB, Ryzen 9 9900X, 96 GB DDR5. It was born specifically for the NVFP4 Nvidia quantisation.

It also runs on smaller setups, so more people can try it: one 16 GB card (5060 Ti and up), Flash-Next with 64 GB of RAM, mixed pairs like a 5070 Ti with a 5060 Ti. People have posted numbers from 2× 5080, 2× RTX PRO 4000 Blackwell and 2× 5060 Ti in the issues. It runs on Windows too, through WSL2 or Docker. Two cards there are slower than on Linux, and a native Windows port is in progress.

#capy-flash v0.7.4#Qwen3.8-27B#Qwen3.8-Flash-Next#NVIDIA NVFP4#NVIDIA RTX 50 Series#Claude Code#Codex CLI#OpenCode#Strata#NInfer

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