The fastest way to run Qwen3.8-Flash-Next on Strix Halo (gfx1151)
The Open Source Strix Halo AI engine. Qwen 3.8 Flash Next Q4_K_XL: 1,801.01 pp, 73.17 tg single user, 194.37 tok/s 8 users; Qwen 3.8 27B Q4_K_XL: 656.33pp, 70.56tg tok/s single user with DFlash2
A close-to-metal Python API for programming AMD Ryzenβ’ AI NPUs (AI Engines), built on an open-source MLIR-based compiler toolchain.
Qwen 3.8 27B ROCmFP4 on AMD Strix Halo (Ryzen AI Max+ 395). Up to 36 tok/s via MTP Speculation, TurboQuant & Mesa RADV Wave64.
Performance-tuned llama.cpp for AMD Strix Halo (gfx1151): FA + MoE-prefill fixes with a bundled current Mesa driver. Vulkan and HIP; portable dir, Docker, and distrobox.
The fastest way to run Qwen3.8 27B on Strix Halo (gfx1151)
High-performance Lemonade alternative for AMD Strix Halo & Radeon β latest MoE models (Ling-3.0-Flash, Qwen 3.8 Flash Next, Ornith 1.5), bleeding-edge RDNA 3.5 Wave64/ROCmFP4 kernels, and silicon-tuned profiles.
Active and open development fork of FastFlowLM.
A two-day, non-expert guide to running local LLMs on an AMD Strix Halo (Ryzen AI Max+ 395) box β full ~120GB memory pool, ROCm backend, NPU in parallel via FastFlowLM, one OpenAI-compatible endpoint.
WHIRL (Windows HIP Inference for RDNA LLMs): native Windows C++/HIP LLM inference engine for the AMD Ryzen AI Max+ 395 (Radeon 8060S) and Radeon AI PRO R9700. Unzip and run, only the AMD driver.
Local AI coding agent harness for AMD Strix Halo (Ryzen AI Max+ 395): Qwen3.8 125B on the iGPU, NPU side-jobs, crash recovery, logged benchmarks. Works with any OpenAI-compatible engine; cloud optional.
Run LLMs and Ollama Qwen across AMD XDNA1 NPU, CPU, and GPU on Ryzen AI Linux systems.