AMD RX 580
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- Deploying Qwen3.5 4B on a Legacy RX 580 Server
A report from 掘金 · 人工智能 documents running Qwen3.5 4B with Ollama 0.40.14 on Windows 10 using an Intel Xeon E5-2670 v2, 32 GB of memory, and an 8 GB AMD RX 580. The author exposes the model to WorkBuddy and Dify through an OpenAI-compatible API, with the Xeon serving as fallback compute at a reported prefill speed of about 54–74 tokens per second. Because the Vulkan flash-attention path produced zero-filled output on longer prompts, the deployment disables flash attention and accepts slower generation for more predictable results.
掘金 · 人工智能 · 🔥 0 - Reddit user reports mixed-vendor GPU node running three Qwen vision models
A Reddit user reported that the lvgale node combines AMD RX 580 and RX 570 GPUs with NVIDIA GTX 1660 Super and GTX 1070 GPUs around an Intel Core i7-6700K. Its custom Nuitka-compiled Python engine, Slipstream, reportedly used a mixed-vendor Vulkan backend and Flash Attention to concurrently serve Qwen3.8:27b-vision at 3.82 t/s, Qwen3.5:9b-vision at 4.75 t/s, and Qwen3.5:2b-vision at 12.47 t/s. The post also claimed stable vision-processing performance across the mixed AMD-NVIDIA topology, but the measurements and stability claims were not independently verified.
r/LocalLLaMA · 🔥 0
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