Re:Qwen3.5: Towards Native Multimodal Agents
by cpburns2009 on Tuesday February 17, 2026 @08:58AM
(#47047534)
In my short testing on a different MoE model, it does not perform well. I tried running Kimi-K2-Thinking-GGUF with the smallest unsloth quantization (UD-TQ1_0, 247 GB), and it ran at 0.1 tps. According to its guide, you should expect 5 tps if the whole model can fit into RAM+VRAM, but if mmap has to be used, then expect less than 1 tps which matches my test. This was on a Ryzen AI Max+ 395 using ~100 GB VRAM.
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Re:Qwen3.5: Towards Native Multimodal Agents
by zardo on Tuesday February 17, 2026 @01:16PM
(#47050883)
That's NVME storage in your test?
Re:Qwen3.5: Towards Native Multimodal Agents
by cpburns2009 on Tuesday February 17, 2026 @02:58PM
(#47052386)
Yes, a WD_BLACK 4TB SN850X NVMe.
Re:Qwen3.5: Towards Native Multimodal Agents
by zozbot234 on Thursday February 19, 2026 @04:36AM
(#47071857)
Running a 247GB model reliably on 100GB VRAM total is a very impressive outcome no matter what the performance. That size of model is one where sensible people will recommend at least 4x the VRAM amount compared to what you were testing with - at that point, the total bandwidth to your storage becomes the bottleneck. Try running models that are just slightly bigger than the amount of VRAM you're using and these tricks become quite essential, for a significantly more manageable hit on performance.