![]() |
|
local video generation really usable yet for Mistral - Printable Version +- Inference (https://www.datasculpting.ai/inference) +-- Forum: Evaluation & Testing (https://www.datasculpting.ai/inference/forumdisplay.php?fid=16) +--- Forum: Quality / Reliability Testing (https://www.datasculpting.ai/inference/forumdisplay.php?fid=68) +--- Thread: local video generation really usable yet for Mistral (/showthread.php?tid=1481) |
Re: local video generation really usable yet for Mistral - paperrunner - 10-18-2026 that fixed it for me too. At this point the real bottleneck is my patience. Re: local video generation really usable yet for Mistral - kernelghost - 10-18-2026 I'd start with the simpler stack. Re: local video generation really usable yet for Mistral - turboscope - 10-18-2026 Quote:Posting this in case it saves someone else a little time. My first guess would be this: On 7900 XTX, the easiest win is often to back off the aggressive settings and see whether the problem survives. A lot of these threads end up being one bad config plus a pile of conclusions drawn from it. Re: local video generation really usable yet for Mistral - llm_wren - 10-18-2026 Not sure I agree there. I wouldn't optimize around that first. On my side the bigger swing came from the runtime and not the model. Could be a workload difference, but I wouldn't generalize too fast from one setup. local video generation really usable yet for Mistral - sparrowcraft - 10-19-2026 Posting this in case it saves someone else a little time. I'm helping a small team set up a local workflow. We don't need a giant stack, but we do care about prefix caching. Would rather learn from your scars than collect my own all at once. Re: local video generation really usable yet for Mistral - vrampilot - 10-19-2026 Thanks, that helps. I don't think your conclusion is far off. I got better results once I stopped chasing one metric and just looked at whether the workflow felt usable. Re: local video generation really usable yet for Mistral - visionforge - 10-19-2026 Good point. I ended up in about the same place using TensorRT-LLM. I got better results once I stopped chasing one metric and just looked at whether the workflow felt usable. |