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prefill bottlenecks on longer prompts for Kimi - Printable Version +- Inference (https://www.datasculpting.ai/inference) +-- Forum: Inference Engines (https://www.datasculpting.ai/inference/forumdisplay.php?fid=9) +--- Forum: Other Engines (https://www.datasculpting.ai/inference/forumdisplay.php?fid=39) +--- Thread: prefill bottlenecks on longer prompts for Kimi (/showthread.php?tid=1445) |
prefill bottlenecks on longer prompts for Kimi - tinycontext - 10-19-2026 Thought I'd post a small recipe because a lot of threads ask similar things. Maybe useful as a starting point: LM Studio on B200, keeping structured output in mind from the start. Maybe useful as a starting point for newer folks. For context, I'm not chasing leaderboard numbers. I mostly want the system to feel consistent day to day. I expected the biggest difference to come from the model, but the stack around it mattered at least as much. Re: prefill bottlenecks on longer prompts for Kimi - macrotinker - 10-19-2026 What worked for me was pretty simple. Start by verifying the driver/runtime combo, then test with a smaller prompt, then look at HBM constraints. A lot of these threads end up being one bad config plus a pile of conclusions drawn from it. |