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prefix caching in llama.cpp: worth it? - Printable Version +- Inference (https://www.datasculpting.ai/inference) +-- Forum: Inference Engines (https://www.datasculpting.ai/inference/forumdisplay.php?fid=9) +--- Forum: llama.cpp / GGUF (https://www.datasculpting.ai/inference/forumdisplay.php?fid=35) +--- Thread: prefix caching in llama.cpp: worth it? (/showthread.php?tid=1240) Pages:
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Re: prefix caching in llama.cpp: worth it? - marbletrack - 10-17-2026 A couple questions before I guess too hard. What model, what runtime, and roughly what context size? Re: prefix caching in llama.cpp: worth it? - dockridge - 10-18-2026 Quote:A couple questions before I guess too hard. What model, what runtime, and roughly what context size? That matches what I was seeing. I don't think your conclusion is far off. Re: prefix caching in llama.cpp: worth it? - rocmriley - 10-18-2026 What worked for me was pretty simple. Before rebuilding anything, I'd test one clean baseline with Llama and compare from there. Not glamorous advice, but repeatable baselines save a lot of time. Re: prefix caching in llama.cpp: worth it? - embershed99 - 10-18-2026 A couple things I'd check first. Start by verifying the driver/runtime combo, then test with a smaller prompt, then look at small local stacks. A lot of these threads end up being one bad config plus a pile of conclusions drawn from it. Re: prefix caching in llama.cpp: worth it? - vrambandit - 10-18-2026 Ran a quick check on my box. My result was mixed: first run looked bad, second run looked normal. The main thing that moved was latency, not quality. Re: prefix caching in llama.cpp: worth it? - visionyard23 - 10-19-2026 My first guess would be this: Start by verifying the driver/runtime combo, then test with a smaller prompt, then look at long context. Not glamorous advice, but repeatable baselines save a lot of time. |