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Vector Databases discussion on M3 Max - Printable Version +- Inference (https://www.datasculpting.ai/inference) +-- Forum: RAG & Knowledge Systems (https://www.datasculpting.ai/inference/forumdisplay.php?fid=14) +--- Forum: Vector Databases (https://www.datasculpting.ai/inference/forumdisplay.php?fid=60) +--- Thread: Vector Databases discussion on M3 Max (/showthread.php?tid=207) |
Vector Databases discussion on M3 Max - emberquill - 09-09-2026 Spent some time on this today and wanted to compare notes. I'm comparing two approaches here: keep it simple on B200, or squeeze more out of the stack and deal with the complexity. Trying to avoid rebuilding the whole thing twice. Re: Vector Databases discussion on M3 Max - localtinker - 09-09-2026 I don't think that's the whole story. 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. Re: Vector Databases discussion on M3 Max - batchfield55 - 09-09-2026 I'd approach it in a boring order. Start by verifying the driver/runtime combo, then test with a smaller prompt, then look at VRAM headroom. A lot of these threads end up being one bad config plus a pile of conclusions drawn from it. I'm happy to test one more variant if you want a second data point. Re: Vector Databases discussion on M3 Max - fastfield4 - 09-10-2026 subscribed, curious where this lands. If you post your exact settings, people here can probably narrow it down pretty fast. Re: Vector Databases discussion on M3 Max - minthall - 09-10-2026 Did a small comparison this afternoon. On 4090 with llama.cpp, I saw basically the same behavior. Re: Vector Databases discussion on M3 Max - byteyard - 09-10-2026 I think the bottleneck is somewhere else. I get why that seems right, but on dual 3090 the bottleneck felt elsewhere. Re: Vector Databases discussion on M3 Max - amberkite - 09-10-2026 Did a small comparison this afternoon. My result was mixed: first run looked bad, second run looked normal. The surprise was that memory pressure showed up before throughput collapsed. |