| ▲ | frigidwalnut 2 days ago | ||||||||||||||||||||||
Cool! I'm thinking about a local set up. What's your usual tokens/second rate? | |||||||||||||||||||||||
| ▲ | victords 2 days ago | parent | next [-] | ||||||||||||||||||||||
Not OP, but I’m running local models on a M1 Max as well with 64GB RAM. It varies by model, but I’m getting 50-60 t/s with Qwen 3.6 35B and Qwen 3 coder 30B. I’ve also used Qwen 3.8 27B but I get 10t/s on it. It’s useable in some use cases, but I rely mostly on my $20 Claude subscription. | |||||||||||||||||||||||
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| ▲ | solarkraft 2 days ago | parent | prev [-] | ||||||||||||||||||||||
NGL: I don’t really have a good way to find out right now. It also doesn’t matter that much because the way the models use the tokes varies a lot. Qwen 3.8 is known for overthinking while Muse Glimmer may be a little slower per token, but it uses them very efficiently, caveman style. Generation speed isn’t the bottleneck anyway, at least on pre M4/M5 devices (the newer chips got significant processing acceleration). It’s prompt processing time. OpenCode’s system prompt can take up to 3 minutes to process, which is why good prompt caching is essential. For that I use omlx, which can persist the KV cache to disk, chunked so you can reuse parts. This helps with the usability a lot, when an agentic session is warm it runs pretty smoothly. New requests can take a couple seconds (sometimes many, which must be fixable somehow). So: It’s not fast, but I also don’t find it awfully slow. My use is typically semi-interactive, for fully interactive use you have to wait a bit, but it’s possible. I personally am still regularly amazed that something even close to this is possible on completely local hardware. | |||||||||||||||||||||||