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Joined 3 years ago
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Cake day: June 12th, 2023

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  • So - I setup that model according to the docs and gave it this prompt:

    Write me a highly optimized n-queens solver in go. It should take advantage of parallelism (what little there is) and output only the solution and how long it took.
    

    After 10 minutes it gave me code that didn’t compile.

    It took another 3 mins to fix the compile error and the output is not correct.

    As I said - LLMs on 8Gig VRAM just aren’t worth it.


  • Yeah - I’ve been playing around more with the Qwen3-Coder-30B-A3B-Instruct MoE model and it’s still quite… Meh. I’ve been using llama.cpp and I’ve tried a bunch of tuning. It works and performs well enough (15t/s) but the output is just garbage. I can do some simple coding but I’m finding I’m fighting with it more than if I just wrote the code myself. Maybe I just have standards that are too high. Claude Opus 3.7 is just in an entirely different league…


  • I’ll check that out - speed isn’t my biggest issue so much as coding performance… The qwen 3.5 model I was using can write code, but it’s… Meh? Like sometimes it doesn’t even compile.

    I did try tweaking llama.cpp to do some cpu offloading and it does seem to allow for much larger contexts at a modest performance loss. I’ll check out larger models.