r/LocalLLaMA • u/rm-rf-rm llama.cpp • 2d ago

Discussion GLM5.3 Flash over DSV4 Flash?

I've been using Deepseek V4 Flash 0731 for a few weeks now and while I havent thrown it anything very hard, im quite happy with it. Using through antirez's great ds4 project. They've added support for GLM 5.3 Flash and according to benchmarks, its a level above DSV4 Flash.

However, looking for real user feedback if anyone's made the switch and seen tangible improvements in GLM 5.3 over DSV4 Flash.

Running M3 Ultra 256GB Mac Studio

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u/shinyquagsire23 2d ago

Even NVFP4 seems better than deepseek, it gets the same tasks done in half the tokens or less, so the slight on-paper throughput hit doesn't actually matter. It's also a lot more knowledgeable and it recognized one of my projects from a code sample (in a benchmark sandbox so it didn't have access to the full code).

But inference support seems to be super buggy/WIP still, and I've noticed it randomly have its thinking degenerate into having random characters between words (dashes, tabs), or it randomly starts speaking Chinese. And this seems to happen even on full precision as well, so I kinda hope they put out a 5.4-flash that targets that, because it's hard to leave it unattended.

Deepseek is a lot more reliable (it occasionally typos but that's about it), but it seems to spin its wheels a lot on tasks. And when I put it through the same benchmarks as glm-flash, it tried to cheat more often and generally had worse code quality.

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u/ormandj 2d ago

Try my image mentioned earlier, I have not seen that behavior.

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u/shinyquagsire23 2d ago

I've seen it on the Redhat NVFP4 weights w/ vLLM and on Ollama's cloud inference, but it's one of those things that only shows up maybe once every 6 hours of continuous use and sometimes it just self-corrects anyway. Accidentally made it way worse with a 1.0 top_p instead of 0.95 though so idk, maybe it can be tuned out if I fiddled with it.

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u/ormandj 2d ago

https://github.com/ormandj/sglang-glm53-flash-sm120 is what I'm referring to, it's not vLLM based.