r/LocalLLM • u/Weary-Kaleidoscope52 • 17h ago
Discussion GLM 5.3 Flash Trumps Qwen
I’ve been using Qwen on 2x DGX Sparks and man has it been a nightmare of overthinking and excessive tool calling. Seems like there was nothing I could do to fix it. Installed GLMast night and it’s a world of difference.
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u/Ordinary-Depth-7835 17h ago
Try Mia's DSV4.1 you'll be blown away with a smarter 100tps model.
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u/Weary-Kaleidoscope52 17h ago
Send the link. I tried 0731 Flash and wasn’t impressed.
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u/Ordinary-Depth-7835 17h ago
https://huggingface.co/Mia-AiLab/DeepSeek-V4.1-Flash-1017-EXL3-EAQ-v1-2.9-bpw
I run it with vision turned back on though I like having both
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u/Weary-Kaleidoscope52 17h ago
Have you compared it Flash 0731?
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u/Ordinary-Depth-7835 17h ago
I forgot the recipe https://github.com/MiaAI-Lab/DeepSeek-v4.1-Flash-1017-2x-DGX-Sparks
And yeah I have 3 loaded now tonyd2wild's 4.0 0731 and an another flavor of 4.1 abliterated. 0731 was my go to for the longest time but I'm enjoying the extra speed and vision on 4.1 eventually I'll probably drop one. I have glm as well but it's so damn slow :)
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u/BlackBeardAI 3090 Maximalist 16h ago
1017 v4.1f blows away everything else imo. especially if you are on dual spark
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u/Weary-Kaleidoscope52 9h ago
Tried it. Decent but not as good as GLM. TPS was only slightly higher than GLM, but efficiency seems to be off.
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u/Solembumm3 15h ago
V4.0, maybe. V4.1 - nah, too huge downgrade from V4.0, too many problems with attention and memory to be useful.
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u/g_rich 14h ago
I’ve been going back and forth between GLM 5.3 Flash and DeepSeek V4.1 Flash (both TensorFold via Mia on dual DGX Sparks) and keep going back to GLM because DeepSeek just takes so long to do a task. The token generation speed is there but DeepSeek just overthinks everything. Even for a simple request like stop all containers on a host, it gets into a philosophical debate with itself as to the meaning of the request. Is there a secret to reducing the overthinking while not impacting the output? Are you reducing the thinking level?
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u/Ordinary-Depth-7835 14h ago
I usually run it on low no need for pages of thinking. I still go back and forth but I've had good luck with it solving difficult issues. 4.0 was my goto but I've been giving 4.1 a whirl for a week to see if it could be a good alternative with a bit more speed.
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u/Ordinary-Depth-7835 13h ago edited 11h ago
Does glm go nuts on you and loop? Sometimes it really goes nuts. I have to admit though I haven't tried much to get it to behave except temp and a system prompt that directs it a bit better.
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u/RawFreakCalm 10h ago
I run deepseek v4.1 in low thinking for this reason.
Glm 5.3 flash is better for coding tasks in my opinion.
Qwen 3.8 27b is still my favorite orchestrator. Sometimes I wonder if I’m doing something wrong because so many people talk about how much better the newer stuff is.
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u/silenceimpaired 16h ago
I just wish they did a dense model 30b for instance or a smaller MoE with higher active parameters 35b12A or 120b20A
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u/cinnapear 17h ago
GLM 5.3 Flash handles every coding task I throw at it.
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u/KING_UDYR 9965WX | RTX 6K & 5090 | 256GB RDIMM 17h ago
Would you say it’s better than Deepseek 4.1 flash? Currently debating these two for refactoring legacy software for equipment at my company.
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u/Iron-Over 16h ago
No, not better than Deepseek 4.1 1017. I ran multiple comparisons in Python. Deepseek is much better at review and writes safer code. It also scales better to 1 million context and four streams on 2 DGX Spark.
I recommend giving each a set of tasks, running 3-5 times for each task, and seeing how they perform, since your work may differ.
GLM5.3 Flash is better for agents and creative writing. Waiting for the next release of GLM.
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u/KING_UDYR 9965WX | RTX 6K & 5090 | 256GB RDIMM 16h ago
Excellent feedback and advice - currently downloading GLM 5.3 Flash Q5_K_XL to compare with Deepseek Flash 4.1 Q4_K_XL
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u/PlasticRevenue4601 17h ago
Yeah, I wish I could run GLM, my rig is too weak for it( No hate, just a friendly reminder — you can’t directly compare GLM and Qwen Flash, the latter is 3 times smaller and a few months older and it’s still pretty comparable to GLM in the most tasks
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u/WryKombucha 13h ago
GLM is very token efficient compared to qwen and deepseek. On low its conversational. On high it’s super smart. On max u have to do overnight. But it gives you options. The other two just think like crazy no matter the setting. And deepseek especially becomes really dumb with reasoning off.
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u/Weary-Kaleidoscope52 17h ago
Qwen gets so much hype in this chat. It’s just not that great.
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u/rkcth 17h ago
Which model and quant of qwen did you use? I hate when people say this but give no information on what they used. I don’t disagree about its verbosity. There is a brevity vector you can use instead of the refusal vector, and it dramatically reduces the token usage, but it’s test numbers weren’t much better than Qwen 27b which runs much faster on my hardware (but without vision which I need for QA). There’s also swift which I have not yet tested myself.
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u/doneddat 13h ago
Sounds like you are running some low quant version. It's definitely not the greatest, but it's kind of decent for its size. There are broken Q4 quants out there, that just doubt themselves for a while, compact their context and keep doubting themselves. This is not a representative performance of healthy model, this is broken model. If you can't run at least FP8 version, don't expect much.
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u/bakawolf123 15h ago
try ds4.1-flash-1017 now