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I've been using GLM 5.3 Flash as the planner and DS 4.1 as the task worker over the last month and the results have been very good, predictable, ridiculously cheap.
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What reasoning level do you use for each?
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I'm the weirdo who is clinging onto GLM 5.2. 5.3 seems to have picked up the bad writing from Opus 5.
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GLM 5.2 was the first open model that I was happy to use as my main. It's a fantastic model. 5.3 cost a lot more per task, was slower and didn't get that much better results for me, so I tried 5.3 Flash for a bit, it was ok, but didn't feel as magical as 5.2 and I have now landed on DeepSeek 4.1 Flash as my main.
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I don't think that's likely, given the close release dates of both? I wonder if 5.3 just choked on too much RL slop, independently of Opus 5.
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Genuinely curious, why not use GPT Sol 6.1 high which has a better cost per task and intelligence ($0.32, 50) or Mimo 2.6 pro? ($0.13, 46) over GLM Max's $2.01, 45?
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Not OP, but I've been trying out Sol 6.1 medium with hermes agent, and I have not been able to match usage costs to what I've been getting with glm 5.3 flash high.

Really don't know why, since I've offloaded thinking to the LLMs in this area of my life. Though even at medium, 6.1-Sol is noticeably better at most tasks I throw at it.

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I'm OP and I have the Ollama basic $20/mo plan.

Been very happy with it although I will say Muse Spark 1.3 being free on OpenCode is my main model these days. If I run out of free credits on OC (which almost never happens) then I drop into GLM Flash 5.3.

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If you liked GLM 5.3, you would appreciate Deepseek V4 Flash a lot. In my personal opinion and use-cases, it outperforms GLM 5.3.
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V4 isn't the newest DeepSeek, and GLM 5.3 non-Flash isn't the same ballpark

- DeepSeek V4.1 Flash has marginally better coding, and smaller experts (8B-In/16B-Out) with more compressed attention and KV cache, so it's faster but will have less expertise per task. It's a 552B model, so while it theoretically may contain more trained data it also requires more RAM (the experts are smaller to compensate for speed loss) making it harder to serve without the distributed KV cache DeepSeek hosts.

- GLM 5.3 Flash has marginally better agentic work, and has video input (DS doesn't), and its experts are 18B so there's more intelligence per task. It's a 320B model so it requires less RAM which will make it cheaper to serve. Considering it's a much smaller model, the higher intelligence indicates their architecture/training is better.

- GLM 5.3 (non-Flash) is far more intelligent than both; it's a 744B model with 40B experts, but it's text-only.

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Model sizes aren't directly comparable, and they aren't even that relevant. I care about result quality, cost, and speed, not size. I switched to deepseek because it was giving me better coding results than GLM, and for far less cost. GLM is still better at planning.
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Stupid question probably because I’ve gotten out of sync with the new releases but is Flash better or worse than vanilla 5.3? I’ve been using 5.3 extensively (and maybe ironically have used flash only for viewing images which I have as a skill in Pi because 5.3 vanilla seemingly doesn’t support vision). I find it generally competent but still very far behind opus 5.5. I’ve been trying to avoid Anthropic but the lift of opus vs GLM is enough that I end up coming back to it. I feel like currently there’s no comparison.

anyway, tldr I would not be happy if stuck with vanilla 5.3 so is flash better and should I move to that?

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GLM 5.3 Flash is better if you need native multi-modal capabilities, higher speed, and lower costs, but worse than vanilla 5.3 in raw reasoning and for complex programming.
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Have you compared to deepseek v4.1 flash? It’s so good, at a ridiculous price
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