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Qwen3.6-Max-Preview: Smarter, Sharper, Still Evolving

qwen.ai

31–40 of 400 posts

Re: Qwen3.6-Max-Preview: Smarter, Sharper, Still Evolving

#31
post #8

I find it odd that none of OpenAI models was used in comparison, but used Z GLM 5.1. Is Z (GLM 5.1) really that good? It is crushing Opus 4.5 in these benchmarks, if that is true, I would have expected to read many articles on HN on how people flocked CC and Codex to use it.

Most HN commenters seem to be a step behind the latest developments, and sometimes miss them entirely (Kimi K2.5 is one example). Not surprising as most people don't want to put in the effort to sift through the bullshit on Twitter to figure out the latest opinions. Many people here will still prefer the output of Opus 4.5/4.6/4.7, nowadays this mostly comes down to the aesthetic choices Anthropic has made.

Re: Qwen3.6-Max-Preview: Smarter, Sharper, Still Evolving

#32
post #2

With them comparing to Opus 4.5, I find it hard to take some of these in good faith. Opus 4.7 is new, so I don't expect that, but Opus 4.6 has been out for quite some time.

I think its only been like 10 weeks. I meant that's forever in AI time, but not a long time in normie people time.

Re: Qwen3.6-Max-Preview: Smarter, Sharper, Still Evolving

#33
Nowadays, I'm working on a realtime path tracer where you need proper understanding of microfacet reflection models, PDFs, (multiple) importance sampling, ReSTIR, etc.. Saying that mine is a somewhat specific use case.

And I use Claude, Gemini, GLM, Qwen to double check my math, my code and to get practical information to make my path tracer more efficient. Claude and Gemini failed me more than a couple of times with wrong, misleading and unnecessary information but on the other hand Qwen always gave me proper, practical and correct information. I’ve almost stopped using Claude and Gemini to not to waste my time anymore.

Claude code may shine developing web applications, backends and simple games but it's definitely not for me. And this is the story of my specific use case.

Re: Qwen3.6-Max-Preview: Smarter, Sharper, Still Evolving

#35
post #26
post #8

I find it odd that none of OpenAI models was used in comparison, but used Z GLM 5.1. Is Z (GLM 5.1) really that good? It is crushing Opus 4.5 in these benchmarks, if that is true, I would have expected to read many articles on HN on how people flocked CC and Codex to use it.

In fact it is appreciated that Qwen is comparing to a peer. I myself and several eng I know are trying GLM. It's legit. Definitely not the same as Codex or Opus, but cheaper and "good enough". I basically ask GLM to solve a program, walk away 10-15 minutes, and the problem is solved.

cheaper is quite subjective, I just went to their pricing page [0] and cost saving compared to performance does not sell it well (again, personal opinion).

CC has a limited capacity for Opus, but fairly good for Sonnet. For Codex, never had issues about hitting my limits and I'm only a pro user.

https://z.ai/subscribe

Re: Qwen3.6-Max-Preview: Smarter, Sharper, Still Evolving

#36
post #18

Earlier quoted context omitted.

Haven’t you heard about Codex?

its an SKU from OpenAI's perspective, broader goal and vision is (was) different. Look at the Claude and GLM, both were 95% committed to dev tooling: best coding models, coding harness, even their cowork is built on top of claude code

I'm not sure how this makes sense when Claude models aren't even coding specific: Haiku, Sonnet, Opus are the exact same models you'd use for chat or (with the recent Mythos) bleeding edge research.

Re: Qwen3.6-Max-Preview: Smarter, Sharper, Still Evolving

#37
post #2

With them comparing to Opus 4.5, I find it hard to take some of these in good faith. Opus 4.7 is new, so I don't expect that, but Opus 4.6 has been out for quite some time.

When Sonnet 4.6 was released, I switchmed my default from Opus to Sonnet because it was about en par with Opus 4.5. While 4.6 and 4.7 are "better", the leap is too small for most tasks for me to need it, and so reducing cost is now a valid reason to stay at that level.

If even cheaper models start reaching that level (GLM 5.1 is also close enough that I'm using it at lot), that's a big deal, and a totally valid reason to compare against Opus 4.5

Re: Qwen3.6-Max-Preview: Smarter, Sharper, Still Evolving

#38
post #3

The fun thing is, you can be aware of the entire range of Qwen models that are available for local running, but not at all about their cloud models. I knew of all the 3.5’s and the one 3.6, but only now heard about the Plus.

Their Plus series have existed since Qwen chat was available , as far as I remember. I can at least remember trying out their Plus model early last year.

Re: Qwen3.6-Max-Preview: Smarter, Sharper, Still Evolving

#39

Nowadays, I'm working on a realtime path tracer where you need proper understanding of microfacet reflection models, PDFs, (multiple) importance sampling, ReSTIR, etc.. Saying that mine is a somewhat specific use case. And I use Claude, Gemini, GLM, Qwen to double check my math, my code and to get practical information to make my path tracer more efficient. Claude and Gemini failed me more than a couple of times with…

What size of Qwen is that, though? The largest sizes are admittedly difficult to run locally (though this is an issue of current capability wrt. inference engines, not just raw hardware).

Re: Qwen3.6-Max-Preview: Smarter, Sharper, Still Evolving

#40
post #8

I find it odd that none of OpenAI models was used in comparison, but used Z GLM 5.1. Is Z (GLM 5.1) really that good? It is crushing Opus 4.5 in these benchmarks, if that is true, I would have expected to read many articles on HN on how people flocked CC and Codex to use it.

Most HN commenters seem to be a step behind the latest developments, and sometimes miss them entirely (Kimi K2.5 is one example). Not surprising as most people don't want to put in the effort to sift through the bullshit on Twitter to figure out the latest opinions. Many people here will still prefer the output of Opus 4.5/4.6/4.7, nowadays this mostly comes down to the aesthetic choices Anthropic has made.

Not just aesthetics though, from time to time I implement the same feature with CC and Codex just to compare results, and I yet to find Codex making better decisions or even the completeness of the feature.

For more complicated stuff, like queries or data comparison, Codex seems always behind for me.

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