Live data from Hacker News

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

qwen.ai

151–160 of 400 posts

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

#151
post #71

Ok I find it funny that people compare models and are like, opus 4.7 is SOTA and is much better etc, but I have used glm 5.1 (I assume this comes form them training on both opus and codex) for things opus couldn't do and have seen it make better code, haven't tried the qwen max series but I have seen the local 122b model do smarter more correct things based on docs than opus so yes benchmarks are one thing but realit…

I tried GLM5.1 last week after reading about it here. It was slow as molasses for routine tasks and I had to switch back to Claude. It also ran out of 5H credit limit faster than Claude.

Z.ai’s cloud offering is poor, try it with a different provider.

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

#152

Earlier quoted context omitted.

I tried GLM5.1 last week after reading about it here. It was slow as molasses for routine tasks and I had to switch back to Claude. It also ran out of 5H credit limit faster than Claude.

If you view the "thinking" traces you can see why; it will go back and forth on potential solutions, writing full implementations in the thinking block then debating them, constantly circling back to points it raised earlier, and starting every other paragraph with "Actually…" or "But wait!"

I see this with Opus too.

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

#154
post #94

Earlier quoted context omitted.

I'd get a bit informed about what exactly Chinese dominance entails. Ask a few Uyghurs, Cantonese Hong Kongers, or even Tibetans. Then decide ...

Ask a few Native Americans about dominance. Or maybe families of African descent. Or maybe families of Japanese Americans who lived in the US during WWII. Or maybe people of Latin descent living in the US today.

The US examples you just gave happened decades (and in some cases hundreds) of years ago. The difference is that it's happening in China right now, and nobody cares.

You really don't see the difference?

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

#155
post #83

Earlier quoted context omitted.

Many people averted religion (which I can get behind with), but have never removed the dogmatic thinking that lay at its root. As so many things these days: It's a cult. I've used Claude for many months now. Since February I see a stark decline in the work I do with it. I've also tried to use it for GPU programming where it absolutely sucks at, with Sonnet, Opus 4.5 and 4.6 But if you share that sentiment, it's alway…

I agree - the problem is it’s hard to see how people who say they’re using it effectively actually are using it, what they’re outputting, and making any sort of comparison on quality or maintainability or coherence. In the same way, it’s hard to see how people who say they’re struggling are actually using it. There’s truth somewhere in between “it’s the answer to everything” and “skill issue”. We know it’s overhyped.…

Well summarized.

We're also seeing that the people up top are using this to cull the herd.

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

#157

Earlier quoted context omitted.

I tried GLM5.1 last week after reading about it here. It was slow as molasses for routine tasks and I had to switch back to Claude. It also ran out of 5H credit limit faster than Claude.

If you view the "thinking" traces you can see why; it will go back and forth on potential solutions, writing full implementations in the thinking block then debating them, constantly circling back to points it raised earlier, and starting every other paragraph with "Actually…" or "But wait!"

> "Actually…" or "But wait!"

You’re absolutely right!

Jokes apart, I did notice GLM doing these back and forth loops.

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

#160

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…

for Anthropic and OpenAI there is a very real danger that people invest serious time finding the strengths of alternative models, esp Chinese/open models that can to some degree be run locally as well

it puts a massive backstop at the margins they can possibly extract from users

Post reply on HN