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

qwen.ai

131–140 of 400 posts

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

#131
post #82

Notice the pattern that Chinese providers are now: 1. Keeping models closed source. 2. Jacking up pricing. A lot. Sometimes up to 100% increase.

Yeah, its almost like the casinos started rigging the game after they got all the addicts hooked. Who saw that coming???

If you overuse LLMs or get excited about them at all, you're ngmi and a complete idiot.

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

#132
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…

The models test roughly equal on benchmarks, with generally small differences in their scores. So, it’s reasonable to choose the model based on other criteria. In my case, I’d switch to any vendor that had a decent plugin for JetBrains.

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

#133
post #94
post #67

Earlier quoted context omitted.

So what? I still prefer that over US total dominance. Let them fight it out.

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.

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

#134
post #55

Earlier quoted context omitted.

GLM-5 is good, like really good. Especially if you take pricing into consideration. I paid 7$ for 3 months. And I get more usage than CC. They have difficulty supplying their users with capacity, but in an email they pointed out that they are aware of it. During peak hours, I experience degraded performance. But I am on their lowest tier subscription, so I understand if my demand is not prioritized during those hours…

Where are you getting 3 months for $7?

They had a Christmas deal that ended January 31.

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

#135
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.

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

#136
post #83
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…

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 wonder to what degree it depends on how easy you find coding in general. I find for the early steps genAI is great to get the ball rolling, but rapidly it becomes more work to explain what it did wrong and how to fix it (and repeat until it does so) than to just fix the code myself.

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

#137
post #84

Earlier quoted context omitted.

I'm a little more optimistic than that. I suspect that the open-weight models we already have are going to be enough to support incremental development of new ones, using reasonably-accessible levels of compute. The idea that every new foundation model needs to be pretrained from scratch, using warehouses of GPUs to crunch the same 50 terabytes of data from the same original dumps of Common Crawl and various Russian…

Change layer size and you have to retrain. Change number of layers and you have to retrain. Change tokenization and you have to retrain.

None of that is true, at least in theory. You can trivially change layer size simply by adding extra columns initialized as 0, effectively embedding your smaller network in a larger network. You can add layers in a similar way, and in fact LLMs are surprisingly robust to having layers added and removed - you can sometimes actually improve performance simply by duplicating some middle layers[0]. Tokenization is probably the hardest but all the layers between the first and last just encode embeddings; it's probably not impossible to retrain those while preserving the middle parts.

[0] https://news.ycombinator.com/item?id=47431671 https://news.ycombinator.com/item?id=47322887

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

#138
post #104

Earlier quoted context omitted.

> We've seen all the American models be closed and proprietary from the start. Most*. OpenAI, contrary to popular belief, actually used to believe in open research and (more or less) open models. GPT1 and GPT2 both were model+code releases (although GPT2 was a "staged" release), GPT3 ended up API-only.

That's fair but those days seem so long gone now. Also the Chinese models aren't following a typical American SaaS playbook which relies on free/cheap proprietary software for early growth. They are not just publishing their weights but also their code and often even publishing papers in Open Access journals to explicitly highlight what methods and advancements were made to accomplish their results

gasp Science!

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

#139
post #127

Earlier quoted context omitted.

I wonder about this. I see two obvious possibilities (if we ignore bias): 1. The models are purposefully nerfed, before the release of the next model, similar to how Apple allegedly nerfed their older phones when the next model was out. 2. You are relying more and more on the models and are using your talent less and less. What you are observing is the ratio of your vs. the model’s work leaning more and more to the m…

I definitely find your last point is true for me. The more work I am doing with AI the more I am expecting it to do, similar to how you can expect more over time from a junior you are delegating to and training. However the model isn't learning or improving the same way, so your trust is quickly broken. As you note, the developer's input is still driving the model quite a bit so if the developer is contributing less…

Your version of the last point is a bit softer I think — parent was putting it down to “loss of talent” but yours captures the gaps vs natural human interaction patterns which seems more likely, especially on such short timescales.

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

#140
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.

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!"
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