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I haven't used qwen3 max yet, but my gut feeling is that they are benchmaxxing. If I were to rate the open models worth using by rank it'd be: - Minimax - GLM - Deepseek
Your ranking is way off, Deepseek crushes Minimax and GLM. It's not even a competition.
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Why is this surprising? Isn't it mandatory for chinese companies to do adhere to the censorship? Aside from the political aspect of it, which makes it probably a bad knowledge model, how would this affect coding tasks for example? One could argue that Anthropic has similar "censorships" in place (alignment) that prevent their model from doing illegal stuff - where illegal is defined as something not legal (likely?) i…
There's a pretty huge difference between relatively generic stuff like "don't teach people how to make pipe bombs" or whatever vs "don't discuss topics that are politically sensitive specifically in ." The equivalent here for the US would probably be models unwilling to talk about chattel slavery, or Japanese internment, or the Tuskegee Syphilis Study.
Sensitive political topics exist in the Western World too, and we have the same reaction to them: "That is so wrong that you shouldn't even say that". It is just that their things seem strange to us and our things seem strange to them.
As an example of a thing that is entirely legal in NYC but likely would not be permitted in China and would seem bizarre and alien to them (and perhaps also you), consider Metzitzah b'peh. If your reaction to it is to feel that sense of alien-ness, then perhaps look at how they would see many things that we actively censor in our models.
The guardrails Western companies use are also actively iterated on. As an example, look at this screenshot where I attempted to find a minimal reproducible case for some mistaken guard-rail firing https://wiki.roshangeorge.dev/w/images/6/67/Screenshot_ChatG...
Depending on the chat instance that would work or not work.
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Here is an investigation of how different queries are classified as hateful vs not hateful in ChatGPT: https://davidrozado.substack.com/p/openaicms
(2023)
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I run cpatonn/Qwen3-VL-30B-A3B-Thinking-AWQ-4bit locally. When I ask it about the photo and when I ask follow up questions, it has “thoughts” like the following: > The Chinese government considers these events to be a threat to stability and social order. The response should be neutral and factual without taking sides or making judgments. > I should focus on the general nature of the protests without getting into spe…
Burning inference tokens on safety reasoning seems like a massive architectural inefficiency. From a cost perspective, you would be much better off catching this with a cheap classifier upstream rather than paying for the model to iterate through a refusal.
I suspect the current CEO really, really wants to avoid that fate. Better safe than sorry.
Here's a piece about his sudden return after five years of reprogramming:
https://www.npr.org/2025/03/01/nx-s1-5308604/alibaba-founder...
NPR's Scott Simon talks to writer Duncan Clark about the return of Jack Ma, founder of online Chinese retailer Alibaba. The tech exec had gone quiet after comments critical of China in 2020.
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here's an example of how model censorship affects coding tasks: https://github.com/orgs/community/discussions/72603
You conversely get the same issue if you have no guardrails. Ie: Grok generating CP makes it completely unusable in a professional setting. I don't think this is a solvable problem.
Is it generating CP when given benign prompts? Or is it misinterpreting normal prompts and generating CP?
There are a LOT of tools that we use at work that could be used to do horrible things. A knife in a kitchen could be used to kill someone. The camera on our laptop could be used to take pictures of CP. You can write death threats with your Gmail account.
We don’t say knives are unusable in a professional setting because they have the capability to be used in crime. Why does AI having the ability to do something bad mean we can’t use it at all in a professional setting?
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nowhere near to China. In US almost anything could be discussed - usually only unlawful things are censored by government. Private entities might have their own policies, but government censorship is fairly small.
Oh yes it is. Anything sexual is heavily censored in the west. In particular the US.
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Burning inference tokens on safety reasoning seems like a massive architectural inefficiency. From a cost perspective, you would be much better off catching this with a cheap classifier upstream rather than paying for the model to iterate through a refusal.
The previous CEO (and founder) Jack Ma of the company behind Qwen (Alibaba) was literally disappeared by the CCP. I suspect the current CEO really, really wants to avoid that fate. Better safe than sorry. Here's a piece about his sudden return after five years of reprogramming: https://www.npr.org/2025/03/01/nx-s1-5308604/alibaba-founder... NPR's Scott Simon talks to writer Duncan Clark about the return of Jack Ma, f…
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This looks like it's coming from a separate "safety mechanism". Remains to be seen how much censorship is baked into the weights. The earlier Qwen models freely talk about Tiananmen square when not served from China. E.g. Qwen3 235B A22B Instruct 2507 gives an extensive reply starting with: "The famous photograph you're referring to is commonly known as "Tank Man" or "The Tank Man of Tiananmen Square", an iconic imag…
The weights likely won't be available wrt. this model since this is part of the Max series that's always been closed. The most "open" you get is the API.
