Qwen2.5-VL-32B: Smarter and Lighter

Big day for open source Chinese model releases - DeepSeek-v3-0324 came out today too, an updated version of DeepSeek v3 now under an MIT license (previously it was a custom DeepSeek license). https://simonwillison.net/2025/Mar/24/deepseek/

Pretty soon I won't be using any American models. It'll be a 100% Chinese open source stack.

The foundation model companies are screwed. Only shovel makers (Nvidia, infra companies) and product companies are going to win.

I still don't get where the money for new open source models is going to come from once setting investor dollars on fire is no longer a viable business model. Does anyone seriously expect companies to keep buying and running thousands of ungodly expensive GPUs, plus whatever they spend on human workers to do labelling/tuning, and then giving away the spoils for free, forever?

ads again. somehow. its like a law of nature.

If nationalist propaganda counts as ads, that might already be supporting Chinese models. Ask them about Tiananmen Square.

Any kind of media with zero or near zero copying/distribution costs becomes a deflationary race to the bottom. Someone will eventually release something that's free, and at that point nothing can compete with free unless it's some kind of very specialized offering. Then you run into a the problem the OP described: how do you fund free? Answer: ads. Now the customer is the advertiser, not the user/consumer, which is why most media converges on trash.

These ads can also have ads blockers though.

Perplexity released the deepseek r1 1331? ( I am not sure I forgot) It basically removes chinese censorships / yes you can ask it about the tiananmen square.

I think the next iteration of these ai model ads would be sneaky which might be hard to remove

Though it's funny you comment about chinese censorship yet american censorship is fine lol

There are lots of "alliterated" versions of models too, which is where people will essentially remove the models ability to reject responding to a prompt. The huihui r1 14b alliterated had some trouble telling me about tiananmen square, basically dodging the question by telling me about itself, but after some coaxing I was able to get the info out of it.

I say this because I think that the Perplexity model is tuned on additional information, whereas the alliterated models only include information trained into the underlying model, which is interesting to see.

Abliterated? Alliterated LLMs might be fun though…