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Comment by mynameismon | Hacker News Reader

Why not Chinese models hosted on American hardware?

The reality is that they're a hell of a lot less cheap on American hardware than on Chinese hardware. At the point you are running Chinese models on US hardware, "Why not nano or haiku" becomes the next relevant question.

Not true. Togetherai, deepinfra, fireworks AI offer a wide range of models like gpt oss that are very capable and far cheaper than the models from big 3.

Are they better? Are they better than GPT5.5?

That depends on the use case. For a lot of business use cases they are good enough. They are certainly better than older models like gpt-4o.

I'm referring to Chinese open source models hosted on American clouds vs Chinese clouds. You're talking about an old and non-agentic capable American produced model.

You are actually referring to open weight models, not open source. Gpt-OSS is an example of an open weight model. It’s highly capable in agentic settings, people use it for coding all the time.

My greater point remains. Models like the qwen variants, minimax, k2.5, glm models are available by American providers like AWS at a much cheaper price than api offerings from the big three LLM providers.

Your point about Chinese models being cheap only on Chinese hardware makes absolutely zero sense. You can check out the model catalog like together ai’s qwen 3.5 9b offering. It’s 25 cents for 1M tokens vs the ridiculous $5/1M tokens for haiku.

Not a great example: Qwen 9b is a tiny model that outputs barely coherent text in a casual chat, nowhere near comparable to Haiku. But the broader point stands.

I am not sure if you are testing qwen 3.5 9b. I would also verify that you are running it correctly. Qwen 3.5 9b is actually a very capable coding model that can do agentic coding albeit it’s obviously not as good as opus.

You can look up the benchmarks on that model as well. Your experience does not align with mine.

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