alt Hacker NewsQwen3 32B is a dense model, it uses all its parameters all the time. GPT OSS 20B is a sparse MoE model. This means it only uses a fraction (3.6B) at a time. It’s a tradeoff that makes it faster to run than a dense 20B model and much smarter than a 3.6B one.
In practice the fairest comparison would be to a dense ~8B model. Qwen Coder 30B A3B is a good sparse comparison point as well.
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selcuka • last Monday at 12:30 AM
> GPT OSS 20B is a sparse MoE model. This means it only uses a fraction (3.6B) at a time.
They compared it to GPT OSS 120B, which activates 5.1B parameters per token. Given the size of the model it's more than fair to compare it to Qwen3 32B.
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Tangential question from an outsider:
When people talk about sparse or dense models, are they spare or dense matrices in the conventional numerical linear algebra sense? (Something like a csr matrix?)