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If it helps, I mean it in a really literal sense. qwen3.6 27b is currently $3.20 per million tokens on openrouter right now which is way overpriced. As good as the 27b is, kimi k2.5 $3.00 and it's just in another league in terms of capability. There's no reason to spend money on it.

And even alibaba's own qwen3.6-plus is $1.95, so it's kinda easy to come to a conclusion that alibaba (nor anyone else) is really interested in hosting that model.

And don't get me wrong, I fully agree with you, qwen3.6 27b is an amazing model. I run it on my own hardware and every day I'm constantly surprised with what it can zero shot.

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Genuinely curious, what are you "fine tuning" these smaller models to do reliably? I hear this talked about a lot but very few people actually cough up examples, and I'd love to actually hear of one.
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depends, a super small one finetuned to do function calling instead sending it to big model and waiting, instead, you ask for a revenue in last month, i do a small llm function call -> show results. some bigger ones, analysis, summary, classification. what is great with smaller ones, and im looking at 2b, 4b is you can get a huge throughput with just vllm and a couple of consumer gpus. what i usually do is basically distillation of a big one onto smaller one.
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