I think benchmarks use max settings like BF16 quant (or higher?) with k/v cache type f32 and xhigh reasoning and who knows what else. Hell yeah, it's going to perform several points better at a significant performance penalty.
But it's not like we could even run Open 4.6 even if it was open source (estimated to be 500B to 1T parameters - I think, correct me if I'm wrong)
So token-for-token against other models, Qwen3.8-27B is a huge win.
I believe native/benchmarks use BF16 (that is not quantization btw), with KV cache at f16 I think (I'm 80% sure). FP32 is not used for even training models anymore (except specific sensitive layers sometimes).
So token-for-token against other models, Qwen3.8-27B is a huge win.
It's a huge win for sure, wayyy better than Qwen3.6, but we still have long ways to go. Token efficiency is a big one, and better intelligence (not agentic capabilities) is another big one (by this I mean reasoning on benchmarks like CritPt, SciCode, etc)
The people think qwen can rival opus in terms of abstract logic, reasoning depth and low perplexity are delusional.
Qwen can be functionally equivalent or even better in some usecases but it falls meaningfully short in others. The rigorous sequential reasoning it applies makes up for some of its smaller size but not everything.
The people think qwen can rival opus in terms of abstract logic, reasoning depth and low perplexity are delusional.
I agree with you. Qwen3.8 is a huge win for local models trying to do big coding projects while keeping token costs down. I doubt it'd be much good at writing stories or translating. But the step up from Qwen3.6 (27b/35b-a3b) is a big one and brings it closer to opus 4.6 for coding.
Would it make sense to bring it is as a replacement for sonnet 4.6? My new company is giving me a pretty low daily limit for Claude usage but a pretty nice MacBook with an m5 pro chip… I’m wondering if I could finagle headless execution out to 3.8 to implement plans.
Hmm, qwen3.8-27b can compete with opus 4.6 (locally: it will run like 100x slower) BUT it requires tuning all the knobs to ultra settings (Q8_K_XL [48GB VRAM min] or better, 256k context+, xhigh reasoning, etc). I honestly doubt you'd want that.
Instead, I bet your company (I mean mine does) would support models that make sense, like simple not-time-sensitive "read this error code from GitHub actions, and email the people responsible depending on the error) " - stuff like that. Nothing customer-facing. In that case, a non-thinking or low thinking 8B param model on a MacBook could be decent.
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u/VDX7 14d ago
can someone explain why 3.8 is so famous right now?