The way it was said made it sound like they had something better than a 35B-A3B coming.

Quick tests suggest it’s pretty good at reasoning and tool use (keen to search to check its thinking) and it seems to waste much less time thinking, too.

So it feels very fast.

But it does not seem to be better than Qwen 3.6 35B at coding. A bit worse, I think, though I will test it more.

If you have a machine that can fit a 35B model in VRAM, I would suggest testing Muse Glimmer with (from memory)

  Reasoning strength: low

Despite being a dense model, this is actually capable of solving code problems faster than the Qwen MoE, despite having only one fifth of the raw token performance.

Honest question/suggestion for the HN audience- Since Qwen released the weights for Qwen3.8 2.4T-A95B and we already have the staring point of Qwen3.6 35B-A3B, couldn't someone distill the bigger model and make a "pseudo" Qwen3.8 35B-A3B? Sure, it wouldn't be an official Qwen release but couldn't someone improve on Qwen 3.6 and get the thing everyone is asking for?

I am calling this a suggestion for the audience because I don't have the will/resources to do this.

The smarter 27B is so fast with MTP I've found I really don't need the 35B-A3B. You get around 70tk/s on a M5 Max lowering to around 40tk/s at higher context sizes.

Personally I find speculative decoding much better strategy than MoE – performance wise it's there at 90-100 t/s on 2x4090, great intelligence – really great fit.

I'm running qwen3.8 27B dense on reasonable hardware (oem spark)

tbh, I have stopped using MoE in the name of speed, the dense (with more active parameters) makes a real difference in output quality

What did you use it for? I've found it somewhat capable but not worth to actually use it (1 9B, that is)

I had to go down to UD-Q3_K_XL for Qwen 3.8 27B to get it to fit in VRAM and be usable, but I worry I'm gutting its intelligence somewhat. I too am interested in faster + more-usable alternative that can exchange blows with the Q3-dumbed 27B.

I need someone to run actual benchmarks between the two.

It looks like they post-trained Qwen3.6. Interesting to see how far they could improve it with they harness/algorithm.

Nobody (with the probable exception of Anthropic given their work on character training) really trains models on their identity and Claude is the only AI persona that's well-defined so if you put yourself into the AI's shoes it's a pretty reasonable guess that it might be Claude. I've had basically every open model claim it's Claude when the topic comes up.

Ornith-1.5-397B is derived from Qwen3.5-397B-A17B via post-training. That process preserves exact parameter count.

Yes: https://huggingface.co/collections/ornith-ai/ornith-15