Each has it's pros and cons. Dense models of equivalent total size obviously do run slower if all else is equal, however, the fact is that 35A3B is absolutely not 'a lot smarter'... in fact, if you set aside the slower inference rates, Qwen3.5 27B is arguably more intelligent and reliable. I use both regularly on a Strix Halo system... the Just see the comparison table here: https://huggingface.co/unsloth/Qwen3.6-35B-A3B-GGUF . The problem that you have to acknowledge if running locally (especially for coding tasks) is that your primary bottleneck quickly becomes prompt processing (NOT token generation) and here the differences between dense and MOE are variable and usually negligible.

"…whereas 35A3B is a lot smarter…"

Must. Parse. Is this a 35 billion parameter model that needs only 3 billion parameters to be active? (Trying to keep up with this stuff.)

EDIT: A later comment seems to clarify:

"It's a MoE model and the A3B stands for 3 Billion active parameters…"

That makes no sense. If you were just going to release the "more hype-able because it's quicker" model then why have a a poll.

What? 35B-A3B is not nearly as smart as 27B.