Comment by davecitron
2 days ago
Dave Citron here, from the MAI team. Thanks for the feedback, we're getting the model card updated to call out 5B active parameters (137B total).
On benchmarks: in the same VS Code harness, MAI-Code-1-Flash scored 51.2% on SWE-bench Pro vs. Haiku's 35.2% which we see as a pretty big leap. But going forward, we'll include additional models in our benchmarks, including models like Qwen 3.6 and Gemma 4.
Have you run it through DeepSWE? I understand that's probably a high ask for this class of model, but would be interesting to see regardless.
Even if it can't fully pass much, there are so many tests against most of the scenarios that you can get a fairly rich report beyond the pass@1 stat. See e.g. this DeepSWE report against the Minimax M3 model: https://entrpi.github.io/misc/deep-swe-minimax-m3/
Hey Dave, I’d love to add your new model in the harness I’m going to opensource very soonish. Going to publish benchmarks on real world tasks.
Qwen HAS to be a part of the discussion here, even though Microsoft is a US based entity. Their 30b MoE models absolutely hit way above their weight when paired with the right harness program, and can be ran on "Costco gaming computer" specs when configured correctly in llama.cpp.
Sorry Trump Administration, but while the US has been downloading more ram by throwing data centers at everything and burning up everyone's power and water, China has come out with what's effectively a prototype edge compute capable AI model - regardless of how they built it. And arguably I can tokenmaxx on it just fine at around 30-40 tokens/sec.
And also, ASICs are on the way. Imagine one of those with a heavy hitting model (MoE or otherwise, Qwen or otherwise) installed in a PCIe slot at 10k+ tokens/sec and 75 watts max (maximum wattage deliverable by the PCIe slot alone) for $300-400 USD each.
https://taalas.com/the-path-to-ubiquitous-ai/
ASIC demo here: https://chatjimmy.ai/
Sorry/not sorry to rip this whole thing to shreds. But I'm sick and tired of these inefficient LLMs being produced that seemingly can only be offered by subscription from a data center, when I'm running a full AI stack right now (model and all) on my computer at home on a 750 watt max power supply. Microsoft really needs to get with the picture here and compete more with Qwen instead of just the US/EU entities.
Sincerely, your neighbor down in Tacoma. https://www.youtube.com/watch?v=V9jlo4Ht2YA&t=229s