Microsoft
bioemu2 is a open-weight Microsoft specialized model.
Running this yourself: can likely run on your own machine.
Live access is not confirmed for this model. No current purchase price is advertised.
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25.5
Quality Score
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Arena ELO
Unknown
Parameters
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Context
This measures the amount of verifiable public evidence we have, not how capable the model is. A missing field means it has not been verified yet, not that its value is zero.
11 of 22 public signals
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Aug 2026
Released
1/5 signals
2/4 signals
3/5 signals
3/4 signals
2/4 signals
Gaps we are still tracking
Launches
3
Benchmarks
1
Research
1
General
5
Recent launch, pricing, benchmark, and API signals linked to this model or its provider.
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View source
More ways to discover, access, and build with MAI models. MAI models are now available through Vercel, giving developers another way to bring Microsoft AI models into the products and experiences they’re building. This includes our existing MAI models plus today’s newest
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The Muon optimizer incurs a significant overhead cost due to its cubic-time Newton-Schulz orthogonalization step. When weights are sharded, communication overhead compounds this computational cost, eroding the benefits of Muon in many settings. We present Dion3, a revision of Muon that targets this overhead at every level of the stack. Our Gram Newton-Schulz algorithm reduces the FLOP cost of orthogonalization, our CuteDSL kernels accelerate it by exploiting symmetry, and our megabatching strategy reduces communication overhead. Moreover, we propose a simple change to the update rule that cuts costs even further: selecting only a fraction of the momentum matrix's rows to orthogonalize at each step. This update rule improves on Dion (another "compressed" version of Muon), in both speed and performance. Overall, Dion3 matches or improves on the loss achieved by Muon but reduces optimizer step time by up to 6x. Dion3 is available via the dion package (https://github.com/microsoft/dion) as a drop-in replacement for Muon.