AIQuiet 4d · day 5
MiMo releases V2.6 with major open-source RL scaling effort
Open-source team dedicates dozens of researchers to one of the largest reinforcement learning runs attempted by a non-commercial model group.
What to know
- MiMo-V2.6 represents a significant compute commitment from an open-source team in an era of severe compute scarcity.
- The project required dedicating dozens of researchers to a single reinforcement learning scaling initiative.
- This is positioned as one of the largest RL runs attempted by a non-commercial model organization.
How it unfolded 1 development · click the chart to see its coverage posts
Sep 22Sep 23Sep 24yesterdaynow · 9:20 AM ET
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“MiMo-V2.6 is very likely one of the largest single RL runs, by compute, that any open-source model team has undertaken to date.”
— @_LuoFuli -
MiMo-V2.6: The Hard Road to Scaling Up RL MiMo-V2.6 is very likely one of the largest single RL runs, by compute, that any open-source model team has undertaken to date. In an era when compute is brutally scarce, we still chose to dedicate a team of several dozen people to one
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