@eisokant: Excited to launch http://MLX.fast with @eigenlabs today. It's an open autoresearch competition to make Laguna XS 2.1 in…
Summary
Eigen Labs launches an open autoresearch competition called MLX.fast to optimize inference speed of the Laguna XS 2.1 model on consumer Macs, aiming to make it as fast as possible via community contributions.
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Excited to launch http://MLX.fast with @eigenlabs today.
It’s an open autoresearch competition to make Laguna XS 2.1 inference as fast as humanly (and agentically) possible on consumer Macs.
Eigen’s agents already found 36.8% faster inference, and that’s before the competition even started.
The best part of open weights is that the community takes a model further than any of us could. Can’t wait to see what everyone does on the leaderboard!
https://mlx.fast
Gajesh (@gajesh): At 6% the size of DeepSeek V4 Pro, Laguna S 2.1 delivers significantly higher performance.
Today, we’re teaming up with @poolsideai to make Laguna XS 2.1 (same architecture as Laguna S 2.1) even faster on consumer Macs.
We’re launching MLX(.)fast: a public competition where
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