SGLang
@sgl_project
Run LLMs fast at any scale 🔗
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Joined May 2025
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Congrats to the @cognition team on the SWE-2 launch! It’s especially exciting to see SpecForge helping improve speculative decoding acceptance within the training stack. We’re proud to have contributed to this effort 🙌
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Introducing SWE-2, our closest model yet to the frontier.
On leading evals, it scores on par with recent frontier models – at up to 70% lower cost.
We scaled RL to multiple trillions of parameters, with a refined recipe that pushes the Pareto curve on both capabilities & cost.
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