Post-training gains for agents and scientific reasoning: Ling-3.1-flash-1019 is a 560B…
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Post-training gains for agents and scientific reasoning: Ling-3.1-flash-1019 is a 560B open-weight MoE with 25B active parameters per token and support for up to 1M context. 🤖 https://modelscope.ai/models/inclusionAI/Ling-3.1-flash-1019 🛠️ Stronger real-world agents: AA-Briefcase improves from approximately 1400 to 1524 Elo, while AutomationBench-AA rises from 62% to 68% versus Ling-3.1-flash. 🧠 Broader reasoning gains: Scores 44 on the Artificial Analysis Intelligence Index v4.3.2, up from 41 for its predecessor. 🔬 Better scientific performance: CritPt increases from 18% to 26%, and SciCode
Posted by ModelScope (16.7k followers) 2 days ago · 22 likes · 1.9k views · view the original post on X. Kept by the Dev Radar as AI dev tools. Tools mentioned: Step-5-Preview.
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