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vLLM day-0 support for Intern-S2-397B: multimodal, reasoning, coding, scientific agents

vLLM announced day-0 serving support for Shanghai AI Lab Intern-S2-397B. The 397B multimodal foundation model targets long-horizon scientific research and scientific agents, with strong multimodal, reasoning, coding, and agent capabilities. Developers can run it on vLLM today via the official recipe.

Key Takeaways

vLLM shipped day-0 serving for Intern-S2-397B across multimodal, reasoning, coding, and scientific-agent workloads.
Official recipe is at recipes.vllm.ai/internlm/Intern-S2-397B for immediate deployment.
Pairs with the same-day Intern-S2-397B weight/eval release already in the feed: open weights plus open serving stack.

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Linked Models & Agents:

⚡ Intern S2 397b🌐 shanghai-ai-lab

#vLLM#Intern-S2#Intern-S2-397B#Day 0#Serving#Open source

ModelScope@ModelScope2022·Collected 50d ago

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Shanghai AI Lab Intern-S2-397B ships BF16/FP8: 84.0 SWE-bench Multilingual, Apache-2.0

ModelScope announced Shanghai AI Laboratory Intern-S2-397B weights in BF16 and FP8 under Apache-2.0. Reported scores include 87.0 on FrontierScience-Olympiad and 84.0 on SWE-bench Multilingual, with long-horizon agent RL, tool use, and thinking/non-thinking modes. Training ingests raw scientific pages (text, visuals, symbols) across 20+ domains. Collection on ModelScope.

Key Takeaways

BF16 and FP8 weights are public under Apache-2.0 on ModelScope.
Reported 84.0 SWE-bench Multilingual and 87.0 FrontierScience-Olympiad as comparison leaders.
Long-horizon agent RL targets tool use and sustained execution, with thinking and non-thinking modes.

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Linked Models & Agents:

#Intern-S2#Intern-S2-397B#Shanghai AI Lab#ModelScope#SWE-bench#Apache-2.0#agent RL