🚀Introducing Intern-S2-Preview-397B, our most capable multimodal foundation model for scientific intelligence and long-horizon agents.🔥
1⃣Delivers a step change in general reasoning, scientific problem solving, and agentic capabilities.
2⃣A new pre-training paradigm preserves text-visual correspondence, strengthens spatial and visual reasoning, and improves data efficiency.
3⃣Achieves leading general-reasoning performance among open-source models and strong results in specialized scientific tasks by scaling diverse scientific RL tasks across 20+ domains and training them jointly.
4⃣Improves generalization and raises the capability ceiling for long-horizon tasks in both general and scientific domains by connecting multiple agent frameworks to large-scale sandboxed environments for black-box agentic reinforcement learning.
😉Model：
@huggingface
https://huggingface.co/internlm/Intern-S2-Preview-397B
@ModelScope2022
https://www.modelscope.cn/models/Shanghai_AI_Laboratory/Intern-S2-Preview-397B
😉GitHub:
https://github.com/InternLM/Intern-S1
😉Try it now at:
https://chat.intern-ai.org.cn
Intern-S2-Preview-397B: open multimodal model for science and agents
AIIntern Large Models releases Intern-S2-Preview-397B, a 397B-parameter open multimodal foundation model for scientific intelligence and long-horizon agents. The post says it leads open-source models in general reasoning and scores strongly on specialized scientific tasks, after training scientific RL tasks across 20+ domains jointly.
Intern Large ModelsOfficial
@intern_lm
Source details
Intern Large Models · x.comPublished · added here
Original title: 🚀Introducing Intern-S2-Preview-397B, our most capable multimodal foundation model for scientific intelligence and long-horizon agents.🔥