Cosmos 3 vs ESMFold2

NVIDIA Cosmos 3 is the first open-source omni-model for physical AI, integrating world generation, physical reasoning, and action generation into one unified system. Built on MoT architecture, it supports robotics, autonomous driving, and synthetic data pipelines via Hugging Face and Diffusers.

NVIDIA releases Cosmos 3, the first Omni model integrating vision, language, sound, and action, built on Mixture-of-Transformer architecture, achieving top scores across multiple physical AI benchmarks with open weights for customization and edge deployment.

NVIDIA launches Cosmos 3, the first unified multimodal model integrating language, video, sound, and action inputs/outputs, built on Mixture of Transformer architecture, open-sourced with weights available on Hugging Face, achieving top scores across physical AI benchmarks including Robo Lab, PiBench, and Vintage.

NVIDIA releases Cosmos 3 (omnimodal world models), Nemotron 3 Ultra (550B LLM), and RTX Spark, driving open physical AI, with Cosmos 3 achieving SOTA in Text2Image and Image2Video.

NVIDIA unveiled major advancements at COMPUTEX, including RTX Spark for local AI agents on Windows, Vera CPU designed for AI agents with 1.8x performance boost, Cosmos 3 open model for robotics and autonomous driving, and Nemotron 3 Ultra, a 550B-parameter open-weight model competing with top models like Kimi K2.6 and Qwen 3.5.

NVIDIA Cosmos 3 can be customized for robot action prediction through post-training, supporting forward dynamics, inverse dynamics, and policy modes using Leo Robot V3 data format and joint configuration for efficient training.

NVIDIA launches Cosmos 3, the first omni-model for physical AI, supporting multimodal inputs and complex physical scene understanding, applicable to robotics, autonomous driving, and industrial simulation.

NVIDIA announces that Cosmos 3 is fully open-sourced, including model weights and post-training recipes, now available on Hugging Face for developers to use and research freely.

Biohub的Protein World Model通过ESMC-6B和ESMFold2处理68亿蛋白质和11亿结构，展示了生物建模可能像语言建模一样扩展，强调稀疏自编码器揭示模型内部生物学。

BioHub 发布 ESMFold2，展示通用语言模型在蛋白质折叠中的强大能力，挑战专有模型如 AlphaFold3。

ESMFold2 提供了最先进的性能来预测、设计和发现蛋白质生物学，特别是在抗体领域的表现尤为突出。