Odyssey-2 Max
Odyssey-2 Max is a scaled, real-time world simulation model designed to move beyond traditional generative AI by learning how the physical world behaves and enabling continuous, interactive environments. It represents the third and most advanced model in the Odyssey-2 family, significantly increasing scale with three times the parameters and ten times the training compute compared to Odyssey-2 Pro, which unlocks new emergent behaviors and more stable, realistic simulations. It is built to simulate physics, human motion, interaction, and environmental dynamics in real time, generating continuous streams of visual output that respond instantly to user input instead of producing fixed clips. Unlike conventional video models that generate short, precomputed sequences, Odyssey-2 Max produces long-running simulations that evolve frame by frame, allowing users to interact with the environment as it unfolds.
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FLUX 3 Action
FLUX 3 Action is an open-weight 7B world-action model designed for action prediction in robotics and other latency-sensitive visual environments. Derived from the multimodal FLUX 3 backbone, it was pretrained on large-scale image, video, and audio data with a strong emphasis on video, then adapted through joint video-action training and fine-tuning for specific embodiments and action spaces. Given an instruction, camera observations, and robot joint positions, the model predicts motor commands together with their expected visual outcomes, allowing a robot to execute actions, observe the environment again, and continuously replan. Unlike approaches that separate visual prediction from control, FLUX 3 Action jointly models future video and actions, transferring world understanding learned from broad video pretraining into robot control. Its single-step 7B checkpoint reaches a 38.3% success rate on RoboLab-120.
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Odyssey
Odyssey is a frontier interactive video model that enables instant, real-time generation of video you can interact with. Just type a prompt, and the system begins streaming minutes of video that respond to your input. It shifts video from a static playback format to a dynamic, action-aware stream: the model is causal and autoregressive, generating each frame based solely on prior frames and your actions rather than a fixed timeline, enabling continuous adaptation of camera angles, scenery, characters, and events. The platform begins streaming video almost instantly, producing new frames every ~50 milliseconds (about 20 fps), so you don’t wait minutes for a clip, you engage in an evolving experience. Under the hood, the model is trained via a novel multi-stage pipeline to transition from fixed-clip generation to open-ended interactive video, allowing you to type or speak commands and explore an AI-imagined world that reacts in real time.
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MiMo-V2.6-Flash
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MiMo-V2.6-Flash is an open-source, natively omnimodal AI model from Xiaomi MiMo designed to balance intelligence, efficiency, and cost. The model supports coding, general agent workflows, visual reasoning, computer use, automation, and multimodal creative tasks. Its capabilities extend beyond software engineering into frontend design, presentation creation, 3D modeling, interactive world generation, video production, and embodied simulation. Xiaomi trained MiMo-V2.6-Flash with large-scale reinforcement learning across coding, general agent, visual, and cybersecurity tasks, completing roughly 750,000 training trajectories. The model is positioned as the more cost-efficient member of the MiMo-V2.6 family while retaining strong performance across software engineering, tool use, automation, and visual coding benchmarks. MiMo-V2.6-Flash is available through MiMo Desktop, AI Studio, MiMo Code, the Xiaomi MiMo API Platform, OpenRouter, and the open-source MiMo-V2.6 release.
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