#Video

AIMiniMax says its open-source H3 model is almost on par with closed-source state-of-the-art video world models on physics. The claim is supported by a quoted benchmark, World Models' Last Exam in Physics, where eight leading models scored at most 57.76/100 across 40 physics tasks, and free-fall videos averaged only 26.61/100 on composite scores.

AIArtificial Analysis reports that Grok Imagine Video 1.5 Lite comes closest to the frontier in Architecture & Real Estate, Consumer, and Productivity & Knowledge Work use cases. It sits furthest from the frontier in Live-Action Film and Frontier use cases. Against Grok Imagine Video 1.5, Lite matches it in Social Media & Creator Content and trails it on the other nine use cases.

AIArtificial Analysis shares an AA-Video-T2V v2.0 text-to-video prompt, a 10-second product-page scene of a presenter revealing a volcano-shaped mist diffuser. The prompt specifies a shift from warm daylight to dim evening lamplight, fixed close-up camera angles, and consistent presenter and product appearance across shots.

AIAmong 12 models on AA-Video-T2V-Silent v2.0, Grok Imagine Video 1.5 Lite is the only one that is both fastest and highest quality, with no model beating it on both measures. It generates a 10-second 1080p clip in a median of 60.5 seconds. Kling 3.0 1080p (Pro) scores slightly higher but takes 94 seconds for a 5-second clip, while Vidu Q3 Turbo is 9 seconds faster on a 5-second 720p clip yet scores well below it.

AIGrok Imagine Video 1.5 Lite ranks #17 on AA-Video-T2V v2.0, two places above Google's Veo 3.1. At 1080p with audio, it costs $0.14 per second versus $0.40 per second for Veo 3.1. Compared with Grok Imagine Video 1.5, Lite is 44% cheaper at 1080p but ranks six places lower.

AISpaceXAI's Grok Imagine Video 1.5 Lite ranks #17 on both AA-Video-T2V v2.0 leaderboards, ahead of Google's Veo 3.1 at about a third of its price. It is the fastest model at its quality level in Artificial Analysis benchmarks, with a median of 60.5 seconds for a 10-second 1080p clip, and it costs $0.14 per second at 1080p, 56% of Grok Imagine Video 1.5's $0.25 per second.

AIOdyssey has launched Odyssey-3, its most powerful foundation world model, with a public research preview. Odyssey-3 Pro scored 66.1 on Physics-IQ Verified video-to-video with best-of-8 sampling, the highest reported result. The model generates environments from prompts and predicts changes in real time as users move through scenes.

AIOdyssey 3 Pro, a world model, is now live as a research preview and ranks first on the Physics-IQ Verified video-to-video benchmark. The post says it can learn from visual observations and map that knowledge to physical controls for robots, cars, video games, and drones. Odyssey-3, the model launched alongside it, is described as free to try.

AIOdyssey has released Odyssey-3, which it describes as a major leap toward world models that power physical AI, generate training environments, and enable new human experiences. The post invites readers to try Odyssey-3 at the company's website but gives no specific benchmarks, parameter counts, or pricing.

AIOdyssey announced Odyssey-3, a foundation world model it says enables applications in physical AI, human experiences, and training intelligences. The company highlights agents learning from experience inside Odyssey-3 while working toward objectives.

AIOdyssey-3 Pro achieved a score of 66.1 on Physics-IQ Verified's video-to-video benchmark, the highest reported score so far. Physics-IQ evaluates physical behavior across fluid dynamics, optics, solid mechanics, magnetism, and thermodynamics.

AIOdyssey-3 is a new world simulator that generates interactive environments from a prompt in real time. It learns representations of physics, dynamics, and cause-and-effect from a broad dataset of visual observations.

AIKling AI is showcasing videos creators have made with its Kling 4.0 and Kling 4.0 Flash models. The post is promotional and includes no specifications, benchmarks, pricing, or feature details.

AINVIDIA has released PixelUMM, an encoder-free unified multimodal model with 15,199,672,064 parameters that handles text, image, and video understanding and generation directly in pixel space. It represents images as 16-by-16 RGB pixel patches on a Qwen3-8B language backbone, with iterative denoising for generation. The checkpoint is licensed for non-commercial research or evaluation only, while the source code is under Apache License 2.0.

AIAlibaba's Wan 3.0 ranks #1 overall on the new Artificial Analysis AA-Video-T2V v2.0 text-to-video leaderboard, priced at $12 per minute of video. The benchmark judges models at 1080p using over 68,000 human preference votes across 1,000 prompts, and the author states Wan 3.0 leads 10 of 20 category boards.

AICreatify Labs released Boreal-H3, a video model built on MiniMax H3 and post-trained specifically for advertising. Reported results include 85.3% reference fidelity, brief success rising from 28% to 50%, and identity match improving from 83% to 94%. Visible defects per clip dropped 70%, while generation time and estimated cost fell 20%.

AIInSpatio-World 1.5 from InSpatio_AI turns a single image, four images, a panorama, or a video into a navigable scene with wide viewpoint changes. The 1.3B model scores 68.72 on WorldScore-Dynamic, ranking first among evaluated real-time and interactive methods, with speeds up to 24 FPS. The post says the code is released under Apache 2.0 and that dependencies keep their own licenses.

AIKling 4.0 extends native single-pass video generation from 15 to 30 seconds and adds Multiple Keyframes supporting up to 10 keyframe images, versus Start & End Frames in Kling 3.0. It also expands reference inputs to up to 15 combined assets, including up to 5 videos totaling 30 seconds, and adds 10-bit HDR at 1080p and 4K. The all-new Kling 4.0 will officially launch in October, and Kling 4.0 Flash became available to a limited group of early-access users on September 28.

AIWan (@Alibaba_Wan) promoted its motion control and animation capabilities with a short post, calling the results solid. The post includes no specifications, benchmarks, or availability details. A related Wan 3.0 experiment shared by another account shows a combat sport motion demonstration.

AIinclusionAI has published Realtime-Venus on Hugging Face with two 9B checkpoints: Realtime-Venus-Omni for audio-visual interaction and Realtime-Venus-Audio for audio-only conversation. Both are built on MiniCPM-o 4.5 with a Qwen3-8B backbone and support full-duplex dialogue, proactive responses, and training-free long-video memory. The asynchronous Realtime-Venus-Harness runtime is hosted in a separate GitHub repository.

AIOdyssey announced Odyssey-3, a foundation world model it describes as a major step forward. The post claims it can control robots, power humanoids, drive cars, train AIs, pilot drones, and play video games, though it gives no benchmarks or technical specifications.

AIShanghai AI Lab's InternLM has published Intern Lumina U2, a 16B-parameter MoE model with 1B active parameters that handles text QA, image generation and editing, and image, video, and 3D understanding. The model uses an 8-codebook fully-discrete visual representation built on AToken. Checkpoints are provided for Huawei Ascend NPUs and NVIDIA GPUs under Apache 2.0, with the technical report still listed as coming soon.

Why it matters: The model unifies text, image, video, and 3D understanding with image generation in one framework, a broader scope than single-modality releases.

AIByteDance has released Bernini-Diffusers-v2 on Hugging Face, a video generation and editing pipeline combining a Qwen2.5-VL planner with Wan2.2 diffusion components. The model card recommends it over Bernini-R for complex requests needing stronger instruction following and multi-step semantic planning. Code and weights are available under Apache License 2.0.

AIMiniMax launches H3, a general-purpose multimodal generation model that understands text, images, video, and audio as unified context. It generates video up to 15 seconds at 2K resolution with native stereo sound, and the company says model weights will be opened in the coming days, subject to applicable laws and regulations. MiniMax also says H3 is priced below mainstream models at 2K and 768p.

Why it matters: The post explains how a unified multimodal design and training choices enable 2K video with native stereo sound, useful for comparing against closed video generators.

AIMiniMax released H3, an open-weights omni-modal model that generates video with native stereo audio up to 2K and 15 seconds. The system combines H3-Context-IR preprocessing, the H3-Base generator at 768p, and H3-Regenerate-2K for 2K output, with the Context-IR and 2K modules available only through API.

Why it matters: The source details a three-module pipeline and open weights with deployment paths, showing how a video model is served and reproduced locally.

AIBlack Forest Labs released FLUX 3, a multimodal model trained on images, video, and audio, and mimic built FLUX-mimic on its video backbone to control robots. In a soft-body kitting task, mimic reports a 95% success rate without single-task fine-tuning, compared with 55% for an adapted π0.5 model. FLUX 3 Video is in early access, with action prediction offered to selected partners and an open-weight backbone planned.

AIMeta Superintelligence Labs has released Muse Image, which can invoke search and coding tools and self-refine its generations before output. It is available today in the Meta AI app, meta.ai, Instagram Stories in the US, and WhatsApp in limited countries, with Facebook coming soon. Meta also previewed Muse Video, which is coming soon to creators and Meta AI and is reported as ranking No. 3 on Arena for text-to-video at the time of writing.

Why it matters: The source describes how search, code execution, and self-refinement change image generation, which matters to anyone comparing agentic media models with plain prompt-to-image systems.

AIByteDance open-sourced inference code and model weights for Bernini-Diffusers, a full video generation and editing pipeline with an MLLM-based semantic planner and a DiT-based renderer. The release bundles a Qwen2.5-VL planner and Wan2.2 diffusion components in one self-contained directory, and the source recommends it over the renderer-only Bernini-R for complex instruction following.

AIByteDance's Sa2VA-Qwen3-VL-4B-SAM3 is built on Qwen3-VL-4B-Instruct with a SAM3 grounding encoder and produces dense image and video referring segmentation alongside chat. It reports 83.7 cIoU on RefCOCO val, 65.3 J&F on MeViS (val_u), and 77.1 on Ref-DAVIS17. The checkpoint is self-contained and loads on Hugging Face with trust_remote_code=True, with no extra packages required.

AIZ.ai released SCAIL-2, an open-source model that animates a reference character from a driving video without skeleton maps or inpainting masks. It also supports character replacement, multi-character scenes, and animal-driving, with 512p and 704p resolutions and inputs whose height and width are both divisible by 32.

AIByteDance has open-sourced the 1.3B-parameter weights of its Bernini Renderer (Bernini-R), available on Hugging Face as ByteDance/Bernini-R-1.3B-Diffusers. Fine-tuned from Wan2.1-1.3B, the model performs close to the 14B variant on simple tasks such as style transfer, subtitle or watermark removal, and local editing, but lags on complex tasks such as human generation. The release requires a CUDA GPU, with an H100 recommended for FlashAttention-3.

AIPrismAudio is a framework that integrates reinforcement learning into video-to-audio generation, using a Chain-of-Thought planning mechanism. It builds on ThinkSound by splitting single-step reasoning into four CoT modules for semantic, temporal, aesthetic, and spatial dimensions, each with targeted reward functions. Code, model weights, and datasets are released for research and educational use under the MIT License, and commercial use requires explicit author authorization.

AIXiaomi introduces MiMo-V2-Omni, a single model that fuses image, video, and audio encoders into a shared backbone with native tool calling and UI grounding. The company reports benchmark results against Gemini 3 Pro, Claude Opus 4.6, and GPT 5.2, and demonstrates browser-based shopping and video-publishing workflows run through the OpenClaw agent scaffold. It also states the model supports over 10 hours of continuous audio understanding.

Why it matters: The page gives benchmark comparisons, a driving-risk demo, and browser-task walkthroughs, letting readers check how far the omni-modal claims extend into agent use.

AIRunway announced GWM-1, its first general world model family, built on Gen-4.5 and generating frames autoregressively in real time under interactive control. It comes in three variants: GWM Worlds for explorable environments, GWM Avatars for conversational characters, and GWM Robotics for robotic manipulation. Runway also says it is working toward unifying these domains under a single base world model, and GWM Robotics includes a Python SDK.

Why it matters: The post separates three GWM-1 variants and ties each to a concrete use, which clarifies where a general world model would fit compared with a single model.

AIRunway announced Gen-4.5, a video generation model that it says holds the top position on the Artificial Analysis Text-to-Video benchmark with 1,247 Elo points. The model is available across all paid Runway plans at comparable pricing, and the post lists limitations including causal reasoning errors, object permanence failures, and success bias.

Why it matters: The post separates Runway's own ranking claim from the listed limitations, such as causal reasoning and object permanence errors, which helps judge where the model is reliable.