#Video

AIA ComfyUI developer generated 15-second 448×256 video in 15 seconds or less on one RTX 5090 using MiniMax H3 with FastVideo's FastH3 V2 checkpoint in four sampling steps. The setup combined sparse attention, a smaller ClipProj text encoder, a pruned INT8 checkpoint, and a fused FP4 MLP, cutting VRAM needs from 80GB to under 30GB. The custom ComfyUI node is open source.

AIPollo AI is using OpenAI's GPT-5.6, GPT-6 Astra, and GPT-Image-2.5 to help creators turn ideas into detailed images and cinematic video ads. The source gives no details on pricing, availability, or performance.

AILuma announced that Claude Motion animations can now open directly in Luma through an MCP connection, letting creators restyle them and reframe them to 9:16, 1:1, 4:3, or 21:9. Claude Motion, currently in beta on Claude Team and Enterprise plans, generates animated explainers from prompts, while Luma's Ray and Uni video models produce final video files.

AIThe article explains how to write AI video prompts that produce authentic claymation and stop-motion looks without physical sculpting or frame-by-frame photography. It stresses specifying material properties such as polymer clay with visible thumbprints, movement rhythm such as a 12fps animation feel, and negative prompts such as "no photorealism" to suppress glossy 3D defaults. It also includes 15 example prompts organized by material, texture, and category.

AIEffective AI horror video prompts depend on three elements: tension built before anything appears, lighting that hides more than it reveals, and a slow reveal that rewards viewer dread. The guide recommends a five-part prompt structure covering subject/setting, lighting source, camera movement, atmosphere, and action/reveal, with subtle modifiers like "almost imperceptibly" to restrain the action. It also includes 15 example prompts for creators building faceless YouTube channels or proof-of-concept trailers.

AIThis guide offers 15 sci-fi prompts for AI video generation across alien worlds, spacecraft, and practical effects, each built on a five-part structure of subject, sequence, setting, shot, and style. It argues that generation is only the start, with refinement, consistency, and delivery determining whether clips are usable in professional production.

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.

AIArtist 852話 Hakoniwa made YUI, the first animated short film created with Comfy Agent, in three days of focused work for about 200,000 yen excluding labor. She used the Agent to regenerate shots, compare video models such as Wan, MiniMax H3 and Seedance, and check outputs against her character sheet. The main film was made mostly with Seedance 2.5, and the making-of video with MiniMax H3.

AIManus 2.0 introduces Video Editor, which lets users refine videos Manus generates, including changes to music, captions, and cut timing, without regenerating the entire video. The article describes Manus creating explainers, launch films, and animations from a single prompt, drawing on web search, video models such as Seedance 2.5, and code for motion graphics.

AIComfy API is now available to all users on a paid Comfy plan, letting them package a ComfyUI workflow with its custom nodes, LoRAs, models, and Python dependencies and deploy it as an autoscaling API endpoint. Builds capture the ComfyUI version and dependencies, and each immutable release gets its own URL, so the tested environment is the deployed one. Usage is billed separately, with GPU time charged by the second and storage prorated hourly.

Why it matters: The post explains how a ComfyUI workflow is packaged into immutable releases and deployed as an autoscaling endpoint, showing a path from local graph to production service.

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.

AIKling AI says Kling 4.0 will support native video generation from 3 to 30 seconds, with up to 10 keyframes for timing control. The full model is scheduled for October 2026, with early access to the new creation page rolling out from September 28.

AIKling 4.0 is entering early access, with a wider rollout planned for October, and Kling 4.0 Flash opens to Ultra Yearly subscribers on September 28. The update generates videos up to 30 seconds in a single pass, accepts up to 15 reference assets, and supports up to 10 keyframe images. Upcoming features include 10-bit HDR output at 4K and 1080p and video extension up to 2 minutes.

Why it matters: The post specifies concrete capability limits such as 30-second native generation, up to 15 references, and 10 keyframes, which help users judge fit for production workflows.

AIGoogle Developers Blog describes how Sparse VideoGen (SVG) routes video diffusion attention heads into spatial or temporal sparse masks and implements them as custom JAX and Pallas Splash Attention kernels on TPU v6e. In isolated single-chip tests with 75.6K tokens and 10 heads, the sparse variants retain about 38.87% of query-key pairs. The article argues that theoretical sparsity must be converted into hardware tile skipping to yield real speedups.

AIManus 2.0 introduces a new agent harness called Cascade, Manus Studio with Video Editor and Game Dev environments, and a standalone Cue app for personal agents. In one tested configuration, Cascade used 23.2% fewer tokens, completed tasks 28.2% faster, and cost 32% less to run than the previous system. Cue is in early access and available with an invite code.

Why it matters: The post separates the new agent harness, Studio, and Cue, and its Cascade chart gives measured token, time, and cost comparisons against the previous system.

AIAmazon Neuron Science and Reactor collaborated to optimize Rolling Forcing, an autoregressive diffusion video model, for real-time generation on AWS Trainium. The model generates 16 frames per second, the standard video playback rate, meeting latency requirements for streaming video generation.

AIGoogle DeepMind has launched Gemini 3.8 Live with Live Avatar, which adds near real-time visual presence to its native live dialogue models. The feature is available today in Gemini Enterprise, supports 97 languages with adaptive lip-sync, and allows custom avatars through enterprise allowlisting. All output carries an imperceptible SynthID watermark.

Why it matters: The post specifies the new avatar capabilities, the Gemini Enterprise access path, and the SynthID watermark, which helps readers judge its enterprise deployment fit.

AIGoogle introduced Gemini 3.8 Live with Live Avatar, which adds a visual persona with lip-syncing and expressions to its live dialogue models. The feature is available in Gemini Enterprise and supports 97 languages, with custom avatars available through enterprise allowlisting. Google says all output is watermarked with SynthID.

Why it matters: The post specifies enterprise availability, custom avatar allowlisting, and 97-language support, which clarifies who can use the feature and how far it reaches.

AIGoogle says Gemini 3.8 Live with Live Avatar is now generally available in Gemini Enterprise, with US and EU endpoints, provisioned throughput, and enterprise compliance. Its video avatars use synchronized lip-syncing, custom avatars are limited to an allowlist, and generated audio and video carry SynthID watermarks. The model also understands and speaks 97 languages and can run tool calls in the background while the conversation continues.

AIKling AI's blog identifies six limitations of current AI video generation, including temporal consistency, character consistency across shots, unrealistic physics, long-form generation, fine details and text, and prompt control. It recommends workarounds such as reference images, shorter single-action clips, storyboards, and adding text or logos in post. The article says Kling VIDEO 3.0 and VIDEO 3.0 Omni offer reference-based subject consistency to help reduce these problems.

AIGoogle Labs released six new Google Flow Tools built by creatives across architecture, sound design, and digital content, including Mondo Sónico, CaptionCast, ThumbnailForge, Surface, CollageMotion Pro, and SwissFlow Studio. Each tool targets a specific workflow, such as generating synchronized audio stems, transcribing and styling captions, or producing animated collages from text prompts. Users can try the tools, duplicate and remix them, or build their own by describing a task in Google Flow.

AIComfy Router is now live on the Comfy Developer Platform, giving developers one API to call frontier image, video, 3D, and audio models. Day one models include Seedance 2.5, MiniMax H3, Nano Banana Pro, GPT Image 2, Kling, and Black Forest Labs, and the provider for each job is selectable. Requests fail rather than silently switching providers, and inputs and outputs are deleted after 24 hours.

Why it matters: The post shows how one API key and a provider parameter let developers swap routes for media models without rewriting calls, with failed requests reporting the provider.

AIComfyUI's update makes the MiniMax H3 video VAE encode up to about 2.2x faster and decode 1.4-2.7x faster, cutting a 1344x768, 129-frame round trip on an RTX 5090 from 24.3 to 12.7 seconds. The gains come from a fused encoder kernel enabled by default, fp16 accumulation support in a custom convolution, and an int8 decoder, and the source says the changes are visually lossless to the eye. Users need ComfyUI v0.36.0 or above, and the int8 VAE file is a drop-in replacement for the standard one.

AIvLLM now supports NVIDIA hardware video decoding through PyNvVideoCodec, moving video decoding off the CPU so multi-GPU video captioning can scale to 8 GPUs. In benchmarks on 8xH100 GPUs, GPU-based decoding provides more than double the throughput of the CPU-based decoder for Qwen/Qwen3-VL-8B-Instruct with 8 single-GPU vLLM replicas. The functionality is included in standard CUDA vLLM releases, and PyNvVideoCodec==2.0.4 is required for custom installations.

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.

AIAt an August 27 Ai2 event on expanding its work with the Paul G. Allen Research Center at Providence Swedish Cancer Institute, panelists identified five persistent challenges for scientific AI. The main ones are keeping AI steerable as research evolves, deciding which tasks to delegate, and avoiding the amplification of weak study design or bad data.

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.

AIGoogle released agentic video understanding for Gemini 3.7 Flash, Gemini 3.6 Flash, and Gemini 3.5 Flash-Lite across the Interactions and GenerateContent APIs. The model dynamically navigates video timelines, requesting transcripts, frames, or audio tracks on demand. The source says this approach uses up to 88% fewer tokens for long-form content than static processing.

Why it matters: The changelog names the affected models and API surfaces, and states a token-use figure that helps developers judge the cost of long video workloads.

AIGoogle is rolling out Gemini Omni 1.1 Flash updates in Google Flow, adding start and end frame controls to keep characters and narrative consistent between transitions. Creators can draft at 360p on lower credit cost, then export final clips in 720p, 1080p, or 4K for digital, social, or broadcast workflows.

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.

AIGoogle has released short films created by its fourth Flow Sessions cohort, a six-week creative partner program for artists. The program uses Google Flow, Google's creative studio featuring its advanced generative models, to support co-creation and passion projects.

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.

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.