Minimax H3
A video generation model released by MiniMax that supports reference-to-video capabilities. Given a single reference image, the model can identify multiple independent objects within it and accurately reconstruct them in generated video output.
Core Facts
MiniMax H3 is a multimodal video generation model capable of simultaneously generating video frames and matching audio (including dialogue, sound effects, and ambient sound).
Prompt Studio can generate structured MiniMax H3 video scripts.
Timeline (last 90 days)
Vlo has built-in workflows for several mainstream models, including Minimax H3, Qwen2.1, Krea2, and LTX2.5.
Minimax H3 now supports int8 quantized model variants.
OmniChar is an open-source solution that encapsulates a character's facial, body, and clothing features in a portable .char file and integrates with the Minimax H3 video generation pipeline.
The workflow uses Flux 2 Klein for static images and Minimax H3 for video generation.
Rendering video at 768×1024, 20 steps, without lightning LoRA on a 12GB GPU takes approximately 35 minutes.
The author uses the Minimax H3 default FL2VA first-and-last-frame video generation workflow in ComfyUI, setting the input image as both the first and last frame to form a closed-loop orbit shot.
Video generation models only guarantee visual plausibility of frames and do not guarantee geometric/physical consistency across frames, causing splat training to generate floating noisy Gaussian blobs (garbage data) in inconsistent regions.
Prompt Studio can generate structured MiniMax H3 video scripts.
MiniMax 3 is also known as Minimax H3.
The author's finished video was generated on the Kinovi AI platform, but they note that any Minimax H3 implementation is equally applicable.
24 more timeline events
All Facts (20)
MiniMax H3 is a multimodal video generation model capable of simultaneously generating video frames and matching audio (including dialogue, sound effects, and ambient sound).
90%VerifiedPrompt Studio can generate structured MiniMax H3 video scripts.
80%UnverifiedVlo has built-in workflows for several mainstream models, including Minimax H3, Qwen2.1, Krea2, and LTX2.5.
50%UnverifiedThe workflow uses Flux 2 Klein for static images and Minimax H3 for video generation.
50%UnverifiedOmniChar is an open-source solution that encapsulates a character's facial, body, and clothing features in a portable .char file and integrates with the Minimax H3 video generation pipeline.
50%UnverifiedVideo generation models only guarantee visual plausibility of frames and do not guarantee geometric/physical consistency across frames, causing splat training to generate floating noisy Gaussian blobs (garbage data) in inconsistent regions.
50%UnverifiedThe author uses the Minimax H3 default FL2VA first-and-last-frame video generation workflow in ComfyUI, setting the input image as both the first and last frame to form a closed-loop orbit shot.
50%UnverifiedRendering video at 768×1024, 20 steps, without lightning LoRA on a 12GB GPU takes approximately 35 minutes.
50%UnverifiedMiniMax 3 is also known as Minimax H3.
50%UnverifiedThe author's finished video was generated on the Kinovi AI platform, but they note that any Minimax H3 implementation is equally applicable.
50%UnverifiedVoice/performance models such as Minimax H3 support embedding emotion tags within text scripts to control a character's tone and mood.
50%UnverifiedCreators say the model can understand far more emotion tags than those listed in the public documentation, with hidden tags that are not officially documented but can still be recognized.
50%UnverifiedMinimax H3 is a multimodal large model launched by Chinese AI company MiniMax, with capabilities for voice synthesis and character performance generation.
50%UnverifiedThe circle-drawing localization technique has the limitation of missing details.
50%UnverifiedDrawing a circle on a reference image in Minimax H3 allows you to specify the exact location within the image where an AI-generated scene will appear.
50%UnverifiedThe circle used for circle-based positioning does not have to be red; you simply need to adjust the prompt accordingly.
50%UnverifiedMatch mode tends to flexibly match the overall style and composition, while max mode more strictly preserves the details of the reference image.
50%UnverifiedUsers seeking higher fidelity may achieve better results by switching to max mode.
50%UnverifiedCircle-based positioning essentially converts the user's hand-drawn annotations into a lightweight spatial condition, with the model jointly parsing the region mask and the text prompt.
50%UnverifiedCompared to full ControlNet, the circle-drawing localization method has a lower technical barrier for users, but its control precision is relatively coarse-grained.
50%