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
Timeline (last 90 days)
Vlo has built-in workflows for several mainstream models, including Minimax H3, Qwen2.1, Krea2, and LTX2.5.
The workflow uses Flux 2 Klein for static images and Minimax H3 for video generation.
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.
Minimax H3 now supports int8 quantized model variants.
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.
Rendering video at 768×1024, 20 steps, without lightning LoRA on a 12GB GPU takes approximately 35 minutes.
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.
23 more timeline events
All Facts (20)
Prompt 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%UnverifiedRendering video at 768×1024, 20 steps, without lightning LoRA on a 12GB GPU takes approximately 35 minutes.
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%UnverifiedThe author's finished video was generated on the Kinovi AI platform, but they note that any Minimax H3 implementation is equally applicable.
50%UnverifiedMiniMax 3 is also known as Minimax H3.
50%UnverifiedMinimax H3 is a multimodal large model launched by Chinese AI company MiniMax, with capabilities for voice synthesis and character performance generation.
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%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%UnverifiedThe circle used for circle-based positioning does not have to be red; you simply need to adjust the prompt accordingly.
50%UnverifiedDrawing a circle on the water surface area of an image will cause the generated scene to appear in the water; the same effect holds when the circle is drawn over background buildings.
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%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%UnverifiedThe circle-drawing localization technique has the limitation of missing details.
50%UnverifiedUsers seeking higher fidelity may achieve better results by switching to max mode.
50%UnverifiedMatch mode tends to flexibly match the overall style and composition, while max mode more strictly preserves the details of the reference image.
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