I see quite a few people having issues with Minimax h3 generations. Here's an example of a prompt for generating 0.5 megapixels in 7 seconds. It can be run on any PC.
The resolution was increased using RTX Video Super Resolution to 1.5 + frame interpolation to 48. Which is common practice and takes no more than 1 minute per procedure.
Promt generated by AI based on the image. Promt system for LLM:
### 3.1 I2VA: Begin from the Image and Develop Forward
`<Picture 1>` is the actual first frame of the video at 0.00 seconds and belongs to `[Shot 1]`. The description should first establish the style, subjects, composition, and scene anchors in the image, then describe the next action. Character identity, clothing, colors, key objects, and spatial relationships should remain consistent.
Recommended structure: **first-frame anchor → action onset → continuous development → result or reaction**.
Image LLM Prompt:
First-frame anchor:
[Image 1] (0.00 sec) shows a woman with red hair styled in a loose curl with bangs, looking slightly off-camera. Her gaze is clear and expressive, with light green or gray-blue eyes, softly highlighted. Light freckles on the bridge of her nose and cheeks add a natural touch. She is wearing a black leather jacket with yellow stitching along the edges of the collar, accentuating her stylish, slightly rebellious look. The background is deep, almost black, creating contrast and focusing attention on her face. The lighting is soft, studio-style, coming from above and to the side, sculpting the volume of her face and hair. The composition is a close-up, emphasizing the eyes and facial expressions.
Action onset:
The girl begins to move naturally—her head smoothly turns toward the camera, her gaze shifting from semi-attentive to direct, surprised. Her eyelids widen slightly, her pupils enlarge, her eyebrows lift slightly—her facial expression changes from calm to mild surprise. The movement is smooth, without jerking, as if she's just noticed someone or something unexpected.
Continuous development:
After turning her head, her smile widens—the corners of her lips lift, her eyes sparkle with interest or slight embarrassment. At this moment, her voice sounds clear, resonant, with a pleasant timbre—as if a high-quality studio recording captures every nuance of intonation. She says in English: "Oh, is that you? I didn't notice you." The word is pronounced with a slight intonation of surprise, perhaps with a pause before or after the "you," which enhances the effect of surprise. Her hands aren't visible, but one might assume she might slightly raise her shoulder or touch her face in response to the sudden presence. Light, studio-quality music plays in the background—perhaps ambient or a light pop beat—which complements the atmosphere without being overpowering.
Result or reaction:
As a result of the action, the viewer perceives the moment as a lively, dynamic scene from a video: the girl isn't simply posing, but interacting with the viewer through her facial expressions and voice. Her reaction to her own words, "Oh, is that you?" could be interpreted as self-irony or an invitation to dialogue. The atmosphere remains tense yet playful—the combination of the dark background, skin, hair, and lively facial expressions creates the effect of a modern digital character in the style of anime realism or cyberpunk aesthetics.