MiniMaxMiniMax·🎬 Video Generation

MiniMax H3 Max Recast

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Quick reference
MiniMax H3 Max Recast — TLDR
  • 🎬 Video generation model from MiniMax's H3 Max tier
  • 🎯 "Recast" variant focused on reworking existing footage
  • 🏢 Built by MiniMax, a Chinese multimodal AI lab
  • 🎨 Suited to stylistic reinterpretation and creative video output
  • 🧩 Part of a broad H3 family spanning text-, image- and reference-to-video
💰 Pricing
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📅 On Venice since
Oct 7, 2026
22 days ago
Provider

MiniMax is an AI company building generative models across multiple modalities, with a focus that spans both language understanding and audio creation. Their rapid release cadence in early 2026—delivering several new models within just a few months—reflects…

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21 models on Venice
12 video · 5 text · 3 music · 1 tts
Since Feb 12, 2026

About this model

MiniMax H3 Max Recast sits in the top "Max" tier of MiniMax's H3 video generation family, arriving in October 2026 as a specialised variant alongside the lab's other H3 Max entry points. Where MiniMax H3 Max covers straightforward prompt-to-video and the image-to-video variant animates a still frame, Recast is the lineage's reworking mode — aimed at taking existing material and recasting it into new form rather than generating from a blank slate.

The H3 family is unusually wide for a video lineup: it spans the baseline H3 models, the H3 Enhanced quality tier, the latency-optimised H3 Max Turbo, reference-conditioned H3 Max R2V, and the camera-control-oriented H3 Max Multi-Angle. MiniMax pairs these with text models in the M series and generative audio work such as MiniMax Music 2.6 and Speech-02 HD.

Best suited to creators who already have source footage or a defined visual concept and want a high-quality transformation of it — restyling, reinterpretation, and iterative creative passes — rather than one-shot generation from a text prompt alone.

This About section is AI-generated from public sources (Claude Opus 5), with no human editing. It may contain inaccuracies — verify critical details against the sources listed above.

Data sources: Venice API · HuggingFace · Wikipedia — enrichment updated 1d ago