Model reference · open weights

MiniMax-H3

Video MiniMaxAI Image→video 2 builds Its own licence terms 5.3M dl/mo

MiniMax-H3 is an open-weight video model from MiniMax. MiniMax-H3-GGUF (GGUF) weighs 18.2 GB; the smallest configuration that runs it is RTX 4090 24 GB.

For self-hosting, compare this build's requirements below with the GPU you plan to rent.

  • MiniMax-H3 is a 33.1B parameter omni-modal generative system developed by MiniMax for image-text-to-video generation.
  • It produces video with native stereo audio at resolutions up to 2K and durations of up to 15 seconds.
  • The model supports stable dialogue in 11 languages and is released under an other licence.

Summary of the MiniMaxAI/MiniMax-H3 model card, 2026-10-01. The estimate below is for another build of the family.

What it is

Released byMiniMax
Released2026-07-28
Parameters33.1B
VRAM18.2 GB for the weights

What it runs on

Memory and cards for MiniMax-H3-GGUF (GGUF)

18.2 GBweights, file size
537 MBruntime overhead
CardWeightsMemory
RTX 3060 12 GB … RTX 4060 Ti 16 GBdoes not fit
RTX 3090 24 GBfits23.4 GB
RTX 4090 24 GBfits23.4 GB
RTX 5090 32 GBfits31.0 GB
L40S 48 GBfits44.0 GB
A100 80 GBfits78.2 GB
H100 80 GBfits78.1 GB
RTX PRO 6000 Blackwell 96 GBfits93.8 GB
DGX Spark (GB10) 128 GB unifiedfits107 GB
H200 141 GBfits138 GB
B200 180 GBfits176 GB

Builds

Sizes, precisions & builds

BuildParamsPrecisionWeightsSmallest setup
MiniMax-H3 ↗ 33.1BBF16 498 GBB200 180 GB
MiniMax-H3-GGUF (above) ↗
packaged by unsloth
10 builds: Q2_K_XL 8.1 GB … Q8_0 42.9 GB
GGUF 18.2 GBRTX 4090 24 GB

From the model card

What MiniMax says about MiniMax-H3

Read the model card

News

Offical skills to improve prompt writing: skills on github

Online API

Use MiniMax-H3 directly via API.

Online App

Use MiniMax-H3 directly via App.

System Overview

MiniMax H3 is a general-purpose, omni-modal generative system. It supports unified understanding of multimodal contexts composed of text, images, video, and audio, and can generate video with native stereo audio at resolutions up to 2K and durations of up to 15 seconds. Thanks to its task-generalization-oriented system design, H3 already possesses broad multimodal context understanding and generation capabilities at the pre-training stage, enabling outstanding performance in following complex multimodal instructions.

H3 supports the following input and output specifications:

CategorySpecification
Output duration4–15 seconds
Output aspect ratioSupports a wide range of aspect ratios, including but not limited to 21:9, 16:9, 4:3, 1:1, 3:4, and 9:16
Output resolutionSupports various resolution dimensions. The shorter side is set to 768 pixels by default. 2K | generation can be achieved with H3-Regenerate-2K
Output frame rate24 FPS
Output audio32 kHz stereo
Supported dialogue languagesStable support for 11 languages: Arabic, Chinese, English, French, German, Italian, Japanese, Korean, Portuguese, Russian, and Spanish. Additional languages are also supported to varying degrees

Model Variants and Input Specifications

Model VariantInput ModeSpecifications
H3-Base-FL2VAFirst-and-last-frame modeSupports zero, one, or two input images. - No image input: Text-to-video mode - One image input: First-frame-to-video or last-frame-to-video generation - Two image inputs: First-and-last-frame-to-video generation
H3-Base-Ref2VAOmni-reference modeSupports multi-modal reference inputs: - Images: ≤ 9 images - Videos: ≤ 3 clips; each clip must be 2–15 seconds long; total duration ≤ 15 seconds - Audio: ≤ 3 clips; each clip must be 2–15 seconds long; total duration ≤ 15 seconds - Mixed inputs: Maximum number of files across all input types is 12

The complete H3 system consists of the following three modules:

  • H3-Context-IR: As inputs become increasingly complex, we build a dedicated system to deeply understand and refine the input multimodal instructions, then convert them into a form that H3 can readily understand—the Context Intermediate Representation—for generation. H3-Context-IR is critical to the quality of the final output, so we strongly recommend incorporating it into your generation pipeline or following the “Prompting Guidance” to build your own context-processing system.
  • H3-Base: Generates audio and video based on the H3-Context-IR output, producing results at 768p resolution.
  • H3-Regenerate-2K: Feeds the 768p result together with the original context back into H3 to regenerate the output at 2K resolution. This process leverages both H3’s powerful generative capabilities and the rich information contained in the original context, enabling it to produce high-resolution outputs with more accurate details and greater visual fidelity.

Model Architecture

H3-Context-IR

H3-Context-IR is a hosted preprocessing and orchestration system designed for free-form multimodal inputs.

It interprets the relationships among text, images, audio, and reference videos, as well as how these materials relate to the intended generation output. Its internal workflow includes instruction parsing, cross-modal association, temporal understanding, and complex logical reasoning.

H3-Context-IR serializes its understanding of the context into a structured representation accepted by H3-Base. Without deviating from the user’s original intent, it may also supplement missing or underspecified semantic details where appropriate.

Because H3-Context-IR relies on a multi-stage workflow and multiple hosted models and services, it is not included in this open-source release. We provide an API that enables users to reproduce the behavior of the official workflow. We also provide detailed tutorials, and developers can follow the Prompting Guidance to build their own preprocessing systems.

For detailed usage instructions, see Recommended Workflow — Full 2K Workflow.

Safety Guardrails

User-submitted text, images and videos, as well as enhanced prompts, are subject to automated moderation. Content suspected of being unlawful, pornographic, or infringing third-party rights may be blocked. We use industry-standard filtering measures but cannot eliminate false positives or false negatives. These guardrails do not affect the Licensee’s obligations under the MiniMax H3 Community License, especially those relating to lawful use and use restrictions.

H3-Base

Architecture Overview
  • H3-Base encodes different modalities using their corresponding encoders or VAEs and organizes the encoded representations into a unified packed multimodal sequence. RoPE is used to capture the necessary spatial and temporal relationships among tokens before the entire sequence is passed to the H3-Omni-Transformer.

  • Specifically, text is encoded by the H3-Encoder; visual inputs are encoded by both the H3-Encoder and the H3-VisualVAE; and audio is encoded solely by the H3-AudioVAE.

  • The H3-Omni-Transformer jointly predicts video and audio latents, which are then decode

Quoted from the model card on Hugging Face. The full card is behind the Hugging Face link above.

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