Mochi

Mochi is an open-source Text-to-Video Foundation Model developed by Genmo to advance accessible, high-quality generative video Technology. designed to unlock AI’s creative potential — what Genmo calls the 'right brain' — Mochi delivers Professional-grade motion synthesis without requiring proprietary infrastructure or paywalled access. It Stands out in the AI video landscape for its combination of open weights, permissive licensing (Apache 2.0), and architectural innovations tailored specifically for spatIoTemporal fIDElity.

What it does

Mochi transfORMs plain text Prompts into coherent, temporally consistent video CLIPs up to 480p resolution. Unlike many closed or API-only video generators, Mochi provides full model weights, training code, and inference tooling — enabling Local Deployment, fine-tuning, and community-driven improvements. Its ouTPUt emphASIzes natural motion, accurate prompt interpretation, and support for complex dynamics like fluid flow and hair simulation — pushing toward photorealistic motion without falling into the uncanny valley.

Key capabilities

• High-fidelity Video Generation: Produces smooth, artifACT-minimized CLIps with strong inter-frame continuity and realistic physics-based motion.
• Robust prompt alignment: Uses a single T5-XXL encoder to translate text into latent space, ensuring precise control over subjects, scenes, actions, and stylistic cues.
• Efficient asymmetric architecture: Built on a 10B-parameter diffusion model with AsymmDiT — a novel non-symmetric Diffusion Transformer that reduces memory overhead while preserving visual quality.
• Video-aware compression: LeveRAGes a custom video VAE to compress temporal data efficiently, accelerating Inference and lowering hardware requirements.
• Ethical safeguards: Includes built-in safety filters in Genmo’s Playground interface to prevent hArmful or non-compliant outputs — though self-hosted deployments may require additional moderation layers.

Who it is for

Mochi serves researchers exploring next-generation video diffusion, developers building custom video pipelines, indie creators seeking royalty-free generative assets, and educators generating illustrative content. Its open nature also benefits robotics and autonomous systems teams needing synthetic video data for simulation and training.

How to get started

Users can begin immediately via Genmo’s Free web-based Playground for quick experimentation. For deeper integration, developers can download model weights and source code from Genmo’s official repository. Local inference requires a GPU with at least 24GB VRAM; documentation and API examples are provided to support integration into existing Workflows or custom UIs.

Pricing and access caveat

Mochi is fully Open Source and free for both Personal and commercial use under the Apache 2.0 license. There are no usage tiers, credits, or subscriptions. However, high-resolution upgrades (e.g., 720p) and extended duration support have not yet been publicly released — their availability may vary. While the Playground offers free access, self-hosted deployments require technical setup and compatible hardware; cloud inference options are not officially documented and may vary by third-party implementation.