How to Use Mochi (Genmo) in 2026 (and a Hosted Alternative)

To use Mochi — Genmo's Mochi 1, an open-source text-to-video model — you generate clips one of three ways: through Genmo's own playground on genmo.ai, by running the openly released weights from Hugging Face on your own GPU, or through a community pipeline like ComfyUI. In every case you describe the shot in a text prompt and the model returns a short clip. Because Mochi is open-source, there is no per-generation price baked into the model itself — your real cost is either Genmo's playground plan or the GPU you own or rent to run the weights.

One thing to be clear about up front: Mochi is not available on Wandura. If you would rather skip the GPU setup and run frontier video models on a hosted, pay-per-generation balance, Wandura's text-to-video tool offers Sora 2, Veo 3.1, and Kling on a single credit balance — a hosted alternative to self-hosting Mochi, covered at the end of this guide.

This guide covers what Mochi is good at, how to run it step by step, how to prompt it, and what it actually costs.

What Mochi is good at

Mochi 1 is Genmo's open-source text-to-video model, released in late 2024 under the permissive Apache 2.0 license — which is a big part of why developers reached for it: you can download the weights, inspect them, fine-tune, and self-host without a proprietary API. It is built on Genmo's Asymmetric Diffusion Transformer (AsymmDiT) architecture and, at roughly 10 billion parameters, was one of the largest openly released video models at launch.

In practice, Mochi's strengths are strong prompt adherence and fluid, natural motion — Genmo highlighted both as design goals. The publicly released preview generates short clips at 480p, so it is best thought of as a research-grade, self-hostable engine for experimentation and fine-tuning rather than a polished one-click product. If you want a hosted AI video generator where several frontier models sit side by side, that is a different trade-off — more on that below.

How to use Mochi, step by step

There are two realistic routes: Genmo's hosted playground (no setup) or running the open weights yourself (full control). The steps below cover both.

1. Pick your route. Use the Genmo playground for a zero-setup trial, or self-host the weights if you need full control, fine-tuning, or offline generation.
2. For the playground: open genmo.ai, create an account, and find the Mochi text-to-video option — check the site for its current free and paid tiers.
3. For self-hosting: download the mochi-1-preview weights from Hugging Face and set up the environment (Genmo's repo and community tools like ComfyUI provide installers). Expect to need a high-VRAM GPU — the original requirements were steep, though community-optimized workflows brought it down to a single high-end card.
4. Write a clear prompt. Name the subject, the action, the camera move, and the style in one line (see prompting tips below).
5. Set your output options. Keep clips short for your first runs — the preview targets 480p, and shorter generations iterate faster and use less GPU time.
6. Generate, review, and iterate. Run the prompt, review the clip, then refine the wording or settings and re-run. Because you control the pipeline, you can tune sampler settings or fine-tune on your own footage.

Prompting tips for Mochi

Mochi rewards specific, visual prompts and is known for following them closely. A reliable pattern is subject + action + camera + lighting/style: "a red paper lantern drifting over a quiet river at night, slow upward tilt, reflections on the water, soft cinematic lighting" beats "a lantern". Describe motion explicitly ("slow dolly in", "handheld pan") and keep one main action per clip — stacking several movements into a single prompt tends to muddy the result. Because self-hosting lets you generate freely, take advantage of it: run two or three variations and keep the best.

Mochi access & cost (and a hosted alternative)

Mochi's pricing is unusual because it is open-source: the weights are free to download, so there is no fixed per-clip price the way a hosted API has. Your actual cost comes from one of two places. On Genmo's playground, you pay whatever plan Genmo offers (check genmo.ai for current free and paid tiers). If you self-host, your cost is the hardware — a high-VRAM GPU you own, or per-hour rental from a cloud GPU provider — plus your own setup time. That is powerful for teams who want control and can amortize a GPU, but it is real overhead if you just want a finished clip today.

A hosted multi-model platform trades that overhead for transparent per-generation pricing. Mochi is not on Wandura, but Wandura runs other frontier video models on a credit balance (1 credit = $0.01), billed per generation with the exact cost shown before you confirm. For scale: a 5-second Sora 2 clip starts at 315 credits (~$3.15) at 720p, and a 5-second 1080p clip runs roughly 440–580 credits on models like Kling 3.0 and Veo 3.1 — no GPU, no setup. See pricing for current packs and plans.

Mochi alternatives

If you like Mochi's open, self-hostable approach, other open-weight video models (from Genmo and others) are worth watching as the ecosystem matures. If instead you want frontier quality without managing hardware, a hosted AI video generator like Wandura lets you run Sora 2, Veo 3.1, and Kling from one balance and A/B the same prompt across them per shot. For a breakdown of how those hosted models compare on motion, realism, audio, and cost, see our Sora 2 vs Veo 3.1 vs Kling comparison — a practical starting point once you have decided that self-hosting Mochi is more than you need.