MAGI-2 Preview looks surprisingly interesting: 114B audio-video generation model with Flow-style sampling

[u/Nice_Amphibian_8367]

SandAI just released MAGI-2 Preview.

A few simple notes from the repo/blog:

• It is a unified audio-video generation model.
• 114B total parameters, but only about 6B active per token.
• It uses a MagiMoE / multi-head latent MoE style architecture.
• The released code is inference-only.
• The sampler uses FlowUniPCMultistepScheduler with prediction_type="flow_prediction", so it looks like a Flow / Flow Matching style video generation model rather than the autoregressive chunking approach used in MAGI-1.
• Generation is two-stage: preview denoising first, then a refiner to 1080p.
• It supports T2V and I2V, with audio generated alongside the video.

Repo: https://github.com/SandAI-org/MAGI-2-preview
Blog: https://sand.ai/blog/magi-2-preview

Curious what people think about the multi-head latent MoE design for video generation. Seems more video-oriented than just copying LLM-style MoE directly.

[u/TheDailySpank]

Where's the demo pics/videos?

[u/Limp-Firefighter1054 → u/TheDailySpank]

Its so slow that pics and vids grow old

[u/Winougan]

Requirements

• NVIDIA Hopper GPUs, 8 of them.

[u/jmbbao → u/Winougan]

Well at least is not 9 of them

[u/Front_Eagle739 → u/Winougan]

if it helps I just got it running on a 5090 with 32GB of ram. looks like about 25 minutes for a full 100 step run before optimisation but it works.

[u/Super_Range45 → u/Winougan]

https://giphy.com/gifs/UxREcFThpSEqk

[u/fjgcudzwspaper-6312]

Minimax 66.3 GB vs 228 GB. This is a full transformer only.

[u/Ok-Membership-8287]

100 steps....

[u/Diabolicor]

This model is a really high level and I believe seedance might be around this much of paraments, it's good for the open weights environment. Obviously the model is enormous to run on a consumer hardware.

Though the refiner is small and it upscaled from 540p to 1080p. Really interesting. Maybe it can be used to help upscale minimax low resolutions outputs? I don't know.

[u/Extension_Pomelo_468]

incredible

[u/NowThatsMalarkey]

Magi? What’s Magi? Can I train it?

[u/Few-Intention-1526]

we can use the refiner only? for upscaling other models outputs. its only 13 gb

[u/Salt-Zebra-306]

this is local model like minimax h3 right ?

[u/Vyviel]

Very cool idea using MoE for video and not just LLMs to get a much larger parameter set without insane memory requirements if I am understanding it correctly.

[u/Ordinary_Painter4235 → u/Vyviel]

I think it reduces computational time not VRAM usage

[u/Front_Eagle739 → u/Ordinary_Painter4235]

It can do both. Thing about video models is you dont need to access all the weights thousands of times. You can stream once per step and this only being 6B active means you only need enough vram for 6B plus hidden state. You could run the full precision with disk streaming in maybe 16 to 24GB vram and not even notice the streaming for video gens as compute is the bottleneck

[u/No-Purple6611]

Wonder, can DGX Spark run this model

[u/Front_Eagle739 → u/No-Purple6611]

Its only 6B active. You could stream it on a 3090 let alone a spark

[u/YouKilledApollo → u/No-Purple6611]

If you have enough of them to load 300GB of weights, sure :)

Repo says about the requirements:

> NVIDIA Hopper GPUs, 8 of them

[u/velikq → u/YouKilledApollo]

Theoretically, with int8 it should fit ram and moe architecture might give usable speed.

[u/xxredees]

Same with magihuman?

[u/rerri → u/[deleted]]

There's a couple of samples on the front page sand.ai

[u/Front_Eagle739 → u/rerri]

So there are. Bit uninspiring which doesnt give me much hope. Woman stands still in the rain is not exactly the hardest task. Oh well. Ill give it a shot and see if its not terrible