Which video model is best for 12GB GPUs?

CogVideoX-5B is the best choice for 12GB cards (like RTX 3060/4070). At 720p with Q4_K_M quantization, it uses approximately 11.3 GB VRAM, fitting comfortably with slight OS headroom.

Mochi 1 vs Wan 2.1: Which needs less VRAM?

Mochi 1 is significantly lighter (~30% less VRAM). While Wan 2.1 requires ~17.7 GB (24GB GPU) for 49 frames, Mochi 1 only needs ~12.2 GB, making it runnable on 16GB GPUs like the RTX 4060 Ti.

Can I run Z-Image Turbo on 8GB VRAM?

Yes, absolutely. With Q4_K_M quantization, Z-Image Turbo uses around 6.9 GB for 1024x1024 generation, leaving over 1GB headroom for the OS on 8GB cards.

Why is Flux.2 impossible on RTX 4090?

Flux.2 requires ~37 GB VRAM due to its massive Mistral 24B text encoder. This exceeds the RTX 4090's 24GB limit, requiring professional cards like the RTX 6000 Ada or aggressive CPU offloading.

AI Video VRAM Calculator: Flux.2, Mochi 1, Wan 2.1 & Z-Image (2025 Guide)

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Common VRAM Questions

CogVideoX-5B is your best choice.

According to our calculator, CogVideoX uses approximately 11.3 GB VRAM at 720p (Q4_K_M). This fits onto a 12GB RTX 3060 or 4070, leaving just enough headroom for the OS.
Note: Close your web browser to free up VRAM before running it.

Mochi 1 is significantly lighter (~30% less VRAM).

For a standard 49-frame video, Wan 2.1 requires about 17.7 GB (demanding a 24GB GPU), whereas Mochi 1 only needs around 12.2 GB. This makes Mochi 1 capable of running on 16GB cards (like the 4060 Ti 16GB) where Wan 2.1 would fail or run extremely slow.

Yes, absolutely.

With Q4_K_M quantization, the total VRAM usage is around 6.9 GB for standard 1024x1024 generation.
This leaves over 1GB of headroom, so it runs smoothly on 8GB cards (RTX 3060 Ti, 4060) without offloading.

Because it requires ~37 GB VRAM.

Flux.2 uses a massive Mistral 24B text encoder. Even at compressed Q4 settings, the weights and compute exceed the 24GB limit of the RTX 4090. To run Flux.2, you either need Enterprise GPUs (RTX 6000 Ada) or aggressive "CPU Offloading," which makes generation very slow.