Local Text-to-Video Model Rankings

RTX 3060 12GB can run 1.3B/480P; 14B is best with 24GB VRAM plus offload.

RTX 4090/5090 24GB or a 48GB workstation GPU, 64GB RAM, 150GB SSD.

• The official repo lists about 8.19GB VRAM for T2V-1.3B, making it practical for consumer GPUs.
• 14B has better quality but needs much more VRAM, storage, and render time.

The 8.3B model targets consumer GPUs; practical use is best from 16GB-24GB VRAM.

RTX 4090/5090 24GB, 64GB RAM, 120GB SSD.

• Good for local creators who care about image quality and motion stability.
• Text-to-image is not a core capability; pair it with FLUX.1, SDXL, or SD3.5 for keyframes.

RTX 4060 8GB can use quantized workflows for short 720x480 clips.

12GB-16GB VRAM, 32GB RAM, 80GB SSD.

• Its main strength is speed and local iteration, useful for storyboards and motion drafts.
• Final hero shots can be rerun in Wan or HunyuanVideo for higher quality.

The 5B model is best with 12GB-16GB VRAM; lower VRAM needs quantization or CPU offload.

RTX 3090/4090 24GB, 64GB RAM, 100GB SSD.

• There is a large body of text-to-video material, making it useful for controlled tests and integration.
• Image-to-video depends on specific model variants or community workflows, so confirm the checkpoint first.

24GB VRAM is the practical starting point; long clips and high resolution raise VRAM and storage needs quickly.

48GB VRAM or multi-GPU, 128GB RAM, 200GB SSD.

• Useful for long-video consistency research, but harder to deploy locally than short-video models.
• Before production use, confirm both the license and required model weights.

24GB VRAM is recommended; lower VRAM needs community quantization and offload.

RTX 4090 24GB or a 48GB workstation GPU, 64GB RAM, 120GB SSD.

• It has a strong visual style, but I2V and T2I are not the native main path.
• Good as a comparison model or for stylized shot experiments.