Wan2.1 I2v 720p 14b Fp16.safetensors __top__ 🎯 Trusted Source

Generating fewer frames per video reduces both VRAM usage and inference time. Many workflows use 33 to 81 frames, but the model can generate longer sequences.

This denotes the numerical precision of the model weights. balances high fidelity with computational efficiency. It allows the model to run on modern consumer and enterprise GPUs without the severe quality degradation sometimes seen in heavily quantized 8-bit or 4-bit versions. 6. .safetensors (The Secure Storage Format)

: Place wan2.1_i2v_720p_14b_fp16.safetensors into your ComfyUI/models/checkpoints/ or ComfyUI/models/diffusion_models/ folder, depending on your workflow structure. wan2.1 i2v 720p 14b fp16.safetensors

"A woman in a red raincoat walks through a puddle. The water splashes upwards. The lighting is overcast. 24fps, cinematic."

If you are running this model on consumer hardware like an RTX 4090, you will likely need to employ optimization strategies within your UI ecosystem (such as ComfyUI or WebUI): Generating fewer frames per video reduces both VRAM

The tag signifies the parameter count of the neural network—specifically, 14 Billion parameters .

: This filename likely appears in a download link on Hugging Face or a torrent for a community-run video generation pipeline (e.g., ComfyUI custom node). To actually run it, you’d need a script that loads the .safetensors into a model definition matching the Wan2.1 i2v architecture. balances high fidelity with computational efficiency

Sample workflow snippet (Conceptual):

If you want to optimize this for your specific setup, let me know: What and how much VRAM you have