Short Film Created on 4 GB VRAM Laptop Using One‑Node‑Flux‑2‑Klein and Wan 2.2 5b fp16
Experiment with One‑Node‑Flux‑2‑Klein and Wan 2.2 5b fp16 on a 4 GB VRAM GPU to validate short‑film generation times and VAE decoding behavior.
Experiment with One‑Node‑Flux‑2‑Klein on a 4 GB VRAM GPU to validate short‑film generation times and VAE decoding behavior.
Summary
User Future‑Aardvark‑1286 demonstrates a short film created on a laptop with an NVIDIA GeForce RTX 3050 Ti Laptop GPU, 4 GB VRAM, and 16 GB system RAM. The workflow combines promptdexter.com prompts with the One‑Node‑Flux‑2‑Klein node built by u/yanokusnir and the Wan 2.2 5b fp16 pipeline tailored for the hardware. Generation of each image takes roughly 400 seconds on average, while the Wan video pipeline requires about 500 seconds plus VAE decoding, extending to 29 minutes when the laptop is unplugged. The user leverages ChatGPT to generate continuous scene prompts, then uses Capcut for post‑production editing. An unexpected switch from VAE decode to VAE Decode Tiled occurs when running Wan, which the author notes. The post highlights the feasibility of high‑quality short‑film production on modest GPUs, encouraging others with similar specs to experiment. The author also mentions the potential of running LTX if the developer releases it. Overall, the example showcases practical limits and workflow tricks for low‑VRAM stable‑diffusion video generation.
Key changes
- GPU: NVIDIA GeForce RTX 3050 Ti Laptop GPU
- VRAM: 4 GB
- System RAM: 16 GB
- One‑Node‑Flux‑2‑Klein workflow used
- Wan 2.2 5b fp16 pipeline employed
- Generation time: ~400 s per image, ~500 s per video
- VAE decode switched to VAE Decode Tiled when running Wan
- ChatGPT used to generate continuous scene prompts