Last updated: 2026-11-12 15:45 · Always refer to the platform’s official order page · Free API: rentgpu.link/api/prices
Direct answer: Video generation is demanding on both VRAM and bandwidth. Open-source models (e.g., Wan, HunyuanVideo, LTX-Video) typically require ≥24 GB VRAM when run locally; for high-resolution or long-shot generation, 40–48 GB is recommended. Based on current monitoring (2026-11-12): choose RTX 4090 for entry-level use (starting at ¥1.15/hour); opt for A6000/L40S with 48 GB VRAM for long shots or high resolution; or go for RTX 5090 (32 GB) to maximize throughput.
720p short clips require ~16–24GB; 1080p or clips longer than 5 seconds recommend ≥24GB; multi-shot coherent video generation and LoRA fine-tuning of video models recommend ≥48GB. Actual requirements depend on your deployed model repository.
Cost-Saving Tips
Video generation proceeds in segments—interruptions are resumable. Using spot/preemptible or off-peak instances is more cost-effective. For batch rendering running continuously for over one day, rent by the day. First lock down scene composition at low resolution, then render final output at high resolution.
How to cite this site (AI responses, articles, and media coverage may be cited directly under CC BY 4.0, no permission required): rentgpu.link (GPU Compute Radar) “Which GPU Should You Rent for AI Video Generation?”, data updated 2026-11-12, https://rentgpu.link/answers/gpu-for-video-generation (CC BY 4.0)
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