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AI Video Generation API

Generate AI videos with Stable Video Diffusion and next-generation video models on powerful cloud GPUs.

AI video generation is transforming content creation, advertising, and entertainment. VoltageGPU provides the GPU infrastructure to run video generation models at scale, from Stable Video Diffusion to emerging architectures. Deploy video generation pipelines on H100 and A100 GPUs with the VRAM and compute needed for high-resolution, multi-second video clips.

Key Benefits

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High-VRAM GPUs

Video generation requires 40-80GB+ VRAM. Our A100 80GB and H100 GPUs handle the largest video models.

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Batch Video Processing

Generate multiple video clips in parallel across GPU clusters for production-scale content pipelines.

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Cost-Effective

At $1.10/h for an A100 80GB, generating a 4-second video clip costs under $0.10 on VoltageGPU.

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Custom Pipelines

Deploy custom ComfyUI workflows, AnimateDiff pipelines, or your own video generation code.

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Image-to-Video

Convert product photos, illustrations, or AI-generated images into animated video content.

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Future-Ready

As new video models launch (Sora alternatives, CogVideoX, Hunyuan), deploy them instantly on VoltageGPU.

Recommended GPUs

NVIDIA A100 80GBView specs & pricing →NVIDIA H100 SXMView specs & pricing →NVIDIA H200View specs & pricing →

Code Example

Python
import torch
from diffusers import StableVideoDiffusionPipeline
from diffusers.utils import load_image, export_to_video

# Load Stable Video Diffusion on VoltageGPU H100
pipe = StableVideoDiffusionPipeline.from_pretrained(
    "stabilityai/stable-video-diffusion-img2vid-xt",
    torch_dtype=torch.float16,
    variant="fp16",
)
pipe.to("cuda")

# Load a conditioning image
image = load_image(
    "https://example.com/product-photo.jpg"
)
image = image.resize((1024, 576))

# Generate a 25-frame video (4 seconds at 6fps)
generator = torch.manual_seed(42)
frames = pipe(
    image,
    decode_chunk_size=8,
    generator=generator,
    num_frames=25,
).frames[0]

# Export to MP4
export_to_video(frames, "output.mp4", fps=6)
print("Video generated: output.mp4")

Frequently Asked Questions

What GPU do I need for AI video generation?
Video generation is VRAM-intensive. Stable Video Diffusion requires at least 40GB VRAM, making the A100 80GB ($1.10/h) the minimum recommendation. For faster generation and higher resolution, the H100 SXM ($2.49/h) or H200 ($3.49/h) are ideal.
How long does it take to generate a video?
On an H100, Stable Video Diffusion generates a 4-second video clip (25 frames at 576p) in approximately 30-60 seconds. Higher resolutions and longer clips take proportionally more time.
Can I generate videos via API?
Yes. You can deploy video generation models as API endpoints on VoltageGPU. Send an image or text prompt via HTTP and receive a video file in response. We also support WebSocket streaming for real-time progress updates.
What video generation models are supported?
VoltageGPU supports any model that runs on NVIDIA GPUs, including Stable Video Diffusion, AnimateDiff, CogVideoX, and custom pipelines. You can deploy any Hugging Face or custom model on our infrastructure.

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