GPU for Rendering

Accelerate your video encoding, image pipelines, and 3D scenes using dedicated RTX GPUs. For short tasks and automation, try SDL deployment. If you also run AI/ML, see GPU rental in India for training and inference workloads.

Common tools

• FFmpeg (NVENC), HandBrake, custom CUDA pipelines
• Blender, Unreal, Unity (headless) for 3D renders
• Stable Diffusion and image upscalers for creative pipelines

Why Indianode

• On-demand GPUs with pay-per-minute billing
• Fast local NVMe, good for frame caches and intermediates
• Automate jobs via SDL deployment or simple tokens

Example SDL (batch render)

version: "2.0"
services:
  render:
    image: linuxserver/ffmpeg
    command:
      - /bin/sh
      - -lc
      - |
        ffmpeg -hwaccel cuda -i input.mp4 -c:v h264_nvenc -preset p5 -b:v 6M output.mp4
    expose:
      - port: 8080
        as: 8080
        to:
          - global: true
profiles:
  compute:
    render:
      resources:
        cpu:
          units: 4
        memory:
          size: 8Gi
        gpu:
          units: 1
          attributes:
            vendor:
              nvidia:
                - "3090"
deployment:
  render:
    dcloud:
      profile: render
      count: 1

You can paste a variant of this into our SDL deployment page and run it with a one-time token. For long jobs, compare costs on Pricing.

Tips

• Prefer NVENC/AV1 for faster encodes with good quality.
• Batch scenes and reuse cached assets on NVMe.
• For concurrent renders, scale out replicas instead of one giant node.

Questions? Contact us. Also explore LLM hosting or Whisper on GPU for AI-enhanced media workflows.