AI Video Render GPU Budget Planner

Forecast the compute budget for AI-generated video production. Enter the finished runtime, delivery frame rate, model throughput in frames per GPU-hour, and the hourly cost of your chosen GPU instance. Optionally specify how many GPUs you will spin up in parallel and the revision buffer you plan to hold for creative iterations. The planner returns required GPU-hours, buffered compute demand, cloud cost, wall-clock render duration, and the hours reserved for late tweaks so producers can set budgets and timelines with confidence.

Total runtime of the rendered deliverable including credits and titles.
Frames per second you plan to deliver in the final master.
Benchmark how many frames your model produces per dedicated GPU-hour on your target instance type.
All-in hourly rate for the chosen GPU instance including storage premiums.
Default 1. Enter how many GPUs you will rent in parallel to shorten wall-clock render time.
Default 20. Adds extra GPU-hours for alternate prompts, style passes, or QC rerenders.

Calculations assume constant render throughput and ignore queue delays, failed jobs, or spot-instance interruptions. Validate the inputs with a short test render and platform SLAs before committing budget to large production runs.

Examples

  • 6 minutes at 24 fps with a model delivering 1,800 frames/GPU-hour at $2.90/hr, one GPU, and a 20% buffer ⇒ 5.76 GPU-hours required, a $16.70 cloud bill, 5.76 hours (0.24 days) of render time, and 0.96 GPU-hours reserved for revisions.
  • 12 minutes at 30 fps, 1,400 frames/GPU-hour, $4.25/hr, four GPUs, and a 25% buffer ⇒ 19.29 GPU-hours needed, an $81.96 spend, 4.82 hours (0.20 days) to render, and 3.86 GPU-hours in the buffer.

FAQ

How do I factor in prompt experimentation?

Increase the revision buffer percentage or manually add expected experiment hours to the base GPU-hour total.

Can I mix GPU instance types?

Benchmark frames per GPU-hour for each instance type and run separate calculations, then combine costs in your production schedule.

Does this include asset storage or egress fees?

No. Add cloud storage, CDN egress, or edit suite charges to the final budget outside of this GPU-only estimate.

What if my team renders overnight?

Set concurrent GPUs to the number of rigs you plan to keep active overnight to ensure the timeline aligns with delivery windows.

How can I account for failed jobs or restarts?

Either increase the revision buffer to cover retry compute or add a separate contingency percentage equal to your historical failure rate.

Additional Information

  • Total frames multiply runtime by frame rate and determine base GPU-hour demand before buffers.
  • Revision buffer inflates base GPU-hours to cover alternative prompts, inpainting passes, or QC rerenders without pausing production.
  • Concurrent GPU count divides buffered GPU-hours to estimate wall-clock render time and overnight throughput.
  • Cloud cost multiplies buffered GPU-hours by the hourly rate; add storage, orchestration, or egress charges separately if billed.
  • Buffer hours show how much compute remains for late changes before budgets are exhausted, helping production leads allocate revision rounds.
  • If you mix instance types, run separate scenarios and sum GPU-hours to compare blended render schedules and costs.

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