Why throughput matters more than you think
When working with AI platforms — whether for image generation, video rendering, or text processing — throughput directly impacts your bottom line. Higher throughput means more content produced per hour, faster iteration cycles, and better resource utilization. Yet many creators and developers leave significant performance on the table by not optimizing their workflow.
Domer's AI video generator is built with performance in mind, but understanding how to optimize your usage makes a real difference.
Understanding the performance bottlenecks
AI generation tasks typically face three types of bottlenecks:
- Queue latency: How long your job waits before processing starts
- Compute time: The actual GPU time needed to generate your output
- Transfer time: How long it takes to move data between systems
Optimizing each of these requires different strategies.
Strategies for maximizing throughput
Batch your requests: Instead of submitting one generation at a time and waiting for results, batch similar requests together. Many platforms process batched jobs more efficiently than individual ones.
Right-size your output: Do you really need 4K resolution for a draft? Generate low-res previews first, then upscale only the approved versions. Using Domer's AI image generator for quick drafts saves enormous time.
Pre-compute references: If you're generating a series with consistent characters, invest upfront in high-quality reference images using GPT Image 2. This eliminates the need to re-establish visual anchors for every generation.
Model selection and performance
Different models have vastly different processing requirements:
- High-fidelity models take longer but produce better results
- Speed-optimized models are perfect for iterations and drafts
- Seedance 2.0 balances quality and speed for video generation
Build a tiered approach: fast models for exploration, premium models for final renders.
Measuring what matters
Track these metrics to optimize your workflow:
- Time from prompt to usable output
- First-attempt success rate
- Cost per minute of finished video
- Rework rate (how often you need to regenerate)
Improving these metrics by 20% compounds dramatically over hundreds of generations. Small optimizations yield big results at scale.
