The Hidden Costs of Generative AI Deployments

When budgeting for an AI project, developers often multiply expected usage by the API token price and stop there. This leads to massive budget overruns. The true cost of multimodal AI lies in the surrounding infrastructure.

1. Output Tokens Cost More

Never forget that output tokens (the text the AI generates) are typically 3x to 5x more expensive than input tokens. If you ask an AI to summarize a video into a 2,000-word report, the generation cost will often exceed the video processing cost.

2. Cloud Egress Fees

If your application sits in AWS US-East-1, but you are piping gigabytes of video to an OpenAI API endpoint outside of your VPC, you will pay hefty network egress fees to your cloud provider.

3. Storage and Pre-processing

Multimodal AI requires staging infrastructure. You must store images, encode videos using FFmpeg servers, and manage queues. This compute overhead is entirely separate from your LLM bill.

Start budgeting accurately by calculating your raw baseline costs. Use our Multimodal Calculator to get exact API baseline figures.