Image Prompt Packaging Cuts Multimodal Inference Costs Up to 91%

A new method called Image Prompt Packaging (IPPg) embeds structured text directly into images, reducing token-based inference costs by 35.8–91% across GPT-4.1, GPT-4o, and Claude 3.5 Sonnet. Performance outcomes are highly model-dependent, with GPT-4.1 showing simultaneous accuracy and cost gains on some tasks. Image Prompt Packaging Cuts Multimodal Inference Costs Up to 91% Deploying large multimodal models at scale is bottlenecked by token-based pricing, where every text token—including those in system prompts, instructions, and context—adds to the bill. A new research paper, "Token-Efficient Multimodal Reasoning via Image Prompt Packaging," introduces a straightforward but systematic approach to this problem: take the text you'd normally send as tokens, render it into an image, and send that image instead. The method, called Image Prompt Packaging (IPPg), treats visual encoding as a first-class variable in system design. By benchmarking across five datasets, three frontier models (G