Image Generation Models: Choosing One, Fixing Errors

The image generation tutorial walks through the request itself. You send a model and a prompt to POST /api/v1/images, decode data[0].b64_json, and write the bytes to disk. This article covers the two decisions that tutorial leaves to you. Which model goes in the model field, and what to do when the API returns an error instead of an image. The model catalog behind the endpoint covers the major image labs, and the slugs change with every release. The catalog changes are why the model choice needs a method rather than a bookmark, and why a few error messages come up again and again. Pick a model by the job first (text-to-image, editing a reference image, vector output, readable text), then by parameter support, then by price. GET /api/v1/images/models lists every model the Image API serves with the union of its providers’ supported_parameters, and each entry links to a per-provider breakdown. For data, our comparison ran one prompt through 20 models and recorded the bill for each, and the image benchmarks score 39 models on 15 prompts. No image model carries the :free suffix, so every generation draws on your credit balance. Low-cost models start around a cent per image. “No…