fal image models vs Google Imagen

fal image models

Hundreds of image models, including FLUX, Nano Banana, GPT Image, Seedream, Recraft and Ideogram, on one key. Billing units vary by model, per image, per megapixel or per token.

Google Imagen

Shutdown dates were published in the Gemini API changelog and the Vertex AI release notes, with replacements named. Discontinued. Calls to imagen model names fail on both the Gemini API and Vertex AI.

fal image models

1. Fetch https://fal.ai/models/<endpoint-id>/llms.txt before calling a model to get its schema and price
2. POST to https://queue.fal.run/<endpoint-id> and poll or pass a webhook, rather than holding a call open on fal.run
3. Use an API-scoped key for agents. ADMIN keys can deploy and manage apps
4. Download outputs you need to keep. CDN retention defaults to at least 7 days, set X-Fal-Object-Lifecycle-Preference to change it
5. Validate inputs before submitting, a malformed request can still be billed

Google Imagen

1. Replace client.models.generate_images with client.models.generate_content and a gemini-3.1-flash-image model
2. Read images from the response content parts, not from generated_images
3. Don't budget from the Vertex Imagen price rows, they describe a retired product
4. If the job needs a mask-based inpaint, use another vendor's fill endpoint, since Gemini image editing is prompt-based