MaxAPI vs fal.ai
fal.ai and MaxAPI both target developers who want hosted image and video generation. fal.ai centers on low-latency inference behind its own fal-client SDK and queue/streaming primitives. MaxAPI centers on OpenAI-compatible endpoints with route-based price tiers so the same model can be billed multiple ways.
API surface
fal.ai exposes its own queue and stream API and provides a fal-client library per language.
MaxAPI exposes the OpenAI image/video endpoints (/v1/images/generations, /v1/images/edits, /v1/videos/generations). Existing OpenAI SDK code targets it by changing the base URL and key.
MaxAPI exposes image and video generation models through the OpenAI-compatible endpoints existing OpenAI SDK code already targets. Each public model also offers multiple route modes (official / official-cheap / mix) so the same request can be billed at different price tiers, and image generation works either through OpenAI's /v1/images/* family or, for Gemini models, through Google's native /v1beta/models/{model}:generateContent path with the same MaxAPI bearer key.
Model coverage on MaxAPI today
- Image: GPT Image 2, Gemini 2.5 Flash Image, Nanobanana Pro, Gemini 3.1 Flash Image Preview, Gemini 3 Pro Image Preview Beta, Gemini 3.1 Flash Image Preview Beta, GPT Image 2 Beta
- Video: Seedance 2.0 Fast Beta, Seedance 2.0 Beta, Seedance 2.0 Fast Beta Face, Seedance 2.0 Beta Face, Seedance 2.0 Fast, Seedance 2.0
- All MaxAPI image models accept OpenAI-style /v1/images/* requests.
- Gemini image models also accept Google's /v1beta/models/{model}:generateContent.
Pricing model
MaxAPI bills in credits where 1 credit = 1 USD. Failed requests are not charged. Each public model exposes route_mode tiers (official, official-cheap, mix); pass route_mode in the request body to pick a tier.
fal.ai's billing varies per model and per execution; check fal.ai's own pricing pages for current rates.
Migration sketch
If you're calling fal.run() or fal.subscribe(), swap to the OpenAI SDK with base_url="https://api.maxapi.dev". Image generation becomes openai.images.generate(...); video generation becomes a POST to /v1/videos/generations + polling /v1/videos/generations/{task_id}. Async polling on the Gemini-native path uses GET /v1beta/operations/{task_id}.
When MaxAPI is the better fit
- Your stack already speaks the OpenAI image API.
- You want a single API surface for GPT Image 2 and Gemini image models with explicit cost tiers.
- You want Seedance text-to-video and image-to-video behind the same auth as the image endpoints.
When fal.ai is the better fit
- You're targeting their specific catalogue or streaming primitives.
- You want their queue/subscription primitives without rebuilding a polling loop.
Try MaxAPI by creating a key on the homepage, or read the API documentation linked from any model page.