Modellix

Where Modellix earns its keep is the boring part of multi-model work: one key, one parameter schema, one invoice. If your backlog includes a stylized batch, a product hero shot, a 10-second video and a voiceover, you can ship all four through a single integration instead of four SDKs with four auth models. The pricing page is unusually candid — 172 models listed with starting rates like GPT Image 2 from $0.006/img and Seedance 2.0 T2V from $0.07/sec — and per-second video billing matters because it lets you price a clip length before you commit. The routing logic is where the catalog gets useful. Nano Banana 2.1 runs on Gemini 3.6 Flash at 1K, 2K and 4K with optional web-search grounding; Seedream 5.0 Lite trades some aesthetic ceiling for real-time info and reasoning; GPT Image 2.5 Flare handles transparent backgrounds that the main GPT Image 2 endpoint refuses. If you have ever patched a production pipeline at 11pm because a model silently dropped a parameter, that documentation is the feature you're paying for. In practice, budget for the learning curve. This is an API and CLI product — there is no drag-and-drop editor, and no free sandbox tier surfaced on the pages we reviewed. New teams should expect to write code before they generate anything meaningful. Compare against the obvious alternatives. Fal and Replicate also aggregate models, but Modellix leans harder on published per-unit rates and per-call cost logs, which matters if procurement asks what a campaign cost. Against going direct: if you run Veo 3.1 exclusively, Google's own pricing is the benchmark to beat. The audit trail is the second real reason to choose it. Every call captures inputs, outputs and cost, so a disputed invoice becomes a query rather than an archaeology project. For agencies billing