CNAPS

CNAPS is a no-code workflow builder where you chain AI models together on a visual canvas instead of juggling a dozen separate subscriptions. You pick what you need — Nano Banana, GPT Image, and FLUX.2 for images, MiniMax-H3, Sora 2, and Ken Burns for video, SeedVR2 7B and SwinIR for upscaling, BiRefNet and SAM3.1 for background removal, ACE-Step and TTS for sound, Claude, ChatGPT, and Gemini for reasoning — wire them into one flow, and run the whole thing end to end. Each step's output becomes the next step's input, and you can swap the model at any node without rebuilding. If you'd rather not build from scratch, a one-click example mode picks the goal and chains the right models for you, no nodes or setup involved. Finished workflows are runnable and forkable: VSR Arena compares three video upscalers on the same clip, VLM Arena puts open-source models side by side, Virtual Try-On handles garment previews, and the Consensus Engine runs multiple LLMs in parallel and surfaces where they agree. Flows save as JSON, publish to the community for others to fork, and can be driven from n8n, Zapier, or Claude through MCP on any plan. The catch to understand before you commit: usage is metered by GPU time, and every plan's allowance refills on a cycle with unused time cleared rather than carried over. All models are available on every tier, including Free — plans differ in GPU allowance and processing speed, not model access. Free outputs carry a watermark; Batch Run starts at Starter; parallel GPU processing starts at Pro. A 2-week Pro trial needs no credit card. It suits marketers, product managers, and ops teams turning a finished pipeline into repeatable output without an engineering ticket. If you need per-call cost accounting, fine-grained sampling parameters, or air-gapped deployment, look elsewhere — or at Enterprise, which handles dedicated SaaS, private cloud, and on-premises.