Unlimited requests, competitive pricing
DevOps, monitoring & dedicated instances
Run our AI inference platform on your infrastructure
It's never been easier to start prototyping on open source and it's never been more reliable to run AI inference in prod.
We build our own GPU kernels for optimizined and reliable inference. Because of this, we have one of the highest throughput of all inference providers on OpenRouter and 99.95% uptime. Don't take our word for it, check out live stats at OpenRouter.
We've gone through the process of building a scalable, reliable and fast AI Inference platform. Speak with us to deploy this on your hardware.
Change absolutely nothing other than the URL, API Key and Model Name and migrate your entire stack from GPT / Claude to nCompass. Check out our docs.
Book a call to speak to an expert on how you can migrate prompts from closed to open source models without losing accuracy.
Lightning-fast public API for AI inference with unlimited requests and competitive pricing
Starting at
$0.15/1M tokens
Managed AI inference platform with DevOps, monitoring, and dedicated model instances
Custom Pricing
Contact for quote
Run our AI Inference Platform on your private and secure infrastructure
Custom Pricing
Contact for quote
nCompass makes deploying models effortless. All we had to do is specify the models we want to use, and they built us an endpoint that's 15% faster and reduced our inference costs by 70%.
After benchmarking every major API provider available on OpenRouter—including exhaustive load‑tests—nCompass distinguished itself as the only platform that met 100% of our performance criteria: it sustained our peak burst profile (≈3k req/min) with zero enforced rate limits, accepted our 128k‑token context windows without truncation. Competing providers throttled requests, capped contexts, or failed under load; ncompass handled traffic effortlessly with responsive support. For scale and developer experience, ncompass.tech was the decisive winner.
nCompass made it incredibly easy to see how newer open source models perform in our real-world workflows without spinning up our own infra. It took less than 5 minutes to migrate from GPT-4. The drop-in integration was seamless, and we saw immediate speedups with zero migration effort. It's a no-brainer for anyone looking to scale LLM inference quickly.