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You can now call models running on your own hardware through a hosted AI gateway. Privately, with one command: `ngrok http 8000 --url https:⁠//vllm.internal` Plus all the public models you know and love. ↓ ngrok.ai

ngrok.aiRoute, Secure & Manage Any LLM with ngrok AI GatewayRoute, secure, and manage traffic to any LLM—cloud or local—with one unified platform. Monitor usage, optimize costs, and keep your AI products online.

ngrok

@ngrok.com

One baseURL change and an access key gets you: → routing to every model, even dedicated ones on AWS, Azure, etc → automatic failover + retries when a model slows or fails → scoped keys per app → token, latency, and cost visibility by app, dev, and model

1/7/26, 7:21 pm0 reposts0 likes

ngrok

@ngrok.com

1 July

When you route to a local model, it's full private connectivity: no publicly addressable URLs, no public IPs to allowlist, or ports to open, wherever you've got those GPUs humming. Works with Ollama, vLLM, LM Studio, and the neoclouds, too.

ngrok

@ngrok.com

1 July

One flat fee: $0.05 per million tokens ,with your inference billed on top. Buy credits as you go. Full writeup → ngrok.com/blog/new-ngr... Docs → ngrok.com/docs/ai-gate...

ngrok.comThe new ngrok.ai | ngrok blogThe ngrok AI Gateway is now app.ngrok.ai. One key, one URL to access any model, including the ones you run yourself, with access controls and per-call cost visibility.