Teams use IonRouter as a drop‑in OpenAI-compatible API to hit the best open models for LLMs, vision, video, and TTS at HALF market rate. You can run agents and multi‑modal apps, and deploy your finetunes on our fleet while we handle optimization and scaling in the background. Under the hood, IonRouter runs a custom inference engine (IonAttention) built for NVIDIA Grace Hopper, cutting price and latency for your workloads.
Hey, congrats to your launch. I am wondering what are the main differences of IonRouter as opose to OpenRouter? Still learning about the model infrastructure, renting, deployment etc, so I hope this is not a silly question to ask!
OpenAI-compatible routing plus lower latency/cost is super compelling for multi‑modal apps. Shared with our dev team.
Hey Suryaa, congrats on the launch! Curious what sparked building your own attention engine. Was there a specific limitation you kept hitting with existing inference setups that made you think okay, we need to build this from scratch ourselves?
How does IonAttention's custom inference engine achieve half the market rate without compromising model quality or response accuracy?
Wow this would actually be so useful to us. What do you actually use to make it so much cheaper?
This looks really cool! For someone that hasn't really worked in this space, can you "explain like I'm 5" and "explain like I'm 16"?
Hey y'all! @veercumulus and I are super excited to launch this product showcasing our proprietary IonAttention Engine: https://cumulus.blog/ionattention
Now serving Kimi, Minimax, GLM, Qwen 3.5, Wan, and more! Also serving your finetunes :)