IonRouter

Veer Shah, Suryaa Rajinikanth, and a team of eight built IonRouter because they looked at AI inference and said "this is absurdly inefficient." They're right. IonAttention is their custom inference stack that multiplexes multiple models on a single GPU—switching between them in milliseconds and adapting to traffic in real time. On a single NVIDIA GH200 running Qwen2.5-7B, they hit 7,167 tokens per second. The "top inference provider" out there? They're getting roughly 3,000. That's 2.4x throughput on the same hardware, and it gets worse for the competition.

Here's the kicker: IonRouter runs five vision-language models simultaneously on ONE GPU. That's not a typo. They've got a case study with 2,700 video clips, concurrent users, and sub-second cold starts. Real-time robotics perception, multi-camera surveillance, game asset generation, AI video pipelines—teams are building all of this on Ion because they don't need to provision a separate GPU for every model anymore. They offer dedicated GPU streams with zero cold starts and per-second billing, so you're not burning money when nothing's happening. Drop-in compatible with the OpenAI API—change one line of code and you're off.

They're based in San Francisco and part of NVIDIA Inception. If you're running inference at scale and you're still paying for idle GPUs, IonRouter is your cheat code.