OpenAI just drew a new line in the AI inference race. The company is previewing Ultrafast mode, a new API service tier that runs GPT-5.6 Sol at up to 750 output tokens per second, 14 times faster than standard processing. The catch: it's launching in limited preview to a select group of API customers, with broader access gated by capacity. But the implications are significant enough to pay attention to now.

Speed as a product feature

For most of AI's recent history, getting faster inference meant accepting a weaker model. You could have speed, or you could have intelligence. Ultrafast is OpenAI's argument that you no longer have to choose. Until now, getting real-time speed typically meant choosing a smaller or more specialized model. Ultrafast points to progress in a new direction: more useful work per second.

To understand what 750 tokens per second actually means in practice, consider the baseline. GPT-5.6 Sol runs at up to 750 tokens a second on Cerebras hardware, roughly 5x the approximately 150 tokens a second most production models deliver today. For a single chatbot exchange, that difference might feel cosmetic. But for agentic workflows, it compounds fast. For an enterprise agent that chains 30 or 40 model calls to finish one back-office task, that 5x compounds into the difference between a workflow that finishes in seconds and one that finishes in minutes.

The predecessor model, GPT-5.5 XHigh, ran at roughly 70 to 100 tokens per second. GPT-5.6 Sol is 7 to 10 times faster than its predecessor at the high end. That is not an incremental improvement. That is a different product category.

The hardware story: why Cerebras

The speed comes from an unusual piece of silicon. While traditional GPUs stitch together dozens of discrete chips, Cerebras builds one giant processor, the Wafer-Scale Engine, that keeps all the model weights local. No memory bottlenecks, no interconnect latency. Just raw, uninterrupted compute flow.