Mercury 2.5: When an LLM Stops Writing One Token at a Time

Thu, 10 Sep 2026 09:00:00 +0530

Every major model you’ve used, GPT, Claude, Gemini, Llama, writes one token at a time, left to right, each one conditioned on everything before it. That’s why streaming responses trickle out word by word. Inception Labs just shipped Mercury 2.5, a diffusion language model that throws that constraint out, generating a whole block of text in parallel and iteratively refining it, and it’s now running at over 1,100 tokens per second on widely available Nvidia GPUs. That’s not a marginal speedup. It’s a different generation mechanism reaching a point where the intelligence gap with autoregressive models has closed enough to matter for real workloads.

Inference-Performance on Kuldeep Pisda

Mercury 2.5: When an LLM Stops Writing One Token at a Time