---
title: "Blackwell"
description: "1 posts about Blackwell, summarised, each linking to the original."
---

# Blackwell
> 1 posts about Blackwell, summarised, each linking to the original.

## Articles

### [How to serve trillions of tokens for trillion-parameter coding agents](https://yomu.fyi/post/how-to-serve-trillions-of-tokens-for-trillion-parameter-coding-agents.md)
- Company: [Modal](https://yomu.fyi/company/modal.md)
- Published: Sep 23, 2026
- Type: Explainer

Serving inference for coding agents requires trillion-parameter sequence models like Moonshot AI’s Kimi K2.6 to process trillions of input and output tokens at extremely high relative and absolute performance. To be economically viable, these services must achieve large fractions of hardware peak performance, using contemporary matrix math accelerators like Tensor Cores at petaFLOP per second scale. Modal optimized by batching multiple sequences together, caching KV state, and patching SGLang with NVFP4 micro-scaling on Blackwell GPUs like the B200. Per-replica performance improved 2.8x per user and 5.6x across users, transforming ruinously expensive into a price-competitive service. One deployment processed hundreds of billions of tokens daily and trillions total, showing that careful engineering and benchmarking are key to scaling inference.