We built an all-synthetic simulation of a hospital that can be shared publicly without any issues. Our data quality is so high, physicians cannot tell the difference between real/synthetic patients. The data is fully verified -- perfect for RL.

Introducing Synthetic Hospital: an open, fully synthetic longitudinal EHR benchmark with verifiable ground truth!

1,268 patients, 5,602 encounters, zero PHI. Physicians could not reliably distinguish its charts from real ones.

📄 arxiv.org/abs/2609.30027
💻 github.com/sparkcpark/syn…
✍️ sparkcpark.github.io/posts/finding-…

Our 2nd release in our open-source week.

CliffCompaction lets you run sessions for millions of tokens and save 50% on token costs. It integrates easily with Claude Code and Codex. We have been using it for months, and it has better vibes than Codex/Claude Code compaction.

CliffCompaction, our autocompaction tool for coding agents, is out!

Sessions run for millions of tokens, agents stay on track, and costs drop by up to 50%.

Paper: arxiv.org/abs/2609.26779
Code: github.com/nguyenvuthient…
PyPI: pypi.org/project/cliffc…
Blog: nguyenvuthientrang.github.io/cliffcompactio…

Releasing our runtime dynamic compression framework that achieves 1.5-2.0 bit compression at high quality. This is integrated into the bitsandbytes2 library, which starts as a private beta today.

Paper: timdettmers.com/papers/runtime…
Private beta signup: forms.gle/Pwtp8CVRULdoEn…

Starting tomorrow, our lab will hold an open-source week: 2 software frameworks, 4 papers, all building a coherent ecosystem.

The theme: Frontier AI on Hardware You Own

Blog post: timdettmers.com/2026/09/21/dla…

SoTA results in:
Autocompaction
Autonomous Research
Model compression
Test-time scaling
Deep Research
And a healthcare RL environment giving you a new level of complexity to train healthcare agents.

The ecosystem that we will release is built to be as usable as possible. Agent sessions that run overnight and go on for tens of millions of tokens is made easy. Model compression of a model is automatic: you just get a good model that runs fast locally -- no expertise required. An autonomous research that works out of the box.

Our ecosystem enables a new level of work that can be done locally.

AI now helps doctors read X-rays, CTs, and MRIs. But once it's deployed in a hospital, almost no one can tell if it's still accurate.

Lattice Health watches deployed imaging AI and flags it the moment it starts to slip.

Congrats on the launch, @sparkcpark!
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