Q Labs company blog
NanoGPT Slowrun: 10x Data Efficiency with Infinite Compute
We've achieved 10x data efficiency with NanoGPT Slowrun within a few weeks. An ensemble of 1.8B parameter models (18B total params) trained on 100M tokens matches what would normally require 1B tokens with a standard LM baseline. Data efficiency matters because compute grows much faster than data . Since our current…
- Points
- 168
- HN comments
- 46
- Submissions
- 1
- Cited by
- 0 commenters
AI & Machine LearningDatabases & Data2026
On Hacker News
| Submitted | Title on HN | Points | Comments |
|---|---|---|---|
| Mar 19, 2026 | NanoGPT Slowrun: 10x Data Efficiency with Infinite Compute by sdpmas | 168 | 46 |
