Test-Time Scaling Goes Further Than Expected
Author: @DmitryRybin1 | Date: 2026-05-03
Expression of surprise at how far test-time scaling (inference-time compute) has been pushed. The gains from spending more compute at inference continue to scale beyond what was previously assumed.
Key Claims
- Test-time compute scaling yields larger gains than commonly appreciated
- The ceiling for inference-time scaling hasn’t been reached
- More thinking time = better outputs, and this relationship extends further than expected
- Challenges the assumption that model quality is fixed at deployment
Takeaways
- Test-time compute is a legitimate scaling axis alongside parameters and training data
- Models like o1/o3 are just the beginning of inference-time scaling
- Implication: smaller models + more inference compute can match larger models