Model
Primer 1.3B
A small model that keeps learning after training.
Think of it as a model with a notebook. What it learns stays with it, and every new problem starts from everything it already knows.
Primer 1.3B
Research system- Parameters
- 1.3B
- Focus
- Post-training learning
- Status
- Experimental
- Deployment
- Private research infrastructure
Primer 1.3B is the research system proving Primer’s learning architecture. It runs on private research infrastructure and is available to strategic partners rather than as a public model release. It is a fixed research artifact: successor systems are not publicly documented.
1.3B
parameters
Why start small?
We are studying how learning works, not winning by size.
A small model makes the question clean: if it learns something after training, the learning is real, not something a giant model already knew. If the mechanism holds up, scale becomes something we add, not the whole strategy.
The difference
Today’s AI, and Primer.
| Today’s AI | Primer | |
|---|---|---|
| After training | Frozen | Keeps learning |
| Something new | Needs retraining | Learns it directly |
| Memory | Overwritten or forgotten | Keeps what it learned |
| Each new skill | Starts from scratch | Builds on the last one |
| Trust | Confident even when wrong | Keeps only what holds up |
Primer is not built to replace today’s large models. It studies the capability they lack: what happens after training.
See the results