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Today, we’re introducing two pieces that fit together to solve that problem:
We now explicitly track Distillable Models available on OpenRouter. These are models whose licenses allow generating synthetic training data.
License metadata is collected directly from model labs and providers, so developers don’t have to interpret terms themselves.
Now you can:
NVIDIA recently launched NeMo Data Designer, an open-source framework for programmatically generating large, high-quality datasets tailored to specific domains. Instead of one-off prompt scripts, it lets you define data generators as code.
It supports:
Using OpenRouter and NeMo Data Designer together enables teams to generate large volumes of synthetic data with clear, enforceable license guarantees, distill large reasoning models into smaller task-optimized variants, and significantly reduce inference costs without sacrificing accuracy. This approach supports repeatable, production-ready specialization workflows built entirely on open tooling.
NVIDIA has also launched a few base models in the Nemotron series, including Nemotron 3 Nano, that are extremely well suited for generating synthetic data.
If you want to see how distillable endpoints and NeMo Data Designer work together in practice, the notebook is the best place to start.
The notebook walks you through:
You can also check out the OpenRouter distillation guide and more docs about NeMo Data Designer here.
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