Metrik
The AI systems engineering platform. Measure, trace, and optimize transformer models.
$ uv tool install metrik-ai # or: pip install metrik-ai
$ metrik explore ./models/SmolLM2-135M
Every claim Metrik makes traces back to the inputs that produced it. Numbers are labelled analytic, measured, or declared, and anything that could not be determined is named with a reason rather than estimated.
What works today
| Command | What it does |
|---|---|
metrik explore <model> |
Architecture, parameters, and memory — no forward pass, no torch |
metrik viz <artifact> |
Charts in the terminal, or one self-contained HTML file |
metrik store |
Content-addressed artifacts, with full lineage |
metrik runs |
What ran, including what failed |
metrik bench --check |
What isolation this machine has — and what it will refuse to run |
metrik explore reads safetensors headers and config.json. It installs and runs on a laptop
with no ML stack at all, in about two seconds for a 270 MB model.
For an observed module tree — real module classes, weight tying by storage identity — install the extra:
$ uv tool install "metrik-ai[torch]"
$ metrik explore ./models/SmolLM2-135M --loader torch
What does not work yet
Profiling, optimization, and benchmark scoring. See ROADMAP.md. The benchmark sandbox refuses rather than running model-generated code unsandboxed, which is not revisitable — see ADR 019.
Apache-2.0.
1 maintainer
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