smaller. faster. open.
Prune, quantize, and distill neural networks. Ship models that are smaller and faster, on any hardware.
from fasterai import optimize
result = optimize(model, sample, target='speed')
result.model # → compressed, ready to use
result.compression # → {'size': 8.1, 'latency': 3.4}
result.export('model.onnx') faster
smaller
less CO₂
Compared to the original uncompressed model. Best-case results from combined pruning, quantization, and distillation.
Choose your path
Two ways to optimize.
Use our open-source tools yourself, or let us handle it for you.
DIY
Open-source, Apache 2.0 licensed
Pruning, quantization, distillation, benchmarking
Full documentation and tutorials
Community support via Discord
Browse Libraries
Use our tools
Done for you
We audit your model and recommend a compression strategy
Apply our proprietary optimization pipeline
Deliver a production-ready compressed model
Typical results: 3–10× speedup, minimal accuracy loss
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