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# Export Compatibility

In order to accelerate a quantized model, Brevitas requires to export the model to an inference toolchain. Brevitas can currently export to:

- FINN - for dataflow acceleration on Xilinx FPGAs.

- PyXIR (experimental) - for DPU acceleration on Xilinx FPGAs.

- Standard ONNX (experimental) - for acceleration with e.g. onnxruntime, or any other ONNX-compliant toolchain.

- Pytorch’s quantized.functional operators (experimental) - for acceleration through Pytorch itself, or any additional downstream toolchains supported by Pytorch (e.g. TVM).

Because Brevitas implements a super-set of layers and datatypes supported by various downstream toolchains and hardware platforms, the result is that each export flow supports only a certain subset of features, in ways that are not necessarely obvious. More examples and documentation will be released to illustrate the various restrictions imposed by each target platform. As a general note though, currently FINN is the only toolchain that supports acceleration of low bit-width datatypes.