Google Pixel (Tensor), MediaTek Dimensity, and Samsung Exynos NPU support are available for enterprise customers only. Contact us for enterprise pricing and access.
The chipset support list is continuously expanding. If your target device is not listed here, Melange will still work using GPU or CPU fallback. Contact us for specific chipset inquiries.
Broadest compatibility, supports models from TensorFlow, PyTorch, and other frameworks
PyTorch Exported Program
.pt2
Recommended
Native PyTorch 2.0+ export format with full graph capture
TorchScript
.pt
Deprecated
Will be removed in a future release. Migrate to .pt2 or .onnx
TorchScript (.pt) support will be deprecated soon. We strongly recommend using PyTorch Exported Program (.pt2) or ONNX for future compatibility and better optimization.
All model inputs must be provided as NumPy arrays (.npy files) during the upload step. These sample inputs are used for:
Defining fixed input shapes for NPU compilation
Running accuracy validation during the benchmark phase
Generating optimized model binaries
NPU compilation hard-codes input shapes to maximize throughput. Even if your original model supports dynamic sizes, the accelerated Melange model will accept only the exact shape of the sample input provided during upload.
