LiteAnyStereo V2

• Original code: https://github.com/TomTomTommi/LiteAnyStereo at 8c97bd4c4da3
• Code licence: MIT (permissive); files: LICENSE
• Weights licence: MIT
• Licence evidence: https://huggingface.co/tomtomtommi/LiteAnyStereoV2/blob/17788d91618646fa781a14462e2926a034b9f49d/README.md#L2
• Training data: Zero-shot model trained on a mixture of synthetic stereo datasets that includes FSD and Dynamic Replica (non-commercial data terms); the repository does not list the data or its terms
• Licence note: Trained on a mixture that includes NVIDIA's FSD dataset and Dynamic Replica, whose terms for commercial use of trained models are unclear (the repository lists no data terms); the status does not depend on the training data.
• Options: cuda_graphs = True (speed only)
• Kernel libraries: igev, cutlass_conv, cudnn_hacc, stereo_ops
• Variants: las2-s, las2-m, las2-l, las2-h
• Outputs: disparity
• Input size: any H x W >= 32, padded to a multiple of 32
• Tested up to (portable, fp16, RTX 5060 Ti 16 GB): las2-s 3000x4000 (7.0 GiB peak allocated, 7.4 reserved); las2-m 3000x4000 (7.0 GiB peak allocated, 7.4 reserved); las2-l 3000x4000 (7.0 GiB peak allocated, 7.4 reserved); las2-h 3000x4000 (8.5 GiB peak allocated, 11.7 reserved)
• las2-s 994x1482, first call: portable + torch.compile 22 s (cold Inductor cache), TensorRT fp16 87 s (ONNX + engine).
• las2-s original 994x1482: torch.autocast(fp16) around the forward
• las2-m original 994x1482: torch.autocast(fp16) around the forward
• las2-l original 994x1482: torch.autocast(fp16) around the forward
• las2-h original 994x1482: torch.autocast(fp16) around the forward
• las2-s load / first call: original 0.11 s / 0.019 s (375x1242), portable 0.09 s / 0.047† s, kernels 0.07† s / 0.015† s
• las2-m load / first call: original 0.17 s / 0.023 s (375x1242), portable 0.12 s / 0.054† s, kernels 0.1† s / 0.02† s
• las2-l load / first call: original 0.39 s / 0.044 s (375x1242), portable 0.23 s / 0.081† s, kernels 0.18† s / 0.031† s
• las2-h load / first call: original 0.26 s / 1.212 s (375x1242), portable 0.18 s / 0.136† s, kernels 0.13† s / 0.062† s
• † measured in the speed sweep after the portable load (or an earlier size) in the same process: file cache and kernels are warm, so the time is lower than a fresh start.
• Protocol, las2-s, las2-m, las2-l: median of 5 after 3 warm-up, uint8 CUDA input (synthetic for bench_inputs sizes), card defaults; gc before each load; peak = max over the first call and the timed calls
• Protocol, las2-h: median of 9 after 3 warm-up, uint8 CUDA input (synthetic for bench_inputs sizes), card defaults; gc before each load; peak = max over the first call and the timed calls

Measured

Original = the original code named under Details, same checkpoint and protocol.

Measured on NVIDIA GeForce RTX 5060 Ti, torch 2.14.1+cu130, fastforks 468fba10, 2026-11-05.

Parity

CPU, float32: max |diff| <= 0.002 vs the original. GPU, float16 (the default), portable and kernels: mean |diff| <= 0.05 px and p99 <= 0.5 px.

Limitations

• The original code's LAS1 (LiteAnyStereo.pth, another architecture) is not included.
• Portable LAS2-H is faster than the original code but allocates more memory.