RT-MonSter++

• Original code: https://github.com/Junda24/MonSter-plusplus at 9167101af8fb
• Code licence: LicenseRef-noncommercial (noncommercial); files: LICENSE
• Weights licence: LicenseRef-noncommercial
• Licence evidence: https://github.com/Junda24/MonSter-plusplus/blob/9167101af8fbe93c706707daa7a8181089c8b1b4/LICENSE#L34
• Training data: mix_all (Zero_shot.pth): 'all the datasets we collect over 2M image pairs' (README), not listed
• Options: cuda_graphs = True (speed only)
• Kernel libraries: igev, cutlass_conv, cudnn_hacc, fastbb
• Variants: rt-monster-plusplus-mix-all
• 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): rt-monster-plusplus-mix-all 1988x2880 (9.3 GiB peak allocated, 11.1 reserved)
• rt-monster-plusplus-mix-all 994x1482, first call: portable + torch.compile 69 s (cold Inductor cache), TensorRT fp16 150 s (ONNX + engine).
• rt-monster-plusplus-mix-all load / first call: original 0.99 s / 0.662 s (375x1242), portable 0.26 s / 0.131† s, kernels 0.23† s / 0.104† 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, 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 portable: NVIDIA GeForce RTX 5060 Ti, torch 2.14.1+cu130, fastforks 468fba10, 2026-11-05; kernels: NVIDIA GeForce RTX 5060 Ti, torch 2.14.1+cu130, fastforks 939adfe8, 2026-11-06.

Parity

CPU, float32: max |diff| <= 0.002 vs the original. GPU, float16 (the default), portable and kernels: mean |diff| <= 0.02 px and p99 <= 0.25 px.