MapAnything

• Original code: https://github.com/facebookresearch/map-anything at 3d10cf7
• Code licence: Apache-2.0 (permissive); files: LICENSE
• Weights licence: Apache-2.0
• Licence evidence: https://github.com/facebookresearch/map-anything/blob/3d10cf7/LICENSE and https://huggingface.co/facebook/map-anything-apache/blob/00f9c245bbcb60522d1ed7f9e9d88462c6e3f38a/README.md
• Training data: The apache variant is trained on the subset of the paper's 13 datasets whose licences allow commercial use (README 'Models'; the exact list is in the paper). The CC-BY-NC facebook/map-anything checkpoint is not packaged.
• Licence note: The map-anything-apache weights are Apache-2.0, but the repository does not list the datasets they were trained on (the paper names the commercially usable subset), so their training-data terms are unclear here.
• Licence note: The CC-BY-NC facebook/map-anything checkpoint is not packaged.
• Options: long_side = 518 (>= 14; also resolution)
• Kernel libraries: fastbb
• Variants: mapanything-apache
• Outputs: depth, confidence, mask, world_points, intrinsics, cam_to_world, metric_scale (in extras); kind: metric
• Input size: any H x W >= 1, resized or padded inside the model
• Tested up to (portable, fp16, RTX 5060 Ti 16 GB): mapanything-apache 3000x4000 (7.1 GiB peak allocated, 9.2 reserved)
• mapanything-apache 336x518, first call: portable + torch.compile 46 s (cold Inductor cache), TensorRT fp16 137 s (ONNX + engine).
• mapanything-apache original (fp32) 336x518: float32 (the authors' autocast off)
• mapanything-apache original 336x518: original default MapAnything.infer(use_amp=True, amp_dtype='bf16')
• mapanything-apache load / first call: original 6.12 s / 2.619 s (336x518), portable 2.89 s / 0.657 s (336x518), kernels 0.57† s / 0.541 s (336x518)
• † 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 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

Measured

640x512 crops, the 7 most co-visible views as sources; GT = depth rendered from the structured-light points. AbsRel / delta1 over GT pixels, after per-image median scaling unless the model takes the cameras (calibrated MVS: cameras, error in mm; PatchMatchNet also the depth range 425-935 mm, MVSAnywhere its own range from the camera baselines). Original = the original code named under Details, same checkpoint and protocol.

Measured on NVIDIA GeForce RTX 5060 Ti, torch 2.14.1+cu130, 2026-11-06.

Parity

CPU, float32: max |diff| <= 0.002 vs the original. GPU, float16 (the default), portable and kernels: mean |diff| <= 1 % and p99 <= 5 % of the reference's median |value| (absolute error of the output depth).