license: apache-2.0
pipeline_tag: depth-estimation
library_name: executorch
base_model: depth-anything/DA3-SMALL
depth-anything-v3
This repository hosts Depth Anything 3 Small (single-image depth estimation)
exported for the
React Native ExecuTorch
library as ExecuTorch .pte programs, ready to run on device.
Upstream model: depth-anything/DA3-SMALL,
revision e08cab65ca0ec38e7826075418411ab90cab4da3.
Variants
| Path | Backend | Precision |
|---|---|---|
small/coreml/depth_anything_v3_small_coreml_fp16.pte |
coreml | fp16 |
small/vulkan/depth_anything_v3_small_vulkan_fp16.pte |
vulkan | fp16 |
small/xnnpack/depth_anything_v3_small_xnnpack_fp32.pte |
xnnpack | fp32 |
small/xnnpack/depth_anything_v3_small_xnnpack_int8.pte |
xnnpack | int8 |
XNNPACK int8
The INT8 export uses dynamic INT8 activations and per-channel INT8 weights for linear layers; convolutions remain floating point. Public inputs and outputs remain float32.
Numerical agreement with the float reference on three photos (cats and the two official DA3 SOH examples) and four upstream example illustrations:
| Image | Range-normalized RMSE | Correlation |
|---|---|---|
| depth_cats | 0.51% | 0.999855 |
| SOH/000 | 0.75% | 0.999915 |
| SOH/010 | 0.66% | 0.999924 |
| demo17 | 1.50% | 0.998355 |
| demo18 | 0.31% | 0.999875 |
| demo19 | 0.81% | 0.999865 |
| demo20 | 1.21% | 0.999060 |
Range-normalized RMSE is RMSE divided by the reference depth range. The worst value was 1.50%, with a minimum correlation of 0.998355. These are numerical export checks, not depth-accuracy benchmarks.
Repository structure
config.json 39 B
small/coreml/config.json 879 B
small/coreml/depth_anything_v3_small_coreml_fp16.pte 70.9 MB
small/vulkan/config.json 879 B
small/vulkan/depth_anything_v3_small_vulkan_fp16.pte 56.4 MB
small/xnnpack/config.json 1.5 kB
small/xnnpack/depth_anything_v3_small_xnnpack_fp32.pte 106.5 MB
small/xnnpack/depth_anything_v3_small_xnnpack_int8.pte 40.6 MB
Compatibility
These files are published for the ExecuTorch v1.4.1 runtime. ExecuTorch gives no forward compatibility guarantee, so an older runtime may fail to load them.
For React Native ExecuTorch model loading, see the documentation. To load these files in your own runtime, read the compatibility note first.