Depth Anything 3 Small (504×504) — Core ML

ByteDance-Seed, ICLR 2026 oral

Relative monocular depth from a single image. DA3 Main Series, Small (0.08B params, DINOv2 ViT-S/14 + DualDPT head). First public Core ML conversion of Depth Anything 3.

Depth Anything 3 Small (504×504) demo

Core ML conversion of ByteDance-Seed/Depth-Anything-3 for on-device inference on iPhone, iPad and Mac. Converted with coremltools; the packages are stateless, so all sequencing and buffering lives in your Swift code.


Task	depth estimation
Upstream	ByteDance-Seed/Depth-Anything-3
Packages	1
Download size	44 MB
Minimum iOS	17.0
Peak RAM	~300 MB

Files

File	Size	Compute units	SHA-256
`DepthAnythingV3_small_504.mlpackage.zip`	44 MB	`all`	`c10f8afa01fdc1d2…`
Total	44 MB

compute_units is not a suggestion -- it is the configuration the conversion was verified against. Moving a package to a different compute unit can silently change the numerics (FP16 attention overflow) or crash on the GPU.

Download

hf download mlboydaisuke/coreml-zoo --include "depth_anything_v3/*" --local-dir ./depth_anything_v3_small_504
unzip './depth_anything_v3_small_504/depth_anything_v3/*.zip' -d ./depth_anything_v3_small_504

Use in Swift

import CoreML

let config = MLModelConfiguration()
config.computeUnits = .all   // as converted — see the table above

// Unzip the .mlpackage, drop it into your Xcode target and Xcode compiles it
// at build time:
let model = try DepthAnythingV3_small_504(configuration: config)

// ...or compile a downloaded .mlpackage at runtime:
let compiled = try await MLModel.compileModel(at: mlpackageURL)
let model = try MLModel(contentsOf: compiled, configuration: config)