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README.md

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+---
+license: apache-2.0
+library_name: ggml
+pipeline_tag: depth-estimation
+tags:
+  - depth-anything
+  - depth-anything-3
+  - depth-estimation
+  - monocular-depth
+  - camera-pose
+  - gguf
+  - ggml
+  - cpp
+  - localai
+base_model:
+  - depth-anything/DA3-SMALL
+  - depth-anything/DA3-BASE
+  - depth-anything/DA3-LARGE
+  - depth-anything/DA3-GIANT
+  - depth-anything/DA3MONO-LARGE
+  - depth-anything/DA3METRIC-LARGE
+  - depth-anything/DA3NESTED-GIANT-LARGE
+---
+
+# Depth Anything 3 — GGUF weights for [depth-anything.cpp](https://github.com/mudler/depth-anything.cpp)
+
+**Brought to you by the [LocalAI](https://github.com/mudler/LocalAI) team.**
+
+GGUF conversions of [ByteDance Depth Anything 3](https://github.com/bytedance-seed/depth-anything-3),
+for use with **[depth-anything.cpp](https://github.com/mudler/depth-anything.cpp)** — a from-scratch
+C++17 / [ggml](https://github.com/ggml-org/ggml) port. No Python, no PyTorch, no CUDA toolkit at
+inference: one self-contained GGUF file plus a small native library and CLI, **faster than PyTorch
+on CPU** and **bit-exact** against the original (correlation 1.0, verified component by component).
+
+Given an image, the engine recovers a dense **depth** map, per-pixel **confidence**, camera
+**extrinsics (3×4)** and **intrinsics (3×3)**, an optional **sky** mask, a back-projected **3D point
+cloud**, and exports to **glb / COLMAP / PLY**.
+
+## Files in this repo
+
+Each GGUF is fully self-contained — every dimension, hyperparameter and preprocessing constant is
+baked into the file; the loader reads them, nothing is hardcoded.
+
+| File | Source checkpoint | Backbone | Depth type | Output |
+|------|-------------------|----------|-----------|--------|
+| `depth-anything-small-f32.gguf` | `DA3-SMALL` | ViT-S | relative | depth + conf + pose |
+| `depth-anything-base-f32.gguf` | `DA3-BASE` | ViT-B | relative | depth + conf + pose |
+| `depth-anything-base-f16.gguf` | `DA3-BASE` | ViT-B | relative | depth + conf + pose |
+| `depth-anything-base-q8_0.gguf` | `DA3-BASE` | ViT-B | relative | depth + conf + pose (near-lossless) |
+| `depth-anything-base-q4_k.gguf` | `DA3-BASE` | ViT-B | relative | depth + conf + pose (**99 MB**) |
+| `depth-anything-large-f32.gguf` | `DA3-LARGE` | ViT-L | relative | depth + conf + pose |
+| `depth-anything-giant-f32.gguf` | `DA3-GIANT` | ViT-g | relative | depth + conf + pose + 3D Gaussians |
+| `depth-anything-mono-large-f32.gguf` | `DA3MONO-LARGE` | ViT-L | relative (monocular) | depth + sky |
+| `depth-anything-metric-large-f32.gguf` | `DA3METRIC-LARGE` | ViT-L | **metric** | metric depth + sky |
+| `depth-anything-nested-anyview.gguf` | `DA3NESTED-GIANT-LARGE` (anyview branch) | ViT-g | relative | depth + conf + pose |
+| `depth-anything-nested-metric.gguf` | `DA3NESTED-GIANT-LARGE` (metric branch) | ViT-L | **metric** | depth + sky |
+
+> The nested model is a **two-file pair**: the engine loads the anyview (ViT-g) branch and the
+> metric (ViT-L) branch together and aligns them to produce metric-scale depth + pose. Download
+> both `depth-anything-nested-anyview.gguf` and `depth-anything-nested-metric.gguf`.
+
+### Which one should I use?
+
+- **Just trying it out / CPU:** `depth-anything-base-q4_k.gguf` (99 MB, near-lossless).
+- **Best quality/speed default:** `depth-anything-base-q8_0.gguf`.
+- **Smallest / fastest:** `depth-anything-small-f32.gguf`.
+- **Highest quality + 3D reconstruction (point cloud / Gaussians):** `depth-anything-giant-f32.gguf`.
+- **Single-image depth with sky mask:** `depth-anything-mono-large-f32.gguf`.
+- **Metric-scale depth (meters), single model:** `depth-anything-metric-large-f32.gguf`.
+- **Best metric-scale depth + pose:** the nested pair (`depth-anything-nested-anyview.gguf` +
+  `depth-anything-nested-metric.gguf`).
+
+## Usage
+
+### depth-anything.cpp (CLI)
+
+```bash
+git clone https://github.com/mudler/depth-anything.cpp && cd depth-anything.cpp
+cmake -B build -DCMAKE_BUILD_TYPE=Release && cmake --build build -j
+
+# download a weight from this repo
+hf download mudler/depth-anything.cpp-gguf depth-anything-base-q4_k.gguf --local-dir models
+
+./build/da3 depth models/depth-anything-base-q4_k.gguf image.jpg --out depth.png
+./build/da3 depth models/depth-anything-base-q4_k.gguf image.jpg --pose poses.json
+./build/da3 reconstruct models/depth-anything-giant-f32.gguf image.jpg --ply cloud.ply
+
+# metric-scale depth from the single metric model
+./build/da3 depth models/depth-anything-metric-large-f32.gguf image.jpg --out depth.png
+
+# metric-scale depth + pose from the nested pair (anyview + metric branches)
+./build/da3 depth models/depth-anything-nested-anyview.gguf image.jpg \
+    --metric-model models/depth-anything-nested-metric.gguf --pfm depth.pfm
+```
+
+See the [README](https://github.com/mudler/depth-anything.cpp) for multi-view, glb/COLMAP export,
+quantization and the flat C API.
+
+### LocalAI
+
+```bash
+local-ai run depth-anything-3-base
+```
+
+## Performance
+
+Faster than PyTorch on CPU at half the memory, bit-exact. AMD Ryzen 9 9950X3D, `threads=16`,
+504×336, sustained:
+
+| engine | quant | model MB | load ms | infer ms | peak RAM MB | vs PyTorch |
+|--------|-------|---------:|--------:|---------:|------------:|-----------:|
+| PyTorch | f32 | 516 | 749 | 416.9 | 1328 | 1.00× |
+| **C++/ggml** | f32 | 393 | **112** | **346.4** | **614** | **1.20×** |
+| **C++/ggml** | q8_0 | 142 | **40** | **319.4** | **363** | **1.31×** |
+| **C++/ggml** | q4_k | **99** | **25** | 395.2 | **320** | 1.05× |
+
+Full methodology in [`benchmarks/BENCHMARK.md`](https://github.com/mudler/depth-anything.cpp/blob/master/benchmarks/BENCHMARK.md).
+
+## License
+
+The GGUF weights are derived from the official Depth Anything 3 checkpoints and inherit their
+**Apache-2.0** license. The depth-anything.cpp code is MIT.
+
+## Citation
+
+```bibtex
+@article{depthanything3,
+  title   = {Depth Anything 3: Recovering the Visual Space from Any Views},
+  author  = {ByteDance Seed},
+  year    = {2025}
+}
+```