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DA3 Monocular Large

depth-anything/DA3MONO-LARGE

published Nov 2025 · updated Nov 2025

DA3 Monocular Large is a monocular relative depth estimation model that directly predicts depth with superior geometric accuracy.

status
coming soon
API providers
0
downloads / mo
47.1K
license
apache-2.0

specs

TaskMonocular Depth Estimation
ArchitecturePlain Transformer (vanilla DINO encoder) with unified depth-ray representation
Parameters0.35B
LicenseApache 2.0

about this model

DA3MONO-LARGE is a monocular depth estimation model that directly predicts relative depth from a single image, producing geometrically accurate depth maps without requiring disparity-based conversions.

Architecture and Design

Built on a single plain transformer (vanilla DINO encoder), the model uses a unified depth-ray representation that eliminates the need for complex multi-task learning. It has 0.35 billion parameters and is trained exclusively on public academic datasets under the Apache 2.0 license.

Capabilities

  • Relative depth estimation with sky segmentation

Performance

Depth Anything 3 significantly outperforms Depth Anything 2 for monocular depth estimation and VGGT for multi-view depth estimation and pose estimation. On standard benchmarks, it surpasses VGGT by 35.7% in camera pose accuracy and 23.6% in geometric accuracy (project page). The paper (arXiv:2511.10647) has been accepted at ICLR 2026 as an Oral presentation.

Limitations

The model is trained on academic datasets, so performance may degrade on domain-specific images or under poor lighting, low image quality, or complex scene conditions.

best for

FAQ

What is the primary use case for DA3 Monocular Large?

It is designed for high-quality relative monocular depth estimation from a single image, directly predicting depth with superior geometric accuracy compared to disparity-based models.

What input formats does the model accept?

The model accepts image paths, PIL images, or numpy arrays. Outputs include depth maps, confidence maps, and optionally 3D exports in formats like GLB, NPZ, and PLY.

How can I use this model via the gigarouter API?

Use the OpenAI-compatible endpoint with your gigarouter API key. See gigarouter documentation for details on request format and endpoint.

What is the license and can it be used commercially?

The model is released under Apache 2.0 license, which permits commercial use.

How does it compare to Depth Anything V2?

DA3 Monocular Large directly predicts depth (not disparity) and significantly outperforms Depth Anything V2 in monocular depth estimation accuracy.

not yet live

We're benchmarking and onboarding DA3 Monocular Large as a hosted, OpenAI-compatible API. Sign in for free credit and be ready when it lands, or tell us you want it and we'll prioritize it.

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