Depth Aything
Capital-efficient model reach
PUBLIC TRACTION
Usage, audience and developer pull
WHY IT IS ON THE RADAR
Capital-efficient model reach
- High reach per model
MODEL FOOTPRINT
What it publishes
- Top tasks
- depth-estimation (36), video-to-3d (1), image-to-3d (1)
- Model sizes
- Unknown (26); <0.5B (18); 0.5-3B (4)
- Base families
- Not declared
- Libraries
- depth-anything-v2, depth-anything-3, transformers, pytorch
DEVELOPER ACTIVITY
How it ships
This record is excluded from serious GitHub comparison until the organization match is verified.
ACTIVITY TIMELINE
Latest observed moves
- HF SpaceSpace published or updated ↗
- HF modelModel published or updated ↗
- HF datasetDataset published or updated ↗
THE NEOLAB STACK
Publicly evidenced tooling
- Training
- Transformers
- Compute
- Not disclosed
- Hardware
- Not disclosed
- Tracking
- Not disclosed
- Bottlenecks
- Not disclosed
“Not disclosed” means no evidence was found in the sampled public metadata or top model card—not that the lab does not use the tool.
COMPARABLE LABS
Nearest modality peers
Large Model Systems Organization
Ultralytics
Open Food Facts
Neta.art
Jasper AIINVESTOR DILIGENCE
Confirm the team and compute inputs behind reach per model; benchmark quality versus the base family.
- HF member count is only a public-profile proxy
- GitHub identity unresolved or absent
- Activity older than 90 days
MISSING FROM THIS RECORD
Completeness: 5 of 14 tracked field groups. Unknowns are explicit so an analyst can close them.
DATA PROVENANCE
Every claim should be auditable.
Platform counters are a point-in-time public snapshot. Editorial facts are only promoted after source review.
NEOLAB TRACKER PRO
Know when the thesis changes.
Weekly deltas, funding and team alerts, portfolio watchlists, CSV exports and an analyst-ready API turn a static profile into a sourcing system.