Model reference · open weights
MegaLoc is an open-weight embedding model from gberton, listed in the AxForge catalogue. AxForge can bring it up on EU-owned hardware for you on request — with the licence handled where one is required.
About
MegaLoc MegaLoc is an image retrieval model for visual place recognition (VPR) that achieves state-of-the-art on most VPR datasets, including indoor and outdoor environments. Paper: MegaLoc: One Retrieval to Place Them All (CVPR 2025 Workshop) GitHub: gmberton/MegaLoc Usage For benchmarking on VPR datasets, see VPR-methods-evaluation. Qualitative Examples Top-1 retrieved images from the SF-XL test set (2.8M database images): Citation
Summarised from the published model card. Read the full card on the HuggingFace links below.
Specifications
| Maker | gberton |
|---|---|
| Type | Embedding models |
| Parameters (lead) | 229M |
| Variants | 1 |
| Runs with | pytorch |
| Released | 2025-02-27 |
| Popularity | 97k downloads / month |
| Likes | 10 |
| Licence | Open weights |
How it works
Variants
Open weights ship in several sizes and precisions. One page, all the variants — pick the one that fits your GPU. VRAM figures are estimates from model size.
| Variant | Params | Precision | VRAM | Fits 16 GB | Weights |
|---|---|---|---|---|---|
| MegaLoc | 229M | BF16 | ~0.5 GB | ✓ | Weights ↗ |
Using it via the API
Once AxForge deploys megaloc for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (megaloc below is illustrative; you get the exact model name on deployment.)
$ curl -sS https://api.axforge.ai/v1/embeddings \
-H "Authorization: Bearer $AXFORGE_API_KEY" \
-H "Content-Type: application/json" \
-d '{"model":"megaloc","input":"text to embed"}'
Licence
Open weights under mit — commercial use is permitted. Deploy it on AxForge EU hardware on request. Read the licence ↗
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