Approved models
5
Records published from this collection
Provider information
lab
Review approach
Verify each model’s source, terms, capabilities, and current availability
naver models in this directory cover image-to-3d, feature extraction. Start with the task you need to solve, then open a model profile to check its recorded inputs, outputs, licensing and deployment options.
Confirm tensor shape, pooling and normalization in the runtime you will use. Evaluate the downstream task on held-out data and compare memory and throughput at realistic batch sizes.
Check whether two entries describe distinct models or different hosted routes for the same model. Keep the checkpoint, host, test settings and evaluation date together. Missing prices and limits mean the directory has no recorded figure, not that use is free or unlimited.
Browse the AI model directory or compare two models.
Review each record individually; collection membership does not imply a recommendation or guarantee of availability.
| naver/DUSt3R_ViTLarge_BaseDecoder_224_linear naver | 10.0 | — | — | — | — |
| naver/DUSt3R_ViTLarge_BaseDecoder_512_dpt naver | 10.0 | — | — | — | — |
| naver/DUSt3R_ViTLarge_BaseDecoder_512_linear naver | 10.0 | — | — | — | — |
| naver/MASt3R_ViTLarge_BaseDecoder_512_catmlpdpt_metric naver | 10.0 | — | — | — | — |
| naver/splade-cocondenser-ensembledistil naver | 5.0 | — | — | — | — |
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About this order: Recommended shows our editorial shortlist first, followed by recent releases. The spec score is a 0–100 figure SyncDev calculates from each vendor's published specifications — context window, reasoning support, input modalities, tool calling, maximum output and how recently the model shipped. It measures breadth of capability, not benchmark performance, so a higher-scoring model is not automatically the better choice for your task.