Approved models
7
Records published from this collection
Provider information
lab
Review approach
Verify each model’s source, terms, capabilities, and current availability
PekingU models in this directory cover object detection. Start with the task you need to solve, then open a model profile to check its recorded inputs, outputs, licensing and deployment options.
Measure missed objects, false positives and localization at several IoU thresholds. Include small, overlapping and partially hidden objects; record input resolution and preprocessing.
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.
| PekingU/rtdetr_r101vd_coco_o365 PekingU | 10.0 | — | — | — | — |
| PekingU/rtdetr_r18vd PekingU | 10.0 | — | — | — | — |
| PekingU/rtdetr_r50vd PekingU | 10.0 | — | — | — | — |
| PekingU/rtdetr_r50vd_coco_o365 PekingU | 10.0 | — | — | — | — |
| PekingU/rtdetr_v2_r101vd PekingU | 10.0 | — | — | — | — |
| PekingU/rtdetr_v2_r18vd PekingU | 10.0 | — | — | — | — |
| PekingU/rtdetr_v2_r50vd PekingU | 10.0 | — | — | — | — |
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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.