rtdetr_r101vd_coco_o365
PekingUapache-2.0vision

rtdetr_r101vd_coco_o365

Updated Nov 13, 2026
Parameters
0.08B
Context
8,192
License
apache-2.0
Updated
Nov 13, 2026

Will it run on your hardware?

Pick your GPU memory - see which quantizations fit, and the cheapest card for the rest

Runs on your 24 GB - best at FP16
4 of 4 quantizations fit rtdetr_r101vd_coco_o365 with real runtime overhead.
Q4_K_M
1 GB
Q5_K_M
1 GB
Q8_0
1 GB
FP16
1 GB
fits tight too big

Need an exact figure for your context length? Use the VRAM calculator.

Run it locally

Copy-paste - running in under a minute

vLLMOpenAI-compatible API
vllm serve PekingU/rtdetr_r101vd_coco_o365

New to this? Start with Ollama · serve to many users with vLLM.

Deep dive

Notes, sources, and the full write-up

rtdetr_r101vd_coco_o365 is an open-weight object detection model from PekingU, published on Hugging Face in June 2024. It has 80M parameters and is released under the apache-2.0 license.

HardwareLink to this section

At full FP16 precision the weights need about 1 GB of memory; 8-bit quantization brings that to roughly 1 GB. That is small enough for most consumer GPUs, Apple Silicon Macs, and many CPUs.

PopularityLink to this section

rtdetr_r101vd_coco_o365 had 1,321,723 downloads on Hugging Face in the last month and has 36 likes.

Run it locallyLink to this section

The weights are on Hugging Face and load with Hugging Face Transformers. Follow the model card for the exact setup and license terms.

Frequently asked

Quick answers to common questions

How much VRAM does rtdetr_r101vd_coco_o365 need?

rtdetr_r101vd_coco_o365 with 0.08B parameters needs approximately 1 GB at Q4_K_M quantization. Use our VRAM calculator for an exact estimate.

Is rtdetr_r101vd_coco_o365 better than other PekingU models?

rtdetr_r101vd_coco_o365 has 0.08B parameters with 8,192 context - a strong choice for object-detection.

What license is rtdetr_r101vd_coco_o365 under?

rtdetr_r101vd_coco_o365 is released under the apache-2.0 license, making it suitable for most commercial and personal projects.

What hardware runs rtdetr_r101vd_coco_o365 well?

With 0.08B parameters, rtdetr_r101vd_coco_o365 requires adequate VRAM. High-end GPUs like the RTX 4090 (24GB), RTX 5090 (32GB), or Mac Studio with unified memory are good options. Check our hardware directory for specific recommendations.

What is the best quantization for rtdetr_r101vd_coco_o365?

Q4_K_M is the recommended sweet spot - ~98% of FP16 quality at ~27% of the size. Q5_K_M (~1 GB) is an option if you have spare VRAM. Use our VRAM calculator to compare.

What models compete with rtdetr_r101vd_coco_o365?

rtdetr_r101vd_coco_o365 competes with other models in its class. Browse our model directory for comparisons, benchmarks, and community reviews to find the best fit.

Nearby options

Similar models and compatible hardware by spec