Vision Analysis
Back to Leaderboard

TinyFormer

tinyformerIn LibreYOLO

AICVlab, NYCU · arXiv 2026

PaperCode
Variants5
Parameters11.0M - 127.1M
Best Paper mAP-
LicenseApache-2.0 + DINOv3

Model Variants

All variants benchmarked on COCO val2017. Click any variant for the full hardware breakdown.

ModelParamsGFLOPsPaper mAPBest FPS
TinyFormer-S11.0MUnknown--Details
TinyFormer-M20.5MUnknown--Details
TinyFormer-L34.0MUnknown--Details
TinyFormer-X52.5MUnknown--Details
TinyFormer-XL127.1MUnknown--Details

Architecture

Type

transformer

Backbone

DINOv3-derived ViT

Neck

PBM

Head

DEIMv2 decoder

detrnms-freeTrained on COCO train2017

Run any model with one line

LibreYOLO has the best catalogue of state-of-the-art detectors, all behind one MIT-licensed Python API.

from libreyolo import LibreYOLO, SAMPLE_IMAGE

# LibreYOLO has the best catalogue of state-of-the-art models.
model = LibreYOLO("LibreRFDETRl.pt")           # RF-DETR-L (transformer flagship)
results = model(SAMPLE_IMAGE, save=True)        # run inference, save the annotated image

# Swap in any other model, same one-line API (weights auto-download):
#   LibreYOLO("LibreYOLO9c.pt")      # YOLO9-C
#   LibreYOLO("LibreYOLOXx.pt")      # YOLOX-X
#   LibreYOLO("LibreDFINEx.pt")      # D-FINE-X
#   LibreYOLO("LibreRTDETRr50.pt")   # RT-DETR-R50