yolo26n

by ultralytics

Edge-optimized NMS-free object detector with 43% faster CPU inference

~3M (Nano)params

HuggingFace Use in Pipeline

Identifiers

Model ID

ultralytics/yolo26n

Feature URI

mixpeek://image_extractor@v1/ultralytics_yolo26n_v1

Overview

YOLO26 is Ultralytics' latest generation real-time object detector, engineered from the ground up for edge and low-power devices. It removes Decoupled Focal Loss (DFL) for simplified export, introduces end-to-end NMS-free inference for streamlined deployment, and uses ProgLoss + STAL for improved small-object accuracy. The MuSGD optimizer (SGD + Muon) delivers up to 43% faster CPU inference.

On Mixpeek, YOLO26 is the default object detection model for video analysis pipelines requiring real-time performance on edge hardware. Its NMS-free architecture eliminates a common deployment pain point, and the Nano variant runs on mobile and IoT devices while maintaining competitive detection accuracy.

Architecture

Attention-centric backbone with R-ELAN modules. NMS-free end-to-end inference via learned object queries. ProgLoss (progressive loss scaling) and STAL (Spatial-Temporal Attention Loss) for improved small-object detection. Available in Nano (N), Small (S), Medium (M), Large (L), and Extra Large (X) variants. Supports export to TensorRT, ONNX, CoreML, TFLite, and OpenVINO.

Mixpeek SDK Integration

from mixpeek import Mixpeek

mixpeek = Mixpeek(api_key="YOUR_API_KEY")

mixpeek.ingest.videos(
    collection="surveillance_feeds",
    source={"type": "s3", "bucket": "camera-feeds"},
    pipeline={
        "object_detection": {
            "model": "mixpeek://image_extractor@v1/ultralytics_yolo26n_v1"
        },
        "embedding": {
            "model": "mixpeek://image_extractor@v1/openai_clip_vit_large_v1"
        }
    }
)