Ultralytics YOLO26 models
Built from the ground up for edge and low-power devices, Ultralytics YOLO26 sets a new standard for real-time vision AI, delivering up to 43% faster CPU inference with a cleaner, simpler architecture.
Trusted by industry leaders
Try YOLO26 Inference
Drag and drop an image to see real-time object detection
Input Image
Upload an image or select an example to test yolo26n. Predict Docs
Drop an image here
or click to browse
Supports JPEG, PNG, WebP, AVIF, HEIC, JP2, TIFF, BMP & more (max 10MB)
Confidence
0.25
IoU
0.70
Image Size
640
API Docs
Deploy your model to get a dedicated inference endpoint with API key authentication — then replace the placeholder URL and key below with your deployment values. Deploy docs
Note: This is example code. Deploy your model first to get your endpoint URL and API key.
import requests
# Replace with your deployment URL and API key
url = "https://your-deployment-url.run.app/predict"
api_key = "YOUR_API_KEY"
# Optional inference parameters (conf, iou, imgsz)
args = {"conf": 0.25, "iou": 0.7, "imgsz": 640}
with open("image.jpg", "rb") as f:
response = requests.post(
url,
headers={"Authorization": f"Bearer {api_key}"},
data=args,
files={"file": f},
)
print(response.json())Key Ultralytics YOLO26 improvements
Up to 43% faster CPU inference
Real-time performance on devices without GPUs, purpose-built for edge and constrained environments.
NMS-free, end-to-end inference
Predictions are generated directly, with no post-processing step. Lower latency, simpler deployment.
No DFL, broader hardware compatibility
Removing Distribution Focal Loss simplifies exports and broadens edge device compatibility.
MuSGD: A smarter optimizer
A hybrid of SGD and Muon inspired by LLM training advances for more stable training.
Ultralytics YOLO models at a glance
Compare recent Ultralytics YOLO model families across speed, accuracy, and supported vision tasks.
| Features |  |  |  |  |
|---|---|---|---|---|
| Speed Image processing time | 1.06 ms | 0.99 ms | 1.5 ms | 1.7 ms |
| Accuracy mAP50-95 | 34.3% | 37.3% | 39.5% | 40.9% |
| Object detection | ||||
| Image classification | - | |||
| Instance segmentation | - | |||
| Semantic segmentation | - | - | ||
| Pose estimation | - | |||
| OBB detection | - |
Why choose Ultralytics YOLO26?
Built for edge and cloud
Runs efficiently on CPUs, GPUs, and edge hardware. Export to 19 formats and deploy anywhere.
Up to 43% faster CPU inference
Real-time vision AI on resource-constrained devices, without sacrificing accuracy.
Open-world detection with YOLOE-26
Detect beyond fixed categories using text prompts, visual prompts, or prompt-free inference.
Seamless integration
YOLO26 follows the same familiar interface as YOLOv8 and YOLO11, with no steep learning curve.
Backed by a global community
Dedicated support channels, active forums, and regular updates keep you moving forward.
Clear licensing
Flexible options for academic, open-source, and commercial use under AGPL-3.0 and Enterprise.
See our models in action
Glacier Robotics reduced PET leakage by 70% across US recycling facilities
See how Glacier Robotics uses Ultralytics YOLO11 to reduce PET leakage by 70%, improve recycling accuracy, and automate waste sorting.
SOHGA cuts parking monitoring time by 30% with Ultralytics YOLO
Learn how SOHGA's MEGURU system uses Ultralytics YOLO26 to automate parking lot patrols, reduce patrol time by 30%, and improve safety.
Scaleout cuts model updates from weeks to hours with Ultralytics YOLO
Discover how Scaleout uses Ultralytics YOLO and federated learning to fine-tune AI models on edge devices while keeping sensitive data secure.
RapiD Engineering deploys seafood quality control 1 week faster with Ultralytics YOLO
See how RapiD Engineering uses Ultralytics YOLO to automate salmon inspection, detect defects in real time, and save a week of engineering work.
Project Ocean Oasis advances reef conservation with Ultralytics YOLO
Discover how Project Ocean Oasis uses Ultralytics YOLO, edge AI, and autonomous monitoring systems to scale reef conservation and ocean intelligence.
Volley powers 250+ on-court AI trainers with Ultralytics YOLO
"What's really nice is that the model performs really well in real time on edge hardware on the trainer, and we can use the same model in the cloud to run the exact same flow."
WG Tech Solutions cuts safety violations by 28% with Ultralytics YOLO and Axelera’s AI Accelerator
Learn how WG Tech Solutions managed to reduce safety violations in manufacturing by 28% leveraging Ultralytics YOLO and Axelera’s AI Accelerator
Stride delivers 1-minute equine gait analysis with Ultralytics YOLO
Learn how Stride leverages Ultralytics YOLO models for horse pose estimation, achieving a full gait analysis in under 1 minute.
Pixelabs achieves 95% recall with Ultralytics YOLO-driven automation
Learn how Pixelabs leverages Ultralytics YOLO models to automate workflows and achieve 95% recall.
SiteAssist improves site safety by processing 770K+ images with Ultralytics YOLO
Learn how SiteAssist leverages Ultralytics YOLO models to improve construction site safety.
Chef Robotics uses Ultralytics YOLO to cut food giveaway by 67%
Explore how Chef Robotics uses Ultralytics YOLO models for precise food assembly.
Cali Intelligence shortens checkout queues by 43% with Ultralytics YOLO
Explore how Cali Intelligence uses Ultralytics YOLO models to reduce retail checkout queues with object detection.
MarineSitu hits 96%+ uptime in underwater monitoring using Ultralytics YOLO
Discover how MarineSitu uses Ultralytics YOLO to transform underwater object detection.
Theia Scientific speeds up microscopy analysis 43× with Ultralytics YOLO
Discover how Theia Scientific uses Ultralytics YOLO to redefine microscopy data analysis.
eSmart Systems halves power line inspection time with Ultralytics YOLO
Discover how eSmart Systems uses Ultralytics YOLO to boost defect detection speed and transform utility inspections.
Axelera AI delivers 34 FPS edge AI inference using Ultralytics YOLO
Discover how Axelera AI uses Ultralytics YOLO to deliver fast, accurate, and efficient edge vision on Metis AI chips.
STMicroelectronics runs Ultralytics YOLO on an MCU at just 9.4 mJ per inference
Discover how STMicroelectronics efficiently deploys Ultralytics YOLO models on low-power microcontrollers to achieve accurate real-time inference at the edge.
Specialvideo reaches 99% food inspection accuracy with Ultralytics YOLO
Discover how Specialvideo uses Ultralytics YOLO models to power real-time AI food inspection, ensuring quality, reducing waste, and boosting efficiency.
Vivity AI saves $5M+ a year in industrial operations with Ultralytics YOLO
Discover how Vivity AI leverages Ultralytics YOLO models to enhance industrial automation, improving efficiency, reducing downtime, and ensuring workplace safety.
Videologic Analytics scales to 10K AI camera licenses with Ultralytics YOLO
Discover how Videologic Analytics integrates Ultralytics YOLO models to enhance video surveillance, improving detection accuracy, reducing false alarms, and optimizing real-time threat monitoring.
Prezent boosts slide detection accuracy by 34% with Ultralytics YOLO
Discover how Prezent leverages Ultralytics YOLO models to automate slide element detection, reducing processing time to under 10 seconds while preserving structure and design.
ALYCE accelerates traffic AI inference by 20% with Ultralytics YOLO
Discover how ALYCE uses Ultralytics YOLO models to enhance data accuracy, optimize urban mobility, and create AI-driven traffic solutions for sustainable, smarter cities.
Kiwitron uses Ultralytics YOLO to detect industrial hazards 30m away
Explore how Kiwitron uses Ultralytics YOLO models in its KewiEye solution to detect and address industrial hazards for better safety.
Glacier Robotics reduced PET leakage by 70% across US recycling facilities
See how Glacier Robotics uses Ultralytics YOLO11 to reduce PET leakage by 70%, improve recycling accuracy, and automate waste sorting.
SOHGA cuts parking monitoring time by 30% with Ultralytics YOLO
Learn how SOHGA's MEGURU system uses Ultralytics YOLO26 to automate parking lot patrols, reduce patrol time by 30%, and improve safety.
Scaleout cuts model updates from weeks to hours with Ultralytics YOLO
Discover how Scaleout uses Ultralytics YOLO and federated learning to fine-tune AI models on edge devices while keeping sensitive data secure.
RapiD Engineering deploys seafood quality control 1 week faster with Ultralytics YOLO
See how RapiD Engineering uses Ultralytics YOLO to automate salmon inspection, detect defects in real time, and save a week of engineering work.
Project Ocean Oasis advances reef conservation with Ultralytics YOLO
Discover how Project Ocean Oasis uses Ultralytics YOLO, edge AI, and autonomous monitoring systems to scale reef conservation and ocean intelligence.
Volley powers 250+ on-court AI trainers with Ultralytics YOLO
"What's really nice is that the model performs really well in real time on edge hardware on the trainer, and we can use the same model in the cloud to run the exact same flow."
WG Tech Solutions cuts safety violations by 28% with Ultralytics YOLO and Axelera’s AI Accelerator
Learn how WG Tech Solutions managed to reduce safety violations in manufacturing by 28% leveraging Ultralytics YOLO and Axelera’s AI Accelerator
Stride delivers 1-minute equine gait analysis with Ultralytics YOLO
Learn how Stride leverages Ultralytics YOLO models for horse pose estimation, achieving a full gait analysis in under 1 minute.
Pixelabs achieves 95% recall with Ultralytics YOLO-driven automation
Learn how Pixelabs leverages Ultralytics YOLO models to automate workflows and achieve 95% recall.
SiteAssist improves site safety by processing 770K+ images with Ultralytics YOLO
Learn how SiteAssist leverages Ultralytics YOLO models to improve construction site safety.
Chef Robotics uses Ultralytics YOLO to cut food giveaway by 67%
Explore how Chef Robotics uses Ultralytics YOLO models for precise food assembly.
Cali Intelligence shortens checkout queues by 43% with Ultralytics YOLO
Explore how Cali Intelligence uses Ultralytics YOLO models to reduce retail checkout queues with object detection.
MarineSitu hits 96%+ uptime in underwater monitoring using Ultralytics YOLO
Discover how MarineSitu uses Ultralytics YOLO to transform underwater object detection.
Theia Scientific speeds up microscopy analysis 43× with Ultralytics YOLO
Discover how Theia Scientific uses Ultralytics YOLO to redefine microscopy data analysis.
eSmart Systems halves power line inspection time with Ultralytics YOLO
Discover how eSmart Systems uses Ultralytics YOLO to boost defect detection speed and transform utility inspections.
Axelera AI delivers 34 FPS edge AI inference using Ultralytics YOLO
Discover how Axelera AI uses Ultralytics YOLO to deliver fast, accurate, and efficient edge vision on Metis AI chips.
STMicroelectronics runs Ultralytics YOLO on an MCU at just 9.4 mJ per inference
Discover how STMicroelectronics efficiently deploys Ultralytics YOLO models on low-power microcontrollers to achieve accurate real-time inference at the edge.
Specialvideo reaches 99% food inspection accuracy with Ultralytics YOLO
Discover how Specialvideo uses Ultralytics YOLO models to power real-time AI food inspection, ensuring quality, reducing waste, and boosting efficiency.
Vivity AI saves $5M+ a year in industrial operations with Ultralytics YOLO
Discover how Vivity AI leverages Ultralytics YOLO models to enhance industrial automation, improving efficiency, reducing downtime, and ensuring workplace safety.
Videologic Analytics scales to 10K AI camera licenses with Ultralytics YOLO
Discover how Videologic Analytics integrates Ultralytics YOLO models to enhance video surveillance, improving detection accuracy, reducing false alarms, and optimizing real-time threat monitoring.
Prezent boosts slide detection accuracy by 34% with Ultralytics YOLO
Discover how Prezent leverages Ultralytics YOLO models to automate slide element detection, reducing processing time to under 10 seconds while preserving structure and design.
ALYCE accelerates traffic AI inference by 20% with Ultralytics YOLO
Discover how ALYCE uses Ultralytics YOLO models to enhance data accuracy, optimize urban mobility, and create AI-driven traffic solutions for sustainable, smarter cities.
Kiwitron uses Ultralytics YOLO to detect industrial hazards 30m away
Explore how Kiwitron uses Ultralytics YOLO models in its KewiEye solution to detect and address industrial hazards for better safety.
Glacier Robotics reduced PET leakage by 70% across US recycling facilities
See how Glacier Robotics uses Ultralytics YOLO11 to reduce PET leakage by 70%, improve recycling accuracy, and automate waste sorting.
SOHGA cuts parking monitoring time by 30% with Ultralytics YOLO
Learn how SOHGA's MEGURU system uses Ultralytics YOLO26 to automate parking lot patrols, reduce patrol time by 30%, and improve safety.
Scaleout cuts model updates from weeks to hours with Ultralytics YOLO
Discover how Scaleout uses Ultralytics YOLO and federated learning to fine-tune AI models on edge devices while keeping sensitive data secure.
RapiD Engineering deploys seafood quality control 1 week faster with Ultralytics YOLO
See how RapiD Engineering uses Ultralytics YOLO to automate salmon inspection, detect defects in real time, and save a week of engineering work.
Project Ocean Oasis advances reef conservation with Ultralytics YOLO
Discover how Project Ocean Oasis uses Ultralytics YOLO, edge AI, and autonomous monitoring systems to scale reef conservation and ocean intelligence.
Volley powers 250+ on-court AI trainers with Ultralytics YOLO
"What's really nice is that the model performs really well in real time on edge hardware on the trainer, and we can use the same model in the cloud to run the exact same flow."
WG Tech Solutions cuts safety violations by 28% with Ultralytics YOLO and Axelera’s AI Accelerator
Learn how WG Tech Solutions managed to reduce safety violations in manufacturing by 28% leveraging Ultralytics YOLO and Axelera’s AI Accelerator
Stride delivers 1-minute equine gait analysis with Ultralytics YOLO
Learn how Stride leverages Ultralytics YOLO models for horse pose estimation, achieving a full gait analysis in under 1 minute.
Pixelabs achieves 95% recall with Ultralytics YOLO-driven automation
Learn how Pixelabs leverages Ultralytics YOLO models to automate workflows and achieve 95% recall.
SiteAssist improves site safety by processing 770K+ images with Ultralytics YOLO
Learn how SiteAssist leverages Ultralytics YOLO models to improve construction site safety.
Chef Robotics uses Ultralytics YOLO to cut food giveaway by 67%
Explore how Chef Robotics uses Ultralytics YOLO models for precise food assembly.
Cali Intelligence shortens checkout queues by 43% with Ultralytics YOLO
Explore how Cali Intelligence uses Ultralytics YOLO models to reduce retail checkout queues with object detection.
MarineSitu hits 96%+ uptime in underwater monitoring using Ultralytics YOLO
Discover how MarineSitu uses Ultralytics YOLO to transform underwater object detection.
Theia Scientific speeds up microscopy analysis 43× with Ultralytics YOLO
Discover how Theia Scientific uses Ultralytics YOLO to redefine microscopy data analysis.
eSmart Systems halves power line inspection time with Ultralytics YOLO
Discover how eSmart Systems uses Ultralytics YOLO to boost defect detection speed and transform utility inspections.
Axelera AI delivers 34 FPS edge AI inference using Ultralytics YOLO
Discover how Axelera AI uses Ultralytics YOLO to deliver fast, accurate, and efficient edge vision on Metis AI chips.
STMicroelectronics runs Ultralytics YOLO on an MCU at just 9.4 mJ per inference
Discover how STMicroelectronics efficiently deploys Ultralytics YOLO models on low-power microcontrollers to achieve accurate real-time inference at the edge.
Specialvideo reaches 99% food inspection accuracy with Ultralytics YOLO
Discover how Specialvideo uses Ultralytics YOLO models to power real-time AI food inspection, ensuring quality, reducing waste, and boosting efficiency.
Vivity AI saves $5M+ a year in industrial operations with Ultralytics YOLO
Discover how Vivity AI leverages Ultralytics YOLO models to enhance industrial automation, improving efficiency, reducing downtime, and ensuring workplace safety.
Videologic Analytics scales to 10K AI camera licenses with Ultralytics YOLO
Discover how Videologic Analytics integrates Ultralytics YOLO models to enhance video surveillance, improving detection accuracy, reducing false alarms, and optimizing real-time threat monitoring.
Prezent boosts slide detection accuracy by 34% with Ultralytics YOLO
Discover how Prezent leverages Ultralytics YOLO models to automate slide element detection, reducing processing time to under 10 seconds while preserving structure and design.
ALYCE accelerates traffic AI inference by 20% with Ultralytics YOLO
Discover how ALYCE uses Ultralytics YOLO models to enhance data accuracy, optimize urban mobility, and create AI-driven traffic solutions for sustainable, smarter cities.
Kiwitron uses Ultralytics YOLO to detect industrial hazards 30m away
Explore how Kiwitron uses Ultralytics YOLO models in its KewiEye solution to detect and address industrial hazards for better safety.
Frequently asked questions
YOLO26 supports export to TensorRT, ONNX, CoreML, TFLite, and OpenVINO, covering the most common edge deployment targets. The NMS-free architecture means fewer integration headaches and lower latency out of the box.
Yes. YOLO26 follows the same interface as previous Ultralytics YOLO releases, so migrating is straightforward. Simply swap in your YOLO26 model weights.
Object detection, instance segmentation, semantic segmentation, image classification, pose estimation, and oriented object detection, all in a single unified model family.
The nano (n) variant is ideal for edge and CPU-constrained devices. The small (s) and medium (m) variants offer a strong balance of speed and accuracy for most applications. The large (l) and extra-large (x) variants deliver maximum accuracy for demanding workloads.
YOLO26 removes DFL for simpler export, eliminates NMS for faster end-to-end inference, improves small-object accuracy with ProgLoss + STAL, introduces the MuSGD optimizer for more stable training, and delivers up to 43% faster CPU inference.
Get started with Ultralytics YOLO!
From annotation to deployment, build vision AI solutions that scale with you.