{
  "id": "yolo26-detect",
  "identity": {
    "family": "yolo26",
    "display_name": "Ultralytics YOLO26 detect",
    "hub_id": "Ultralytics/YOLO26 (yolo26n.pt)",
    "api_name": null,
    "revision": null,
    "variants": [
      "yolo26s.pt",
      "yolo26m.pt",
      "yolo26l.pt",
      "yolo26x.pt"
    ],
    "license": "AGPL-3.0",
    "commercial_use": false,
    "commercial_use_note": "AGPL-3.0: offering it over a network obliges publishing the whole application's source under AGPL; closed commercial use needs an Ultralytics Enterprise license.",
    "release_date": "2026-01-14",
    "paper_url": null,
    "repo_url": "https://github.com/ultralytics/ultralytics"
  },
  "task": {
    "category": "detection",
    "modalities_in": [
      "image"
    ],
    "modalities_out": [
      "boxes",
      "labels",
      "scores"
    ],
    "best_at": "Fast detect for the fixed COCO label set; n size runs in real time on CPU.",
    "worst_at": "Closed label set (needs fine-tuning for new classes); license blocks closed commercial use; small or crowded objects at 640 input."
  },
  "io": {
    "input": {
      "image": {
        "resolution": "640x640 letterboxed",
        "color": "RGB"
      },
      "prompts": "none (fixed classes)"
    },
    "output": {
      "boxes": "xyxy pixels",
      "labels": "COCO 80 classes",
      "scores": "0..1"
    }
  },
  "mixpeek_wiring": {
    "extractors": [],
    "feature_uris": [],
    "vector_indexes": [],
    "retriever_stages": [],
    "composes_with": [
      "detector boxes -> crops -> SigLIP vectors per object (one document per object, or a multi-vector per frame)",
      "labels -> payload field -> attribute filter in a retriever",
      "scene splits -> keyframes -> detector -> object documents with frame timestamps"
    ]
  },
  "run": {
    "status": "not_runnable",
    "status_reason": "Blocked by AGPL-3.0 and pickle .pt weights. Would run as a custom extractor plugin that exports the checkpoint to ONNX once (ultralytics export format=onnx) and serves it with onnxruntime on CPU, emitting boxes, labels and crops.",
    "serve_apps": [],
    "runtime": "ultralytics YOLO (or onnxruntime after export)",
    "weights_format": "pickle",
    "trust_remote_code": false,
    "size_on_disk_mb": 5.5,
    "params_millions": null,
    "preprocessing": "Letterbox to 640x640 (stride-aligned padding), RGB, scale to 0..1.",
    "postprocessing": "Confidence threshold then end-to-end, NMS-free",
    "serving_shape": "both",
    "batch_size": null,
    "serve_batch": null,
    "scale_to_zero": {
      "min_replicas": 0,
      "max_replicas": 1,
      "idle_timeout_s": 600,
      "memory_gb": 1,
      "num_cpus": 1,
      "num_gpus": 0,
      "cold_start_s": {
        "warm_node_s": null,
        "new_node_s": null,
        "source": null
      },
      "cpu_fallback": true
    }
  },
  "cost": {
    "unmeasured": true,
    "measured": null,
    "note": "No committed measurement; plan row 3 measures it in the standalone image."
  },
  "evidence": {
    "unmeasured": true,
    "items": []
  },
  "refs": [
    "hf://Ultralytics/YOLO26@070ac3c51435984d992ba92eb3f234daf4e4500d"
  ],
  "formats": [
    {
      "ref": "hf://Ultralytics/YOLO26@070ac3c51435984d992ba92eb3f234daf4e4500d",
      "format": "pytorch_pt",
      "file": "25 files, e.g. yolo26l-cls.pt",
      "loader": "torch.load (pickle); Mixpeek refuses pickle weights (shared/security/torch_pickle.py)",
      "supported_today": false
    }
  ],
  "use_cases": [
    "object-detection"
  ],
  "recommended": {
    "value": false,
    "for": [],
    "reason": null
  },
  "demos": [],
  "seo": {
    "title": "Ultralytics YOLO26 detect: object detection model",
    "description": "Ultralytics YOLO26 detect is a image object detection model (AGPL-3.0). Not runnable on Mixpeek today.",
    "keywords": [
      "Ultralytics YOLO26 detect",
      "yolo26",
      "object detection",
      "Ultralytics/YOLO26 (yolo26n.pt)",
      "object-detection"
    ],
    "faqs": [
      {
        "q": "What is Ultralytics YOLO26 detect best at?",
        "a": "Fast detect for the fixed COCO label set; n size runs in real time on CPU."
      },
      {
        "q": "What are the limits of Ultralytics YOLO26 detect?",
        "a": "Closed label set (needs fine-tuning for new classes); license blocks closed commercial use; small or crowded objects at 640 input."
      },
      {
        "q": "Can Ultralytics YOLO26 detect be used commercially?",
        "a": "No. AGPL-3.0: offering it over a network obliges publishing the whole application's source under AGPL; closed commercial use needs an Ultralytics Enterprise license."
      },
      {
        "q": "How does Ultralytics YOLO26 detect run on Mixpeek?",
        "a": "Blocked by AGPL-3.0 and pickle .pt weights. Would run as a custom extractor plugin that exports the checkpoint to ONNX once (ultralytics export format=onnx) and serves it with onnxruntime on CPU, emitting boxes, labels and crops."
      }
    ]
  },
  "last_verified": "2026-11-05",
  "sources": [
    "https://huggingface.co/Ultralytics/YOLO26",
    "https://docs.ultralytics.com/models/yolo26/",
    "https://www.ultralytics.com/license",
    "https://roboflow.com/model-licenses/yoloe"
  ],
  "registry": null,
  "templates": [],
  "usage": {
    "namespaces": null,
    "collections": null,
    "uncounted": true,
    "templates": 0,
    "counted_at": null,
    "source": null
  },
  "facets": {
    "status": "not_runnable",
    "category": "detection",
    "family": "yolo26",
    "license": "AGPL-3.0",
    "commercial_use": false,
    "modalities_in": [
      "image"
    ],
    "modalities_out": [
      "boxes",
      "labels",
      "scores"
    ],
    "use_cases": [
      "object-detection"
    ],
    "recommended": false,
    "release_date": "2026-01-14",
    "params_millions": null,
    "size_on_disk_mb": 5.5,
    "vector_dims": null,
    "vector_distance": null,
    "weights_format": "pickle",
    "formats": [
      "pytorch_pt"
    ],
    "loadable_today": false,
    "trust_remote_code": false,
    "cpu_fallback": true,
    "num_gpus": 0,
    "memory_gb": 1,
    "min_replicas": 0,
    "serving_shape": "both",
    "served": false,
    "ref_schemes": [
      "hf"
    ],
    "has_evidence": false,
    "cost_measured": false,
    "template_count": 0,
    "usage_namespaces": null,
    "usage_collections": null,
    "usage_uncounted": true,
    "has_demo": false,
    "rank_score": 0
  },
  "rank_score": 0
}