{
  "id": "mobilesam",
  "identity": {
    "family": "mobilesam",
    "display_name": "MobileSAM",
    "hub_id": "dhkim2810/MobileSAM (mobile_sam.pt)",
    "api_name": null,
    "revision": null,
    "variants": [],
    "license": "Apache-2.0",
    "commercial_use": true,
    "commercial_use_note": "Apache-2.0 per the GitHub repo (the hub mirror is tagged MIT); no use restrictions either way.",
    "release_date": "2023-06",
    "paper_url": "https://arxiv.org/abs/2306.14289",
    "repo_url": "https://github.com/ChaoningZhang/MobileSAM"
  },
  "task": {
    "category": "segmentation",
    "modalities_in": [
      "image"
    ],
    "modalities_out": [
      "masks",
      "scores"
    ],
    "best_at": "SAM with a 5M-parameter TinyViT encoder: box or point prompted masks on CPU in tens of milliseconds.",
    "worst_at": "Mask quality below SAM 2; images only."
  },
  "io": {
    "input": {
      "image": {
        "resolution": "1024x1024"
      },
      "prompts": "points and boxes"
    },
    "output": {
      "masks": "binary masks with IoU predictions"
    }
  },
  "mixpeek_wiring": {
    "extractors": [],
    "feature_uris": [],
    "vector_indexes": [],
    "retriever_stages": [],
    "composes_with": [
      "detector boxes -> MobileSAM masks -> masked crops -> SigLIP"
    ]
  },
  "run": {
    "status": "not_runnable",
    "status_reason": "Weights are a .pt pickle and the model code is the repo's (segment_anything fork). The repo ships an ONNX export script; once exported to ONNX it runs as a CPU plugin with onnxruntime.",
    "serve_apps": [],
    "runtime": "mobile_sam package (sam_model_registry['vit_t']) or onnxruntime after export",
    "weights_format": "pickle",
    "trust_remote_code": false,
    "size_on_disk_mb": 41,
    "params_millions": 10,
    "preprocessing": "Resize longest side to 1024, pad, normalize.",
    "postprocessing": "Threshold mask logits, pick by predicted IoU.",
    "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://dhkim2810/MobileSAM@4e2e5245fe9dc63096d575d36e70eb39b03b3aba",
    "github://ChaoningZhang/MobileSAM/weights/mobile_sam.pt"
  ],
  "formats": [
    {
      "ref": "hf://dhkim2810/MobileSAM@4e2e5245fe9dc63096d575d36e70eb39b03b3aba",
      "format": "pytorch_pt",
      "file": "mobile_sam.pt",
      "loader": "torch.load (pickle); Mixpeek refuses pickle weights (shared/security/torch_pickle.py)",
      "supported_today": false
    },
    {
      "ref": "github://ChaoningZhang/MobileSAM/weights/mobile_sam.pt",
      "format": "pytorch_pt",
      "file": "mobile_sam.pt",
      "loader": "torch.load (pickle); Mixpeek refuses pickle weights (shared/security/torch_pickle.py)",
      "supported_today": false
    }
  ],
  "use_cases": [
    "segmentation",
    "object-detection"
  ],
  "recommended": {
    "value": false,
    "for": [],
    "reason": null
  },
  "demos": [],
  "seo": {
    "title": "MobileSAM: segmentation model",
    "description": "MobileSAM is a image segmentation model (Apache-2.0). Not runnable on Mixpeek today.",
    "keywords": [
      "MobileSAM",
      "mobilesam",
      "segmentation",
      "dhkim2810/MobileSAM (mobile_sam.pt)",
      "object-detection"
    ],
    "faqs": [
      {
        "q": "What is MobileSAM best at?",
        "a": "SAM with a 5M-parameter TinyViT encoder: box or point prompted masks on CPU in tens of milliseconds."
      },
      {
        "q": "What are the limits of MobileSAM?",
        "a": "Mask quality below SAM 2; images only."
      },
      {
        "q": "Can MobileSAM be used commercially?",
        "a": "Yes. Apache-2.0 per the GitHub repo (the hub mirror is tagged MIT); no use restrictions either way."
      },
      {
        "q": "How does MobileSAM run on Mixpeek?",
        "a": "Weights are a .pt pickle and the model code is the repo's (segment_anything fork). The repo ships an ONNX export script; once exported to ONNX it runs as a CPU plugin with onnxruntime."
      }
    ]
  },
  "last_verified": "2026-11-05",
  "sources": [
    "https://huggingface.co/dhkim2810/MobileSAM",
    "https://github.com/ChaoningZhang/MobileSAM",
    "https://arxiv.org/abs/2306.14289"
  ],
  "registry": null,
  "templates": [],
  "usage": {
    "namespaces": null,
    "collections": null,
    "uncounted": true,
    "templates": 0,
    "counted_at": null,
    "source": null
  },
  "facets": {
    "status": "not_runnable",
    "category": "segmentation",
    "family": "mobilesam",
    "license": "Apache-2.0",
    "commercial_use": true,
    "modalities_in": [
      "image"
    ],
    "modalities_out": [
      "masks",
      "scores"
    ],
    "use_cases": [
      "segmentation",
      "object-detection"
    ],
    "recommended": false,
    "release_date": "2023-06",
    "params_millions": 10,
    "size_on_disk_mb": 41,
    "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": [
      "github",
      "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
}