{
  "artifacts": [
    {
      "file": "ppocrv6_small_rec_640_fp32.tflite",
      "sha256": "904c9a589763123d8a4c01d205c78669cfe3723b2a23b2221bdeb26fccc66a5d",
      "size_mb": 20.482
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  ],
  "benchmarks": [],
  "browser": {
    "backends": [
      {
        "backend": "wasm_xnnpack",
        "date": "2026-09-25",
        "env": {
          "browser": "chromium",
          "browser_version": "151.0.7922.34",
          "headless": true,
          "jspi": true,
          "litertjs_core_version": "2.5.3",
          "machine_label": "mac-studio-m4-max",
          "os": "macOS",
          "os_version": "27.0.0",
          "webgpu_adapter": {
            "architecture": "metal-3",
            "description": "",
            "device": "",
            "vendor": "apple"
          }
        },
        "full_delegation": null,
        "latency_p50_ms": 83.455,
        "loads": true,
        "max_rel_diff": null,
        "output_match": null,
        "provenance": "measured",
        "runs": true
      },
      {
        "backend": "webgpu_mldrift",
        "date": "2026-09-25",
        "env": {
          "browser": "chromium",
          "browser_version": "151.0.7922.34",
          "headless": true,
          "jspi": true,
          "litertjs_core_version": "2.5.3",
          "machine_label": "mac-studio-m4-max",
          "os": "macOS",
          "os_version": "27.0.0",
          "webgpu_adapter": {
            "architecture": "metal-3",
            "description": "",
            "device": "",
            "vendor": "apple"
          }
        },
        "full_delegation": true,
        "latency_p50_ms": 23.417,
        "loads": true,
        "max_rel_diff": 0.00010432126105638897,
        "output_match": true,
        "provenance": "measured",
        "runs": true
      }
    ],
    "demo_url": null,
    "sweep_source": "data/sweep/2.5.3/2026-09-25/pp-ocrv6-small__ppocrv6_small_rec_640_fp32.json"
  },
  "conversion": {
    "command": ".venv/bin/python conversion/build.py rec --width 640",
    "quantization": "none — fp32 (conversion/README.md: 'Reproduce the FP32 conversion'; the card: 'FP16 and INT8 artifact variants were not evaluated')",
    "tool": "litert-torch",
    "tool_version": "0.9.4 (litert-converter 0.4.0; torch 2.13.0; Python 3.12.12 per conversion/README.md)"
  },
  "cross_runtime": [],
  "delegation": {
    "backend": "gpu_mldrift",
    "blocking_ops": [
      "CONV_2D",
      "ADD",
      "DEPTHWISE_CONV_2D",
      "PAD",
      "SUM",
      "MUL",
      "RESHAPE",
      "SUB",
      "TRANSPOSE",
      "MAX_POOL_2D",
      "CONCATENATION",
      "AVERAGE_POOL_2D",
      "LOGISTIC",
      "MEAN",
      "SQUARED_DIFFERENCE",
      "RSQRT",
      "FULLY_CONNECTED",
      "SLICE",
      "BATCH_MATMUL",
      "SOFTMAX"
    ],
    "coverage_ops_pct": 4.6,
    "lint_report_version": "1.1",
    "litert_version": "2.2.0",
    "matched_provenance_counts": {
      "measured": 17,
      "unmatched": 264
    },
    "partitions": 13
  },
  "model": {
    "family": "pp-ocrv6-small",
    "id": "pp-ocrv6-small__ppocrv6_small_rec_640_fp32",
    "license": "apache-2.0",
    "source_url": "https://huggingface.co/litert-community/PP-OCRv6-Small-LiteRT",
    "task": "image-to-text"
  },
  "pitfalls": [
    "FP32 model storage and GPU computation precision are separate settings: the same four files passed only 27/37 tensor cases at the runtime's default GPU precision and 37/37 with explicit FP32 (card, 'FP32 model storage and GPU computation precision are separate settings').",
    "NPU execution completed but its parity failed (19/37 tensor cases, 0/6 complete image cases); NPU is not a supported configuration for this release (card).",
    "Outputs are probabilities; do not apply another softmax. The 18,710-entry dictionary already contains blank at index 0 and space at the final index; greedy CTC collapses repeats then drops blank (card, recognizer usage).",
    "Graph rewrites are exact re-implementations, not approximations: the detector's two k2/s2 transposed convolutions became zero stuffing + flipped convolution, fused QKV split into 4D branches, spatial means split, clamps / hard sigmoid as ReLU differences; exact GELU retained (conversion/README.md)."
  ],
  "schema_version": "1.1"
}