{ "type": "aggregate_saved_runtime_measurements", "comparison": "Different hardware, cohorts, windows and timing units; not a matched speed ranking or speedup measurement.", "quantiles": "NumPy median and linear-interpolated 0.95 quantile", "measurements": [ { "model": "TextCortex/laya-cybersec", "checkpoint": "R2a", "subset": "single_window", "hardware": "Apple MPS (local Mac GPU)", "unit": "complete single-window input", "scope": "All 279 one-window inputs from the saved 1042-input run; sequential batch-one Laya API scoring, including encoding; no dedicated all-shape warmup. Excludes model loading and PDF extraction.", "source_sha256": "048522ef775ca1402dd37314cb3bb06800ec8e38829d118ab477d7b564b44f9b", "observations": 279, "p50_ms": 95.3577909967862, "p95_ms": 148.5410204855725 }, { "model": "TextCortex/laya-cybersec", "checkpoint": "R2a", "subset": "all_inputs", "hardware": "Apple MPS (local Mac GPU)", "unit": "complete saved input, including all windows", "scope": "All 1042 saved inputs: 723 clean PDF texts, 107 attack excerpts and 212 skills; 1500-character windows with 200-character overlap, scored sequentially. Excludes model loading and PDF extraction.", "source_sha256": "048522ef775ca1402dd37314cb3bb06800ec8e38829d118ab477d7b564b44f9b", "observations": 1042, "p50_ms": 730.2949790027924, "p95_ms": 4570.080316357779 }, { "model": "jev-latest", "subset": "pdf_chunk_requests", "hardware": "Hosted API", "unit": "successful chunk request", "scope": "10533 successful requests for 830 saved PDF inputs; includes network and provider time, excludes prior failed attempts and retry backoff. Concurrent request harness; not complete-document wall time. Provider revision unavailable.", "source_sha256": "4ecff2adb4f4bf57aff4cffd8fa316144d1d974d3cbe00ac2584336ca3bb4dcc", "observations": 10533, "p50_ms": 263.58416699804366, "p95_ms": 348.8895498017257 }, { "model": "TextCortex/clef-cybersecurity", "checkpoint": "validation-selected epoch 3, calibrated", "subset": "length_rank_sample", "hardware": "NVIDIA B200", "unit": "complete saved input, including all windows", "scope": "Complete saved text tokenization and model scoring; excludes loading, PDF extraction, network and queue time. All measured shapes warmed; batch one, accelerated FLA/causal-conv1d runtime. 64 uniformly spaced ranks by character length; independent of labels and scores", "documents": 64, "repetitions": 2, "peak_allocated_gib": 19.843493461608887, "source_sha256": "ced52ccc1ad8ef9c5a6342fa70adf37d3d28bb56151e8054f1125105355d19a8", "observations": 128, "p50_ms": 40.00461706891656, "p95_ms": 510.47315176110715 } ], "privacy": "Aggregate values only; no customer text, identifiers or individual measurements." }