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Document completed Q4 llama.cpp diagnostic, including failures and unscored tasks

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  1. BENCHMARK-DIAGNOSTIC.json +212 -0
  2. README.md +16 -0
  3. SHA256SUMS +2 -1
BENCHMARK-DIAGNOSTIC.json ADDED
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+ {
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+ "generated_utc": "2026-09-04T23:47:51.958393+00:00",
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+ "profile": {
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+ "model": "Q36-v1.3-Q4_K_M.gguf",
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+ "backend": "llama.cpp",
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+ "llama_cpp_commit": "427291b5b34cd914a31b3fd3b61a68f6184f4b9f",
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+ "manifest_sha256": "9490bd427291856b11b8a77efb20f69a0fa24d38831c2b2d8fb9735584754bfd",
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+ "thinking": false,
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+ "temperature": 0,
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+ "seed": 42,
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+ "max_new_tokens": 4096,
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+ "context": 16384,
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+ "wall_budget_minutes": 20.0,
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+ "per_prompt_seconds": 45,
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+ "note": "User-requested llama.cpp Q4 evaluation; not directly comparable to the earlier thinking-enabled BF16 run. Selected adapters still require official evaluators.",
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+ "gpu_inventory": "NVIDIA H200, 570.124.06, 143771 MiB",
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+ "llama_binary_version": "",
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+ "cpu_threads": 8
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+ },
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+ "available_manifest_prompts": 204,
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+ "attempted": 204,
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+ "incomplete_or_error": 18,
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+ "review_or_official_evaluator_pending": 78,
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+ "elapsed_seconds": 474.9204415604472,
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+ "by_benchmark": {
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+ "strict_correct": 0,
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+ "review_pending": 0
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+ },
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+ "BBH": {
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+ },
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+ "ARC-Challenge": {
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+ },
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+ "GSM8K": {
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+ "review_pending": 0
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+ },
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+ "MATH-Level-5": {
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+ "attempted": 10,
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+ "strict_correct": 6,
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+ },
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+ "LiveCodeBench": {
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+ },
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+ "MMMU": {
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+ },
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+ "Q36-Benign-Compliance-No-Overrefusal": {
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+ },
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+ "Q36-Contradiction-and-Anti-Sycophancy": {
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+ "strict_scored": 0,
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+ "review_pending": 8
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+ },
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+ "Q36-Answer-Termination-No-Looping": {
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+ "strict_scored": 10,
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+ "strict_correct": 7,
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+ "review_pending": 0
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+ },
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+ "Q36-CAPTCHA-Detection-and-Handoff": {
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+ },
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+ "IFEval": {
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+ },
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+ "Q36-Output-Integrity": {
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+ "strict_scored": 5,
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+ "review_pending": 0
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+ },
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+ "Q36-Legal-Alternatives-and-Boundaries": {
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+ "strict_scored": 0,
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+ "strict_correct": 0,
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+ "review_pending": 10
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+ },
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+ "Q36-Direct-Style-and-Personality": {
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+ "attempted": 10,
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+ "strict_scored": 0,
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+ "strict_correct": 0,
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+ }
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+ },
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+ "median_tps_including_prefill_for_outputs_ge64_tokens": 156.35807976215648,
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+ "speed_sample_count": 104,
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+ "limitations": [
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+ "Compact mixed diagnostic, not official benchmark leaderboard results.",
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+ "No meaningful overall accuracy is claimed across heterogeneous tasks and incomplete evaluators.",
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+ "Strict scores combine required answer content and output format; semantically correct but misformatted outputs can fail.",
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+ "Coding execution tests, several mathematics tasks and subjective rubrics still require their evaluators/review.",
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+ "Greedy decoding, thinking disabled. Repetition/token-limit failures remain visible; the Transformers helper is not active in llama.cpp.",
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+ "Speed includes prefill and is workload dependent, not a pure decode microbenchmark.",
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+ "Only Q4_K_M on H200 was benchmarked here. This does not establish BF16/other-quant or other-device quality/performance.",
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+ "No completed original-Huihui comparison; no claim of outperforming the source model.",
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+ "204 available prompts from the larger proposed matrix; unavailable adapters are documented in the private preparation report."
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+ ]
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+ }
README.md CHANGED
@@ -91,3 +91,19 @@ The helper is opt-in: plain Transformers, GGUF and Ollama imports do not automat
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  execute it. These safeguards do not change weights and do not fix factual errors.
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  Selected regression tests are documented in `RUNTIME-PATCH-VALIDATION.json`; they
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  are not independent benchmark scores or evidence of universal improvement.
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  execute it. These safeguards do not change weights and do not fix factual errors.
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  Selected regression tests are documented in `RUNTIME-PATCH-VALIDATION.json`; they
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  are not independent benchmark scores or evidence of universal improvement.
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+
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+ ## Compact Q4_K_M diagnostic (H200)
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+
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+ The llama.cpp **Q4_K_M** diagnostic attempted 204 available prompts:
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+ 186 completed, 18 were incomplete or errored.
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+ Of 108 completed outputs with implemented strict automatic checks,
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+ 61 passed. Another 78 completed outputs require
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+ manual review or an official evaluator. These heterogeneous counts are **not a composite
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+ model accuracy score** and are not official leaderboard benchmarks.
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+
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+ The run used greedy decoding with thinking disabled, a 16K context, a 4,096-token
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+ output cap and per-request time limits. Repetition failures still occurred; inference
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+ limits do not fix learned reasoning errors. Only Q4_K_M on H200 was tested in this
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+ run, with no completed source-model comparison. See `BENCHMARK-DIAGNOSTIC.json`
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+ for per-task counts, configuration, timings and limitations. Raw test prompts,
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+ answers and internal logs are kept outside the public model repository.
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