Policy satisfied

Every configured check passed for this paired evaluation. Independent recipient acceptance is a separate step.

What was compared

Recorded field	Baseline	Subject
ArtifactDiffers	hf://mistralai/Ministral-3-8B-Instruct-2512-BF16@f6fae9795746f63c9be8344932f01275f3c63734	derived://mistralai/Ministral-3-8B-Instruct-2512-BF16@f6fae9795746f63c9be8344932f01275f3c63734#llama.cpp-b10015-q5_k_m@sha256:b2c56b655b15577c30734b28b820d054e43df06c7712b74b9c170bff5f10f253
Model IDDiffers	mistralai/Ministral-3-8B-Instruct-2512-BF16	gguf-sha256-b2c56b655b15577c30734b28b820d054e43df06c7712b74b9c170bff5f10f253.gguf
ProviderDiffers	hf_transformers	llama_cpp

Additional recorded context (10)

Additional fields

Workflow: Runtime execution
Task: text_causal
Paired records: 400
Schedule digest: sha256:9ac24cf5e4b904197117fa8d0d9661d88fdf0dae1cc39ddfa711aa820de60fad
Dataset: TIGER-Lab/MMLU-Pro/ministral3-instruct
Dataset split: test-balanced-400
Dataset source SHA-256: c3d83209d6f36023f0a5aef5ee9be895891cc66ecc1b7196e83227558a38fade
Dataset source format: jsonl
Selected records: 400
Selection limit: Not specified

Baseline and candidate have different authenticated artifact digests; the evidence does not identify a transformation procedure.

Results and requirements

Exact-match accuracy

Scope: All paired records

Policy satisfied

All configured checks passed.

Baseline: 44.75%
Subject: 45.25%
Change: +0.5 ppPaired 95% CI: -1.12 to +2.119 pp
Observed pairs: 400

EstimatePaired 95% confidence interval Policy thresholdNo changeAllowed change region

Decision checks
Check	Observed	Required	Result
Paired lower boundThe lower bound must meet the allowed change, not just the point estimate.	-1.11994 pp	>= -2 pp	Passed
Record countThe comparison must include the configured minimum number of paired records.	400	>= 400	Passed
Interval widthThe interval must be narrow enough for the configured precision requirement.	3.23886 pp	<= 10 pp	Passed
Baseline accuracyEach side must meet the configured absolute accuracy floor.	44.75%	>= 20%	Passed
Candidate accuracyEach side must meet the configured absolute accuracy floor.	45.25%	>= 20%	Passed

Higher scores are better; the change is candidate minus baseline in percentage points.
The policy tests the interval bound, not just the observed change.
Authenticated observations are supplementary; the paired metric and policy remain the complete acceptance calculation.

Next steps

Review the decision checks and their requirements.
Run invarlock verify with your independently supplied trust profile and receipt destination to create the signed acceptance or rejection receipt.
Keep this report alongside the original immutable evidence and the separate verification receipt.

Scope and limitations

This report summarizes the evidence bundle. Rendering checks its integrity and embedded signature; independent acceptance requires verification with your own trust inputs.
Results apply to the recorded cases, metric and policy. A pass does not establish general model quality, safety or representative production performance.
The interval describes paired binary outcomes under its stated method. Population interpretation requires an appropriate sampling design.

Evidence details

Identities, methods and exact recorded values

Comparison and policy identities

Comparison: comparison-4472c601a80f319859c4bf0c505c399c
Metric: exact_match
Policy: sha256:48e929519390c41e91c5e907e7e3f3d6d0b26e5ac4345136c4f6b85244b191d9
Evidence signer: sha256:e1f2aab12ee457abad9b0c74b1b9dcd0ce0429e541c15f17b814071b7fd9abab

Paired outcome analysis

{
  "baseline_fail_subject_pass": 6,
  "baseline_pass_subject_fail": 4,
  "both_fail": 215,
  "both_pass": 175,
  "discordant_pairs": 10,
  "effect_size_confidence_interval": {
    "confidence_level": 0.95,
    "lower_pp": -1.119943249438997,
    "method": "newcombe_hybrid_score_paired_v2",
    "upper_pp": 2.118915687037841
  },
  "effect_size_pp": 0.5,
  "mcnemar_exact_two_sided_p_value": 0.75390625
}

Authenticated observations

[
  {
    "authority": "observation",
    "bindings": {
      "artifact_digests": {
        "baseline": "sha256:2bba1d6c1331980047b18d9b00da21d997dc9ca26a183434e512bfc348b2e891",
        "subject": "sha256:fa3ab58b49a8e08b4901a3f990c0d0a401ec7930bd90a632f564ff7f71f1b1a6"
      },
      "comparison_id": "comparison-4472c601a80f319859c4bf0c505c399c",
      "policy_digest": "sha256:48e929519390c41e91c5e907e7e3f3d6d0b26e5ac4345136c4f6b85244b191d9",
      "schedule_digest": "sha256:9ac24cf5e4b904197117fa8d0d9661d88fdf0dae1cc39ddfa711aa820de60fad"
    },
    "format": "invarlock/evidence-observation-v1",
    "kind": "artifact_transformation",
    "observation_id": "ministral3-8b-bf16-to-gguf-q5-k-m",
    "payload": {
      "conversion": {
        "output": {
          "byte_length": 16987563264,
          "filename": "Ministral-3-8B-Instruct-BF16.gguf",
          "sha256": "b6dc36267813cef3a367b3e23528f5e367db5713ca6f2dd1f1a40a3eb1344ada",
          "type": "BF16"
        },
        "runtime_image_digest": "sha256:b905cf3b278531333d47fc80ba5b110793f80717fc2acc526e8dd291ae8f3301",
        "tool": {
          "name": "llama.cpp/convert_hf_to_gguf.py",
          "source_commit": "12127defda4f41b7679cb2477a4b0d65ee6a0c8f",
          "source_sha256": "5ab75e394f4c71425ecce64a213dab3b8e3e9cfe0f19d0dcda4d5a4f7733da83",
          "source_tag": "b10015"
        }
      },
      "format": "invarlock/example-gguf-deployment-transformation-v1",
      "quantization": {
        "runtime_image_digest": "sha256:aa5d7b75a807e786175e9edf9927cbbc0bb3099bcc2d95fe07e56f80bbfeedb6",
        "tool": "llama-quantize",
        "type": "Q5_K_M"
      },
      "source": {
        "checkpoint_tree_sha256": "sha256:6cbddcebc289550569cc3f6a93676a8f4f605d8574b8aec8448d61594a283996",
        "repository": "mistralai/Ministral-3-8B-Instruct-2512-BF16",
        "revision": "f6fae9795746f63c9be8344932f01275f3c63734",
        "tokenizer_contract_sha256": "b9e3906504b6235b5c289fe9d3f7a86512f968dfe300771ec660080924615dbc"
      },
      "subject": {
        "byte_length": 6058747136,
        "filename": "Ministral-3-8B-Instruct-Q5_K_M.gguf",
        "sha256": "b2c56b655b15577c30734b28b820d054e43df06c7712b74b9c170bff5f10f253"
      }
    },
    "scope": "subject"
  }
]

Exact comparison data

{
  "baseline": {
    "mean_score": 0.4475
  },
  "comparison": {
    "kind": "exact_match_delta_pp",
    "minimum": -2.0,
    "value": 0.5
  },
  "comparison_id": "comparison-4472c601a80f319859c4bf0c505c399c",
  "format": "invarlock/comparison-report-v3",
  "metric": "exact_match",
  "paired_binary": {
    "baseline_fail_subject_pass": 6,
    "baseline_pass_subject_fail": 4,
    "both_fail": 215,
    "both_pass": 175,
    "discordant_pairs": 10,
    "effect_size_confidence_interval": {
      "confidence_level": 0.95,
      "lower_pp": -1.119943249438997,
      "method": "newcombe_hybrid_score_paired_v2",
      "upper_pp": 2.118915687037841
    },
    "effect_size_pp": 0.5,
    "mcnemar_exact_two_sided_p_value": 0.75390625
  },
  "policy_digest": "sha256:48e929519390c41e91c5e907e7e3f3d6d0b26e5ac4345136c4f6b85244b191d9",
  "record_count": 400,
  "sample_qualification": {
    "interval_width": {
      "maximum": 10.0,
      "observed": 3.238858936476838,
      "passed": true,
      "unit": "percentage_points"
    },
    "passed": true,
    "record_count": {
      "minimum": 400,
      "observed": 400,
      "passed": true
    }
  },
  "side_accuracy": {
    "baseline": {
      "observed": 0.4475,
      "passed": true
    },
    "minimum": 0.2,
    "passed": true,
    "subject": {
      "observed": 0.4525,
      "passed": true
    }
  },
  "subject": {
    "mean_score": 0.4525
  },
  "uncertainty": {
    "interval_mass": 0.95,
    "lower": -1.119943249438997,
    "method": "newcombe_hybrid_score_paired_v2",
    "scope": "paired_binary_outcomes",
    "upper": 2.118915687037841
  },
  "verdict": "pass"
}