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piq40_logic_symmetric × Gemma 2 9B IT ✓ PASS

BENCHMARK QUESTION

Question ID

piq40_logic_symmetric

Prompt

In each row, the middle number is the square of the difference between the two edge numbers. If a row is 5, ?, 5, what is missing?

Options

—

GOLD / BENCHMARK TRUTH

Raw expected value

Evaluation rule type

normalized_exact

Raw evaluation rule

{
  "expected": 0,
  "type": "normalized_exact"
}

CANDIDATE / MODEL OBSERVATION

Model display name

Gemma 2 9B IT

Model ID

gemma2-9b-it

Raw model response

Execution status

success

Structured output

—

Model configuration

{
  "adapter": "transformers_local",
  "base_url": null,
  "device": "cuda",
  "dtype": "auto",
  "extra_headers": {},
  "generation": {
    "do_sample": false
  },
  "id": "gemma2-9b-it",
  "local_files_only": true,
  "max_new_tokens": 32,
  "model": "[local-model-path-redacted]/gemma2-9b-it",
  "quantization_method": null,
  "secret_env": null,
  "supports_json_mode": false,
  "timeout": 60
}

EVALUATION RESULT

Result

PASS

Stored evaluation status

passed

Score

1.0

gate_status

pass

conclusive

true

evaluator_name

pegasus.normalized_exact

evaluator_version

rule_type

normalized_exact

Reason

deterministic rule satisfied

Evaluator error

—

GRADER EVIDENCE

evaluation.evidence

{
  "actual_normalized": "0",
  "expected_normalized": "0"
}

EXECUTION EVIDENCE

effective_candidate_prompt

In each row, the middle number is the square of the difference between the two edge numbers. If a row is 5, ?, 5, what is missing?

Return only the final answer. Do not include explanation or reasoning.

Return only the final answer. Do not include explanation.

benchmark_prompt

In each row, the middle number is the square of the difference between the two edge numbers. If a row is 5, ?, 5, what is missing?

latency_ms

70.82319899927825

usage

{
  "input_tokens": 70,
  "output_tokens": 3
}

provider_metadata

{
  "adapter": "transformers_local",
  "cuda_version": "12.8",
  "device": "cuda",
  "dtype": "auto",
  "generation_latency_ms": 70.46952300879639,
  "gpu_compute_capability": [
    12,
    0
  ],
  "gpu_name": "NVIDIA GeForce RTX 5090",
  "model": "[local-model-path-redacted]/gemma2-9b-it",
  "model_load_ms": 3646.1853710061405,
  "peak_cuda_memory_allocated_bytes": 18541714432,
  "provider": "transformers_local",
  "torch_version": "2.9.0+cu128",
  "transformers_version": "4.51.3"
}

timestamp

2026-08-25T18:16:47.029949+00:00

response_id

d78a9528eca04f699c190dc07f319b18

run_id

a76b48f155d1417ea42cb8c6269bb4ba

Execution error

—

Run artifact directory

runs/pattern-iq/gemma-2-9b-it

Raw stored response

{
  "benchmark_prompt": "In each row, the middle number is the square of the difference between the two edge numbers. If a row is 5, ?, 5, what is missing?",
  "effective_candidate_prompt": "In each row, the middle number is the square of the difference between the two edge numbers. If a row is 5, ?, 5, what is missing?\n\nReturn only the final answer. Do not include explanation or reasoning.\n\nReturn only the final answer. Do not include explanation.",
  "error": null,
  "execution_status": "success",
  "latency_ms": 70.82319899927825,
  "model_id": "gemma2-9b-it",
  "provider_metadata": {
    "adapter": "transformers_local",
    "cuda_version": "12.8",
    "device": "cuda",
    "dtype": "auto",
    "generation_latency_ms": 70.46952300879639,
    "gpu_compute_capability": [
      12,
      0
    ],
    "gpu_name": "NVIDIA GeForce RTX 5090",
    "model": "[local-model-path-redacted]/gemma2-9b-it",
    "model_load_ms": 3646.1853710061405,
    "peak_cuda_memory_allocated_bytes": 18541714432,
    "provider": "transformers_local",
    "torch_version": "2.9.0+cu128",
    "transformers_version": "4.51.3"
  },
  "question_id": "piq40_logic_symmetric",
  "response_id": "d78a9528eca04f699c190dc07f319b18",
  "run_id": "a76b48f155d1417ea42cb8c6269bb4ba",
  "structured_output": null,
  "text": "0",
  "timestamp": "2026-08-25T18:16:47.029949+00:00",
  "usage": {
    "input_tokens": 70,
    "output_tokens": 3
  }
}

Raw stored evaluation

{
  "conclusive": true,
  "error": null,
  "evaluator_name": "pegasus.normalized_exact",
  "evaluator_version": "1",
  "evidence": {
    "actual_normalized": "0",
    "expected_normalized": "0"
  },
  "gate_status": "pass",
  "reason": "deterministic rule satisfied",
  "response_id": "d78a9528eca04f699c190dc07f319b18",
  "rule_type": "normalized_exact",
  "score": 1.0,
  "status": "passed"
}