{"event": "preflight", "before": {"native": false, "qwen4b": true, "ollama": true}, "context": 32768, "output_limit": 256, "note": "Installed quantizations and draft settings differ; not an engine-only comparison."}
{"event": "startup", "runtime": "native", "ready_s": 6.0203687970060855}
{"event": "prompts", "values": {"code": "<|im_start|>user\nImplement a Python function dedupe(items, key) preserving first occurrence order. Return only code with type hints, a short docstring, and three assertions covering empty input, duplicate IDs and stable order. Do not explain.<|im_end|>\n<|im_start|>assistant\n<think>\n\n</think>\n\n", "intel": "<|im_start|>user\nReturn JSON only with keys summary, facts, uncertainties, next_actions. Evidence: Acme reported revenue of 12 million versus 10 million last year. Operating expense rose from 7 to 9 million. Cash is 4 million. The CEO expects growth next year but supplied no forecast. Distinguish reported facts from predictions and calculate revenue growth.<|im_end|>\n<|im_start|>assistant\n<think>\n\n</think>\n\n", "plan_code": "<|im_start|>user\nContext note 0: requests must validate input, preserve order, avoid shared mutable state, and handle missing keys explicitly.\nContext note 1: requests must validate input, preserve order, avoid shared mutable state, and handle missing keys explicitly.\nContext note 2: requests must validate input, preserve order, avoid shared mutable state, and handle missing keys explicitly.\nContext note 3: requests must validate input, preserve order, avoid shared mutable state, and handle missing keys explicitly.\nContext note 4: requests must validate input, preserve order, avoid shared mutable state, and handle missing keys explicitly.\nContext note 5: requests must validate input, preserve order, avoid shared mutable state, and handle missing keys explicitly.\nContext note 6: requests must validate input, preserve order, avoid shared mutable state, and handle missing keys explicitly.\nContext note 7: requests must validate input, preserve order, avoid shared mutable state, and handle missing keys explicitly.\nContext note 8: requests must validate input, preserve order, avoid shared mutable state, and handle missing keys explicitly.\nContext note 9: requests must validate input, preserve order, avoid shared mutable state, and handle missing keys explicitly.\nContext note 10: requests must validate input, preserve order, avoid shared mutable state, and handle missing keys explicitly.\nContext note 11: requests must validate input, preserve order, avoid shared mutable state, and handle missing keys explicitly.\nContext note 12: requests must validate input, preserve order, avoid shared mutable state, and handle missing keys explicitly.\nContext note 13: requests must validate input, preserve order, avoid shared mutable state, and handle missing keys explicitly.\nContext note 14: requests must validate input, preserve order, avoid shared mutable state, and handle missing keys explicitly.\nContext note 15: requests must validate input, preserve order, avoid shared mutable state, and handle missing keys explicitly.\nContext note 16: requests must validate input, preserve order, avoid shared mutable state, and handle missing keys explicitly.\nContext note 17: requests must validate input, preserve order, avoid shared mutable state, and handle missing keys explicitly.\nContext note 18: requests must validate input, preserve order, avoid shared mutable state, and handle missing keys explicitly.\nContext note 19: requests must validate input, preserve order, avoid shared mutable state, and handle missing keys explicitly.\nContext note 20: requests must validate input, preserve order, avoid shared mutable state, and handle missing keys explicitly.\nContext note 21: requests must validate input, preserve order, avoid shared mutable state, and handle missing keys explicitly.\nContext note 22: requests must validate input, preserve order, avoid shared mutable state, and handle missing keys explicitly.\nContext note 23: requests must validate input, preserve order, avoid shared mutable state, and handle missing keys explicitly.\nContext note 24: requests must validate input, preserve order, avoid shared mutable state, and handle missing keys explicitly.\nContext note 25: requests must validate input, preserve order, avoid shared mutable state, and handle missing keys explicitly.\nContext note 26: requests must validate input, preserve order, avoid shared mutable state, and handle missing keys explicitly.\nContext note 27: requests must validate input, preserve order, avoid shared mutable state, and handle missing keys explicitly.\nContext note 28: requests must validate input, preserve order, avoid shared mutable state, and handle missing keys explicitly.\nContext note 29: requests must validate input, preserve order, avoid shared mutable state, and handle missing keys explicitly.\nContext note 30: requests must validate input, preserve order, avoid shared mutable state, and handle missing keys explicitly.\nContext note 31: requests must validate input, preserve order, avoid shared mutable state, and handle missing keys explicitly.\nContext note 32: requests must validate input, preserve order, avoid shared mutable state, and handle missing keys explicitly.\nContext note 33: requests must validate input, preserve order, avoid shared mutable state, and handle missing keys explicitly.\nContext note 34: requests must validate input, preserve order, avoid shared mutable state, and handle missing keys explicitly.\nContext note 35: requests must validate input, preserve order, avoid shared mutable state, and handle missing keys explicitly.\nContext note 36: requests must validate input, preserve order, avoid shared mutable state, and handle missing keys explicitly.\nContext note 37: requests must validate input, preserve order, avoid shared mutable state, and handle missing keys explicitly.\nContext note 38: requests must validate input, preserve order, avoid shared mutable state, and handle missing keys explicitly.\nContext note 39: requests must validate input, preserve order, avoid shared mutable state, and handle missing keys explicitly.\nImplement this approved plan in Python: accept records with id and value; reject missing id; merge duplicates keeping the last value but first-seen id order; return a new list without changing inputs. Return only the function and three assertions.<|im_end|>\n<|im_start|>assistant\n<think>\n\n</think>\n\n"}}
{"event": "sample", "runtime": "native", "case": "first_request", "repeat": 0, "output_limit": 32, "prompt_sha256": "dec552d8e2c12251ffa18557eb5650bf99230db9bc7cef98cb8e9a0bafcc4627", "ttft_s": 0.991350402997341, "elapsed_s": 3.4895737260085298, "output_tokens": 32, "decode_tps": 12.41012169525465, "wall_decode_tps": 12.408818584975304, "evaluated_prompt_tokens": 24, "prefill_tps": 24.235178168951503, "timing": {"cache_n": 0, "prompt_n": 24, "prompt_ms": 990.296, "prompt_per_token_ms": 41.26233333333334, "prompt_per_second": 24.235178168951506, "predicted_n": 32, "predicted_ms": 2497.961, "predicted_per_token_ms": 80.57938709677418, "predicted_per_second": 12.41012169525465, "draft_n": 23, "draft_n_accepted": 23}, "output": "1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 1"}
{"event": "sample", "runtime": "native", "case": "code", "repeat": 0, "output_limit": 256, "prompt_sha256": "d41635ab24b1bed388eb23aae7a167210287987a6538089181fed776318b67ac", "ttft_s": 1.3450053429987747, "elapsed_s": 18.44030380899494, "output_tokens": 205, "decode_tps": 11.93331243833724, "wall_decode_tps": 11.933105491300509, "evaluated_prompt_tokens": 56, "prefill_tps": 46.26497105547748, "timing": {"cache_n": 0, "prompt_n": 56, "prompt_ms": 1210.419, "prompt_per_token_ms": 21.614625, "prompt_per_second": 46.26497105547748, "predicted_n": 205, "predicted_ms": 17095.002, "predicted_per_token_ms": 83.7990294117647, "predicted_per_second": 11.93331243833724, "draft_n": 162, "draft_n_accepted": 150}, "output": "```python\nfrom typing import Any, Callable, Iterable, List\n\ndef dedupe(items: Iterable[Any], key: Callable[[Any], Any]) -> List[Any]:\n    \"\"\"Deduplicate items preserving first occurrence order.\"\"\"\n    seen: set = set()\n    result: List[Any] = []\n    for item in items:\n        k = key(item)\n        if k not in seen:\n            seen.add(k)\n            result.append(item)\n    return result\n\nassert dedupe([], lambda x: x) == []\nassert dedupe([1, 2, 1, 3, 2], lambda x: x) == [1, 2, 3]\nassert dedupe([{\"id\": 1}, {\"id\": 2}, {\"id\": 1}, {\"id\": 3}], lambda x: x[\"id\"]) == [{\"id\": 1}, {\"id\": 2}, {\"id\": 3}]\n```"}
{"event": "sample", "runtime": "native", "case": "code", "repeat": 1, "output_limit": 256, "prompt_sha256": "d41635ab24b1bed388eb23aae7a167210287987a6538089181fed776318b67ac", "ttft_s": 0.555447208986152, "elapsed_s": 17.646483813994564, "output_tokens": 205, "decode_tps": 11.936328115149054, "wall_decode_tps": 11.936081158483926, "evaluated_prompt_tokens": 4, "prefill_tps": 9.688678536912654, "timing": {"cache_n": 52, "prompt_n": 4, "prompt_ms": 412.853, "prompt_per_token_ms": 103.21325, "prompt_per_second": 9.688678536912654, "predicted_n": 205, "predicted_ms": 17090.683, "predicted_per_token_ms": 83.77785784313726, "predicted_per_second": 11.936328115149054, "draft_n": 162, "draft_n_accepted": 150}, "output": "```python\nfrom typing import Any, Callable, Iterable, List\n\ndef dedupe(items: Iterable[Any], key: Callable[[Any], Any]) -> List[Any]:\n    \"\"\"Deduplicate items preserving first occurrence order.\"\"\"\n    seen: set = set()\n    result: List[Any] = []\n    for item in items:\n        k = key(item)\n        if k not in seen:\n            seen.add(k)\n            result.append(item)\n    return result\n\nassert dedupe([], lambda x: x) == []\nassert dedupe([1, 2, 1, 3, 2], lambda x: x) == [1, 2, 3]\nassert dedupe([{\"id\": 1}, {\"id\": 2}, {\"id\": 1}, {\"id\": 3}], lambda x: x[\"id\"]) == [{\"id\": 1}, {\"id\": 2}, {\"id\": 3}]\n```"}
{"event": "sample", "runtime": "native", "case": "intel", "repeat": 0, "output_limit": 256, "prompt_sha256": "db605caba9222a3b2ea796aaff934f46b1892ac8de322d56bf20c664e37aca05", "ttft_s": 1.9878481539926725, "elapsed_s": 26.278709114994854, "output_tokens": 256, "decode_tps": 10.497851336839615, "wall_decode_tps": 10.497775291266553, "evaluated_prompt_tokens": 84, "prefill_tps": 42.296157696188715, "timing": {"cache_n": 0, "prompt_n": 84, "prompt_ms": 1985.996, "prompt_per_token_ms": 23.642809523809525, "prompt_per_second": 42.296157696188715, "predicted_n": 256, "predicted_ms": 24290.685, "predicted_per_token_ms": 95.25758823529412, "predicted_per_second": 10.497851336839615, "draft_n": 228, "draft_n_accepted": 178}, "output": "{\n  \"summary\": \"Acme experienced 20% revenue growth year-over-year, rising from 10 million to 12 million, while operating expenses increased by 28.6% from 7 million to 9 million. The company currently holds 4 million in cash. The CEO anticipates future growth but has not provided specific financial forecasts.\",\n  \"facts\": [\n    \"Current year revenue is 12 million.\",\n    \"Previous year revenue was 10 million.\",\n    \"Current year operating expense is 9 million.\",\n    \"Previous year operating expense was 7 million.\",\n    \"Current cash balance is 4 million.\",\n    \"Revenue growth rate is 20%.\"\n  ],\n  \"uncertainties\": [\n    \"The CEO's expectation of growth next year is a prediction without a supplied forecast, making the magnitude and likelihood of future growth uncertain.\"\n  ],\n  \"next_actions\": [\n    \"Request a detailed financial forecast from the CEO to quantify expected growth.\",\n    \"Analyze the impact of the higher operating expense growth rate (28.6%) compared to revenue growth (20%) on future margins.\"\n  ]\n}"}
{"event": "sample", "runtime": "native", "case": "intel", "repeat": 1, "output_limit": 256, "prompt_sha256": "db605caba9222a3b2ea796aaff934f46b1892ac8de322d56bf20c664e37aca05", "ttft_s": 0.5614852380094817, "elapsed_s": 24.848657882001135, "output_tokens": 256, "decode_tps": 10.499485648726573, "wall_decode_tps": 10.499369512370302, "evaluated_prompt_tokens": 4, "prefill_tps": 9.644875677552516, "timing": {"cache_n": 80, "prompt_n": 4, "prompt_ms": 414.728, "prompt_per_token_ms": 103.682, "prompt_per_second": 9.644875677552516, "predicted_n": 256, "predicted_ms": 24286.904, "predicted_per_token_ms": 95.24276078431372, "predicted_per_second": 10.499485648726573, "draft_n": 228, "draft_n_accepted": 178}, "output": "{\n  \"summary\": \"Acme experienced 20% revenue growth year-over-year, rising from 10 million to 12 million, while operating expenses increased by 28.6% from 7 million to 9 million. The company currently holds 4 million in cash. The CEO anticipates future growth but has not provided specific financial forecasts.\",\n  \"facts\": [\n    \"Current year revenue is 12 million.\",\n    \"Previous year revenue was 10 million.\",\n    \"Current year operating expense is 9 million.\",\n    \"Previous year operating expense was 7 million.\",\n    \"Current cash balance is 4 million.\",\n    \"Revenue growth rate is 20%.\"\n  ],\n  \"uncertainties\": [\n    \"The CEO's expectation of growth next year is a prediction without a supplied forecast, making the magnitude and likelihood of future growth uncertain.\"\n  ],\n  \"next_actions\": [\n    \"Request a detailed financial forecast from the CEO to quantify expected growth.\",\n    \"Analyze the impact of the higher operating expense growth rate (28.6%) compared to revenue growth (20%) on future margins.\"\n  ]\n}"}
{"event": "sample", "runtime": "native", "case": "plan_code", "repeat": 0, "output_limit": 256, "prompt_sha256": "ace5e2e4dcdf19dd754c043e1a4f386609d52d51202b432fa36135a1340a1b63", "ttft_s": 14.122856924004736, "elapsed_s": 38.64015711299726, "output_tokens": 256, "decode_tps": 10.400916585872618, "wall_decode_tps": 10.400818933337806, "evaluated_prompt_tokens": 1089, "prefill_tps": 77.12516479395576, "timing": {"cache_n": 0, "prompt_n": 1089, "prompt_ms": 14119.905, "prompt_per_token_ms": 12.965936639118459, "prompt_per_second": 77.12516479395576, "predicted_n": 256, "predicted_ms": 24517.07, "predicted_per_token_ms": 96.14537254901961, "predicted_per_second": 10.400916585872618, "draft_n": 228, "draft_n_accepted": 178}, "output": "```python\ndef merge_records(records):\n    \"\"\"\n    Accept records with id and value; reject missing id; merge duplicates keeping the last value but first-seen id order; return a new list without changing inputs.\n    \"\"\"\n    if not isinstance(records, list):\n        raise TypeError(\"Input must be a list\")\n    \n    # Validate each record\n    for i, record in enumerate(records):\n        if not isinstance(record, dict):\n            raise TypeError(f\"Record at index {i} must be a dict\")\n        if 'id' not in record:\n            raise ValueError(f\"Record at index {i} is missing 'id'\")\n    \n    # Use a dict to track first-seen order and last value\n    # Key: id, Value: (first_seen_index, last_value)\n    seen = {}\n    order = []  # list of ids in first-seen order\n    \n    for record in records:\n        rid = record['id']\n        value = record.get('value')  # value may be missing, that's okay per spec (only id is required)\n        \n        if rid not in seen:\n            seen[rid] = value\n            order.append("}
{"event": "sample", "runtime": "native", "case": "plan_code", "repeat": 1, "output_limit": 256, "prompt_sha256": "ace5e2e4dcdf19dd754c043e1a4f386609d52d51202b432fa36135a1340a1b63", "ttft_s": 0.43123342099715956, "elapsed_s": 24.93830334598897, "output_tokens": 256, "decode_tps": 10.405247247852907, "wall_decode_tps": 10.405160665084495, "evaluated_prompt_tokens": 4, "prefill_tps": 9.33770026449036, "timing": {"cache_n": 1085, "prompt_n": 4, "prompt_ms": 428.371, "prompt_per_token_ms": 107.09275, "prompt_per_second": 9.33770026449036, "predicted_n": 256, "predicted_ms": 24506.866, "predicted_per_token_ms": 96.10535686274511, "predicted_per_second": 10.405247247852907, "draft_n": 228, "draft_n_accepted": 178}, "output": "```python\ndef merge_records(records):\n    \"\"\"\n    Accept records with id and value; reject missing id; merge duplicates keeping the last value but first-seen id order; return a new list without changing inputs.\n    \"\"\"\n    if not isinstance(records, list):\n        raise TypeError(\"Input must be a list\")\n    \n    # Validate each record\n    for i, record in enumerate(records):\n        if not isinstance(record, dict):\n            raise TypeError(f\"Record at index {i} must be a dict\")\n        if 'id' not in record:\n            raise ValueError(f\"Record at index {i} is missing 'id'\")\n    \n    # Use a dict to track first-seen order and last value\n    # Key: id, Value: (first_seen_index, last_value)\n    seen = {}\n    order = []  # list of ids in first-seen order\n    \n    for record in records:\n        rid = record['id']\n        value = record.get('value')  # value may be missing, that's okay per spec (only id is required)\n        \n        if rid not in seen:\n            seen[rid] = value\n            order.append("}
{"event": "startup", "runtime": "ollama_daemon", "ready_s": 2.0079784970002947}
{"event": "sample", "runtime": "ollama", "case": "first_request", "repeat": 0, "output_limit": 32, "prompt_sha256": "dec552d8e2c12251ffa18557eb5650bf99230db9bc7cef98cb8e9a0bafcc4627", "ttft_s": 6.386816208003438, "elapsed_s": 8.692689856005018, "output_tokens": 32, "decode_tps": 13.875820082647854, "wall_decode_tps": 13.443928303212372, "evaluated_prompt_tokens": 24, "prefill_tps": 24.91896146074952, "timing": {"total_duration": 8692104761, "load_duration": 5421214897, "prompt_eval_count": 24, "prompt_eval_cached_count": 0, "prompt_eval_duration": 963122000, "eval_count": 32, "eval_duration": 2306170000}, "output": "1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 1"}
{"event": "placement", "runtime": "ollama", "value": {"models": [{"name": "qwen3.8:27b", "model": "qwen3.8:27b", "size": 17536049478, "digest": "aaee06c39dcf2437cde036998d960e1fc1494b8191be7cc9657d01e509097813", "details": {"parent_model": "", "format": "gguf", "family": "qwen35", "families": ["qwen35"], "parameter_size": "27.3B", "quantization_level": "Q4_K_M"}, "expires_at": "2026-09-26T15:56:38.782110485+05:45", "size_vram": 17536049478, "context_length": 32768}]}}
{"event": "sample", "runtime": "ollama", "case": "code", "repeat": 0, "output_limit": 256, "prompt_sha256": "d41635ab24b1bed388eb23aae7a167210287987a6538089181fed776318b67ac", "ttft_s": 1.338609753001947, "elapsed_s": 18.329839904996334, "output_tokens": 210, "decode_tps": 12.35925748406009, "wall_decode_tps": 12.300463128943498, "evaluated_prompt_tokens": 56, "prefill_tps": 46.584445121028054, "timing": {"total_duration": 18329286207, "load_duration": 992430, "prompt_eval_count": 56, "prompt_eval_cached_count": 0, "prompt_eval_duration": 1202118000, "eval_count": 210, "eval_duration": 16991312000}, "output": "```python\nfrom typing import Any, Callable, Iterable, List\n\n\ndef dedupe(items: Iterable[Any], key: Callable[[Any], Any]) -> List[Any]:\n    \"\"\"Deduplicate items preserving first occurrence order based on key.\"\"\"\n    seen: set[Any] = set()\n    result: List[Any] = []\n    for item in items:\n        k = key(item)\n        if k not in seen:\n            seen.add(k)\n            result.append(item)\n    return result\n\n\nassert dedupe([], lambda x: x) == []\nassert dedupe([{\"id\": 1}, {\"id\": 2}, {\"id\": 1}, {\"id\": 3}], lambda x: x[\"id\"]) == [{\"id\": 1}, {\"id\": 2}, {\"id\": 3}]\nassert dedupe([\"a\", \"b\", \"a\", \"c\", \"b\"], lambda x: x) == [\"a\", \"b\", \"c\"]\n```"}
{"event": "sample", "runtime": "ollama", "case": "code", "repeat": 1, "output_limit": 256, "prompt_sha256": "d41635ab24b1bed388eb23aae7a167210287987a6538089181fed776318b67ac", "ttft_s": 0.5212416220019804, "elapsed_s": 17.518911243998446, "output_tokens": 210, "decode_tps": 12.354657747879715, "wall_decode_tps": 12.295803168778843, "evaluated_prompt_tokens": 56, "prefill_tps": 148.99560995077823, "timing": {"total_duration": 17518045108, "load_duration": 1493229, "prompt_eval_count": 56, "prompt_eval_cached_count": 52, "prompt_eval_duration": 375850000, "eval_count": 210, "eval_duration": 16997637999}, "output": "```python\nfrom typing import Any, Callable, Iterable, List\n\n\ndef dedupe(items: Iterable[Any], key: Callable[[Any], Any]) -> List[Any]:\n    \"\"\"Deduplicate items preserving first occurrence order based on key.\"\"\"\n    seen: set[Any] = set()\n    result: List[Any] = []\n    for item in items:\n        k = key(item)\n        if k not in seen:\n            seen.add(k)\n            result.append(item)\n    return result\n\n\nassert dedupe([], lambda x: x) == []\nassert dedupe([{\"id\": 1}, {\"id\": 2}, {\"id\": 1}, {\"id\": 3}], lambda x: x[\"id\"]) == [{\"id\": 1}, {\"id\": 2}, {\"id\": 3}]\nassert dedupe([\"a\", \"b\", \"a\", \"c\", \"b\"], lambda x: x) == [\"a\", \"b\", \"c\"]\n```"}
{"event": "sample", "runtime": "ollama", "case": "intel", "repeat": 0, "output_limit": 256, "prompt_sha256": "db605caba9222a3b2ea796aaff934f46b1892ac8de322d56bf20c664e37aca05", "ttft_s": 1.981836552004097, "elapsed_s": 26.25346060200536, "output_tokens": 254, "decode_tps": 10.464902899297229, "wall_decode_tps": 10.423694742420288, "evaluated_prompt_tokens": 84, "prefill_tps": 42.45853090450318, "timing": {"total_duration": 26252771424, "load_duration": 1118995, "prompt_eval_count": 84, "prompt_eval_cached_count": 0, "prompt_eval_duration": 1978401000, "eval_count": 254, "eval_duration": 24271606000}, "output": "{\n  \"summary\": \"Acme reported a 20% year-over-year revenue increase to 12 million, while operating expenses rose by 28.6% to 9 million. The company holds 4 million in cash. The CEO expressed expectations for future growth but provided no specific financial forecasts.\",\n  \"facts\": [\n    \"Current year revenue is 12 million.\",\n    \"Previous year revenue was 10 million.\",\n    \"Current year operating expense is 9 million.\",\n    \"Previous year operating expense was 7 million.\",\n    \"Current cash balance is 4 million.\",\n    \"Revenue growth rate is 20%.\"\n  ],\n  \"uncertainties\": [\n    \"The CEO's expectation of growth next year is a prediction without supporting data.\",\n    \"No specific financial forecast was supplied for the next year.\"\n  ],\n  \"next_actions\": [\n    \"Request a detailed financial forecast from the CEO to quantify expected growth.\",\n    \"Analyze the impact of the higher operating expense ratio on future profitability.\",\n    \"Monitor cash flow to ensure the 4 million cash reserve supports the increased operational costs.\"\n  ]\n}"}
{"event": "sample", "runtime": "ollama", "case": "intel", "repeat": 1, "output_limit": 256, "prompt_sha256": "db605caba9222a3b2ea796aaff934f46b1892ac8de322d56bf20c664e37aca05", "ttft_s": 0.5269240829948103, "elapsed_s": 24.791163296991726, "output_tokens": 254, "decode_tps": 10.468126368583883, "wall_decode_tps": 10.426867200272902, "evaluated_prompt_tokens": 84, "prefill_tps": 222.91514628806473, "timing": {"total_duration": 24790447840, "load_duration": 1143050, "prompt_eval_count": 84, "prompt_eval_cached_count": 80, "prompt_eval_duration": 376825000, "eval_count": 254, "eval_duration": 24264132000}, "output": "{\n  \"summary\": \"Acme reported a 20% year-over-year revenue increase to 12 million, while operating expenses rose by 28.6% to 9 million. The company holds 4 million in cash. The CEO expressed expectations for future growth but provided no specific financial forecasts.\",\n  \"facts\": [\n    \"Current year revenue is 12 million.\",\n    \"Previous year revenue was 10 million.\",\n    \"Current year operating expense is 9 million.\",\n    \"Previous year operating expense was 7 million.\",\n    \"Current cash balance is 4 million.\",\n    \"Revenue growth rate is 20%.\"\n  ],\n  \"uncertainties\": [\n    \"The CEO's expectation of growth next year is a prediction without supporting data.\",\n    \"No specific financial forecast was supplied for the next year.\"\n  ],\n  \"next_actions\": [\n    \"Request a detailed financial forecast from the CEO to quantify expected growth.\",\n    \"Analyze the impact of the higher operating expense ratio on future profitability.\",\n    \"Monitor cash flow to ensure the 4 million cash reserve supports the increased operational costs.\"\n  ]\n}"}
{"event": "sample", "runtime": "ollama", "case": "plan_code", "repeat": 0, "output_limit": 256, "prompt_sha256": "ace5e2e4dcdf19dd754c043e1a4f386609d52d51202b432fa36135a1340a1b63", "ttft_s": 15.554881431991816, "elapsed_s": 38.57908819700242, "output_tokens": 256, "decode_tps": 11.118768777037936, "wall_decode_tps": 11.075300122283391, "evaluated_prompt_tokens": 1089, "prefill_tps": 70.03516742938973, "timing": {"total_duration": 38578399168, "load_duration": 1308106, "prompt_eval_count": 1089, "prompt_eval_cached_count": 0, "prompt_eval_duration": 15549331000, "eval_count": 256, "eval_duration": 23024132000}, "output": "```python\ndef merge_records(records):\n    \"\"\"\n    Accept records with id and value; reject missing id;\n    merge duplicates keeping the last value but first-seen id order;\n    return a new list without changing inputs.\n    \"\"\"\n    if not isinstance(records, list):\n        raise TypeError(\"Input must be a list\")\n    \n    # Validate each record\n    for i, record in enumerate(records):\n        if not isinstance(record, dict):\n            raise TypeError(f\"Record at index {i} must be a dict\")\n        if 'id' not in record:\n            raise ValueError(f\"Record at index {i} is missing 'id'\")\n        if 'value' not in record:\n            raise ValueError(f\"Record at index {i} is missing 'value'\")\n    \n    # Use a dict to track first-seen order and last value\n    # OrderedDict or regular dict (Python 3.7+ preserves insertion order)\n    merged = {}\n    for record in records:\n        rid = record['id']\n        # If id already exists, update value (keep last value)\n        # If not, insert (preserves first-seen order)\n"}
{"event": "sample", "runtime": "ollama", "case": "plan_code", "repeat": 1, "output_limit": 256, "prompt_sha256": "ace5e2e4dcdf19dd754c043e1a4f386609d52d51202b432fa36135a1340a1b63", "ttft_s": 0.3954597650008509, "elapsed_s": 24.098851647999254, "output_tokens": 256, "decode_tps": 10.80049059540953, "wall_decode_tps": 10.75795402019668, "evaluated_prompt_tokens": 1089, "prefill_tps": 2788.2754170891326, "timing": {"total_duration": 24097888081, "load_duration": 1159571, "prompt_eval_count": 1089, "prompt_eval_cached_count": 1085, "prompt_eval_duration": 390564000, "eval_count": 256, "eval_duration": 23702627000}, "output": "```python\ndef merge_records(records):\n    \"\"\"\n    Accept records with id and value; reject missing id; merge duplicates keeping the last value but first-seen id order; return a new list without changing inputs.\n    \"\"\"\n    if not isinstance(records, list):\n        raise TypeError(\"Input must be a list\")\n    \n    # Validate each record\n    for i, record in enumerate(records):\n        if not isinstance(record, dict):\n            raise TypeError(f\"Record at index {i} must be a dict\")\n        if 'id' not in record:\n            raise ValueError(f\"Record at index {i} is missing 'id'\")\n        if 'value' not in record:\n            raise ValueError(f\"Record at index {i} is missing 'value'\")\n    \n    # Use a dict to track first-seen order and last value\n    # We need to preserve first-seen id order, and for duplicates keep the last value\n    # Use an ordered approach: iterate through records, track seen ids in order, and update values\n    \n    # First, determine the order of first-seen ids\n    seen_ids = []\n    id_to_index = {}\n    for record in records"}
{"event": "restored", "native": false, "qwen4b": true, "ollama": true}