| {"schema": 2, "epoch": 87727, "nonce": "d2e3b073ce96b429", "hotkey": "5FTZeWt4a9qGrMr89s7vZ47V1c3yY53ZTpRnqamWVtJZ72SH", "source_hash": "24837b9ae6895829747c5eb448673693fedbeb2e3e62a5ca170051a512053fc0", "weights_hash": "7870dc30c4bcf7089a89aebd25c7926d2b875424ed6cf65a30cbaf9de38c369c", "model_id": "router", "total_cost_usd": 0.08664, "n_calls": 6, "call_log_hash": "156dd58bb5d13d826e6f1d684255e46c6e19108d7d43c898e8891caad1c6de95", "measurement": "1449fadb4821cadef93f7eecc8c3b040e2cd244e01a2607ea531e5f7055c38d8", "confined": true, "latency_s": 68.635, "tokens_in": 930, "tokens_out": 11989, "results": [{"benchmark": "mmlu", "task_id": "mmlu-2348", "answer": "B", "cost_usd": 1.22e-05, "chosen_rung": 4, "rungs_used": [4], "distribution": [0.006476, 0.006476, 0.006476, 0.006476, 0.961143, 0.006476, 0.006476]}, {"benchmark": "mmlu", "task_id": "mmlu-7296", "answer": "A", "cost_usd": 3.39e-05, "chosen_rung": 4, "rungs_used": [4], "distribution": [0.006476, 0.006476, 0.006476, 0.006476, 0.961143, 0.006476, 0.006476]}, {"benchmark": "math", "task_id": "gsm8k-963", "answer": "Let Stan\u2019s number of Pok\u00e9mon be \\(S\\).\n\n- Alex caught \\(S+5\\).\n- Adelwolfe caught \\(D\\).\n- Stan caught 13 less than 4 times Adelwolfe\u2019s amount:\n \\[\n S=4D-13\n \\]\n- Together:\n \\[\n (S+5)+S+D=339\n \\]\n \\[\n 2S+D=334\n \\]\n So:\n \\[\n D=334-2S\n \\]\n\nSubstitute into \\(S=4D-13\\):\n\n\\[\nS=4(334-2S)-13\n\\]\n\n\\[\nS=1323-8S\n\\]\n\n\\[\n9S=1323\n\\]\n\n\\[\nS=147\n\\]\n\n147", "cost_usd": 0.0001832, "chosen_rung": 4, "rungs_used": [4], "distribution": [0.006476, 0.006476, 0.006476, 0.006476, 0.961143, 0.006476, 0.006476]}, {"benchmark": "math", "task_id": "gsm8k-879", "answer": "Hair: $400 \nManicure: \\( \\frac14 \\times 400 = 100\\) \nPedicure: \\( \\frac34 \\times 100 = 75\\) \nTotal: \\(400 + 100 + 75 = 575\\)\n\n575", "cost_usd": 7.440000000000002e-05, "chosen_rung": 4, "rungs_used": [4], "distribution": [0.006476, 0.006476, 0.006476, 0.006476, 0.961143, 0.006476, 0.006476]}, {"benchmark": "code", "task_id": "lcb-abc398_a", "answer": "n = int(input())\nif n % 2:\n ans = \"-\" * (n // 2) + \"=\" + \"-\" * (n // 2)\nelse:\n ans = \"-\" * (n // 2 - 1) + \"==\" + \"-\" * (n // 2 - 1)\nprint(ans)", "cost_usd": 9.229999999999997e-05, "chosen_rung": 4, "rungs_used": [4], "distribution": [0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0]}, {"benchmark": "code", "task_id": "lcb-arc191_a", "answer": "import sys\n\ndef solve():\n input_data = sys.stdin.read().split()\n if not input_data:\n return\n N = int(input_data[0])\n M = int(input_data[1])\n S = input_data[2]\n T = input_data[3]\n\n t_last = T[-1]\n \n counts = [0] * 10\n for ch in T[:-1]:\n counts[ord(ch) - 48] += 1\n\n counts_ideal = list(counts)\n S_ideal = []\n used_from_T = []\n\n for ch in S:\n val = ord(ch) - 48\n best_d = -1\n for d in range(9, val, -1):\n if counts_ideal[d] > 0:\n best_d = d\n break\n if best_d != -1:\n S_ideal.append(chr(best_d + 48))\n used_from_T.append(best_d)\n counts_ideal[best_d] -= 1\n else:\n S_ideal.append(ch)\n used_from_T.append(None)\n\n target_val = ord(t_last) - 48\n\n k_opt = -1\n # Check for >\n for i in range(N):\n if target_val > ord(S_ideal[i]) - 48:\n k_opt = i\n break\n\n # If not found, check for ==\n if k_opt == -1:\n for i in range(N):\n if target_val == ord(S_ideal[i]) - 48:\n k_opt = i\n break\n\n # If still not found, k_opt = N - 1\n if k_opt == -1:\n k_opt = N - 1\n\n ans = []\n counts_ans = list(counts)\n\n for i in range(k_opt):\n ans.append(S_ideal[i])\n u = used_from_T[i]\n if u is not None:\n counts_ans[u] -= 1\n\n ans.append(t_last)\n\n for i in range(k_opt + 1, N):\n val = ord(S[i]) - 48\n best_d = -1\n for d in range(9, val, -1):\n if counts_ans[d] > 0:\n best_d = d\n break\n if best_d != -1:\n ans.append(chr(best_d + 48))\n counts_ans[best_d] -= 1\n else:\n ans.append(S[i])\n\n print(\"\".join(ans))\n\nif __name__ == '__main__':\n solve()", "cost_usd": 0.086244, "chosen_rung": 5, "rungs_used": [5], "distribution": [0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0]}], "quote": {"measurement": "1449fadb4821cadef93f7eecc8c3b040e2cd244e01a2607ea531e5f7055c38d8", "report_data": "7215d9fe3c6b3056c88cc198f29b8daad6999464189fd7ce96e08bce1e512bed", "platform_sig": 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