Grok 4.3 (Venice) on Analyze five months of AI coding-agent session logs
XGrok 4.3 (Venice) · venice-mini-agent v1.2 · cloud · 2026-10-15 · by @bobsiopener
- Cost
- $0.02
- Wall time
- 10s
- Human step-ins
- 0
- Outcome
- Pass
Compare with other models on this task →
Summary
Exact prompt
sessions.csv logs 5 months of AI coding-agent sessions. Write answers.json with exactly these keys: "total_sessions" (int), "total_prs" (int), "total_api_equiv_usd" (number rounded to 2 decimals), "busiest_month_by_sessions" (string like "2026-07"), "median_minutes" (number), "usd_per_pr_by_tool" (object tool -> total api_equiv_usd / total prs_opened for that tool, rounded to 2 decimals). Then write REPORT.md with a 5-bullet summary.
Task prompt given to the agent (headless, offline, synthetic fixture inputs): sessions.csv logs 5 months of AI coding-agent sessions. Write answers.json with exactly these keys: "total_sessions" (int), "total_prs" (int), "total_api_equiv_usd" (number rounded to 2 decimals), "busiest_month_by_sessions" (string like "2026-07"), "median_minutes" (number), "usd_per_pr_by_tool" (object tool -> total api_equiv_usd / total prs_opened for that tool, rounded to 2 decimals). Then write REPORT.md with a 5-bullet summary. Inspired by https://x.com/quinn_leng/status/2085828592127336541 (unverified; not checked with the author). This is an independent re-run on a reproducible synthetic task; it does not report or reproduce the original post's numbers. Cost is real Venice spend (paid from DIEM credit), as reported by Venice.
Success criteria: All automated rubric checks pass: total_sessions correct; total_prs correct; total_api_equiv_usd correct; busiest_month_by_sessions correct; median_minutes correct; usd_per_pr_by_tool correct; REPORT.md written.
Setup notes: Harness: venice-mini-agent v1.2 via Venice OpenAI-compatible API. Minimal OpenAI-compatible tool loop (/workspace/usecase-runner/venice_agent.py): tools list_files/read_file/write_file/run_shell in the work dir, max 25 turns, max_tokens 16000/call, temperature 0.2, Venice system prompt and web search off, $0.08 per-run cost cap. Identical for all Venice models. Cost source: Venice /api/v1/models model_spec.pricing (USD per 1M tokens), fetched 2026-10-14; cost computed from per-call usage. Paid from Bob's DIEM daily allowance. input_tokens includes cached reads; cached_tokens = cache reads; cache_write_tokens = cache writes (0 if not reported). Single run, no retries; scored automatically (7/7 checks). Runner notes: Adapted: real 5-month usage logs replaced by a seeded mock sessions.csv; deterministic answers. Single run, no retries. Same rubric/score.py as Claude runs. Web disabled.
Metrics
- Cost
- $0.02
- Wall time
- 10s
- Human step-ins
- 0
- Turns
- 5
| Model | Input tok | Output tok | Cost |
|---|---|---|---|
| XGrok 4.3 (Venice)venice/grok-4-3 | 28,245 | 794 | $0.02 |
Reproduce this run
- Use the use case prompt on the use case page.
- Same setup: Grok 4.3 (Venice) (venice/grok-4-3) via
venice-mini-agent v1.2, cloud. - It counts as a success only if it meets every success criterion: All automated rubric checks pass: total_sessions correct; total_prs correct; total_api_equiv_usd correct; busiest_month_by_sessions correct; median_minutes correct; usd_per_pr_by_tool correct; REPORT.md written.
- Log model, tokens, wall time, human step-ins and the evidence log, then submit it as a reproduction. A different model? Submit a head-to-head rerun.
How runs are scored: Methodology.
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Automated checks
Trust 80% comes from these checks (how Trust % works).
- Run date is not in the future : passed
- Model is in the dated pricing table : passed
- Cost recomputed from tokens matches : passed
- Cached tokens are consistent : passed
- Output throughput is plausible : passed
- Autonomy matches step-ins : passed
- Step-ins do not exceed turns : passed
- Retries agree with first-try result : passed
- Evidence log SHA-256 matches : passed
- Evidence log is substantial : passed
Evidence log
{"turn": 1, "response": {"id": "4b61cbec-0e69-9daa-b1a0-f2edfdb8d0ba", "object": "chat.completion", "created": 1792023621, "model": "grok-4-3", "choices": [{"index": 0, "message": {"role": "assistant", "content": null, "refusal": null, "reasoning_content": "I'm starting to analyze the sessions.csv file to extract the five-month AI coding-agent session data.\n\n[encrypted reasoning omitted, 742 chars]", "reasoning_encrypted": true, "reasoning_details": [{"type": "reasoning.encrypted", "format": "xai-responses-v1", "index": 0, "id": "rs_4b61cbec-0e69-9daa-b1a0-f2edfdb8d0ba", "data": "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"}], "tool_calls": [{"id": "call-bb5cf7be-e404-44ad-b059-35b7a464739f-0", "type": "function", "function": {"name": "list_files", "arguments": "{\"path\":\".\"}"}}]}, "finish_reason": "tool_calls", "logprobs": null}], "usage": {"prompt_tokens": 601, "completion_tokens": 147, "total_tokens": 748, "prompt_tokens_details": {"cached_tokens": 128}, "cache_read_input_tokens": 128, "completion_tokens_details": {"reasoning_tokens": 137}}, "cost": {"usd": 0, "diem": 0.00111711}, "venice_parameters": {"strip_thinking_response": false, "disable_thinking": false, "enable_e2ee": true, "enable_web_search": "off", "enable_web_scraping": false, "enable_web_citations": false, "include_search_results_in_stream": false, "include_venice_system_prompt": false, "enable_x_search": false, "web_search_citations": [], "return_search_results_as_documents": false}}}
{"turn": 1, "tool": "list_files", "args": {"path": "."}, "result": "./sessions.csv"}
{"turn": 2, "response": {"id": "e8d87967-ef1e-9dad-8eb7-a85414837bf0", "object": "chat.completion", "created": 1792023622, "model": "grok-4-3", "choices": [{"index": 0, "message": {"role": "assistant", "content": null, "refusal": null, "reasoning_content": "[encrypted reasoning omitted, 386 chars]", "reasoning_encrypted": true, "reasoning_details": [{"type": "reasoning.encrypted", "format": "xai-responses-v1", "index": 0, "id": "rs_e8d87967-ef1e-9dad-8eb7-a85414837bf0", "data": "N+YMaTblcG2oehjqHl4vR+5HmLBj5/lQ3B3zTu2qnQO5ghOo0Ul3SsQ4JO1vCPBPB0155HccsyQvNJK4TrHkBmgUL/sQbkBbitJlZ1EOPZdaRThHyv9wZW7Z6ryXD4t5QOU1zEps1+EXSM6qhtGFqOrIAKBlSuCcZGQpD/cJM9zUUHDxpRxLoe1t1we/pBwCvLQOXXtfrKK9QU6UYIJepqFGQfld9puAsaeKoXwtYNBDB8NiOWHV9JOQtRDDLzq2HlF9VU2J4G7/OZvn2ThekTXZaNQbVyuckvxLKUO++kV/RvrvaMHBpfEFq2OkgUVIap7roTo5/WBn5ysakrIXfal54QOJd1C4OSfkiAbNgKY"}], "tool_calls": [{"id": "call-8cf4e9aa-01a0-4167-95ed-68c098dd1388-1", "type": "function", "function": {"name": "read_file", "arguments": "{\"path\":\"sessions.csv\"}"}}]}, "finish_reason": "tool_calls", "logprobs": null}], "usage": {"prompt_tokens": 619, "completion_tokens": 64, "total_tokens": 683, "prompt_tokens_details": {"cached_tokens": 384}, "cache_read_input_tokens": 384, "completion_tokens_details": {"reasoning_tokens": 53}}, "cost": {"usd": 0, "diem": 0.0006031400000000001}, "venice_parameters": {"strip_thinking_response": false, "disable_thinking": false, "enable_e2ee": true, "enable_web_search": "off", "enable_web_scraping": false, "enable_web_citations": false, "include_search_results_in_stream": false, "include_venice_system_prompt": false, "enable_x_search": false, "web_search_citations": [], "return_search_results_as_documents": false}}}
{"turn": 2, "tool": "read_file", "args": {"path": "sessions.csv"}, "result": "session_id,month,tool,minutes,prs_opened,api_equiv_usd\ns0000,2026-09,codex,93,2,23.56\ns0001,2026-09,claude-code,121,0,16.24\ns0002,2026-06,claude-code,97,1,21.72\ns0003,2026-08,claude-code,148,0,0.38\ns0004,2026-06,codex,73,0,22.91\ns0005,2026-08,claude-code,20,0,15.47\ns0006,2026-08,claude-code,35,0,24.31\ns0007,2026-05,claude-code,57,0,21.82\ns0008,2026-07,codex,52,1,21.91\ns0009,2026-06,claude-code,178,0,24.17\ns0010,2026-08,codex,7,0,10.4\ns0011,2026-06,codex,18,0,7.57\ns0012,2026-09,claude-code,154,2,17.71\ns0013,2026-05,codex,92,0,12.04\ns0014,2026-07,claude-code,125,1,17.63\ns0015,2026-05,codex,7,2,8.97\ns0016,2026-08,claude-code,142,1,9.19\ns0017,2026-09,claude-code,117,0,17.71\ns0018,2026-09,claude-code,32,0,23.24\ns0019,2026-08,codex,133,0,22.32\ns0020,2026-07,codex,29,1,18.72\ns0021,2026-07,codex,11,1,23.65\ns0022,2026-05,claude-code,89,1,15.29\ns0023,2026-06,codex,72,2,13.65\ns0024,2026-07,codex,80,0,19.98\ns0025,2026-06,codex,125,0,18.02\ns0026,2026-05,codex,10,0,18.53\ns0027,2026-07,codex,118,2,10.57\ns0028,2026-05,claude-code,128,0,20.97\ns0029,2026-06,claude-code,163,1,2.71\ns0030,2026-08,codex,40,0,21.13\ns0031,2026-07,claude-code,118,1,21.31\ns0032,2026-09,codex,126,2,18.25\ns0033,2026-08,codex,76,1,10.12\ns0034,2026-06,claude-code,98,1,24.0\ns0035,2026-08,codex,48,0,12.32\ns0036,2026-09,codex,18,0,17.38\ns0037,2026-05,codex,95,1,17.63\ns0038,2026-07,codex,69,2,17.91\ns0039,2026-07,claude-code,150,0,11.88\ns0040,2026-07,codex,173,0,11.6\ns0041,2026-09,codex,91,0,16.12\ns0042,2026-08,codex,46,2,11.27\ns0043,2026-07,codex,134,0,13.26\ns0044,2026-06,claude-code,94,1,7.11\ns0045,2026-05,codex,45,1,19.52\ns0046,2026-09,codex,79,1,13.85\ns0047,2026-07,claude-code,52,0,14.68\ns0048,2026-09,claude-code,58,2,4.55\ns0049,2026-05,codex,59,0,1.4\ns0050,2026-06,claude-code,83,0,12.09\ns0051,2026-09,claude-code,108,1,8.81\ns0052,2026-09,claude-code,153,0,5.98\ns0053,2026-07,claude-code,91,1,23.81\ns0054,2026-08,claude-code,178,1,9.38\ns0055,2026-05,codex,26,0,13.65\ns0056,2026-07,codex,92,0,10.51\ns0057,2026-09,codex,121,0,3.96\ns0058,2026-08,codex,52,0,15.23\ns0059,2026-07,claude-code,99,0,8.18\ns0060,2026-09,claude-code,85,2,21.92\ns0061,2026-09,codex,111,1,24.42\ns0062,2026-08,codex,124,2,9.53\ns0063,2026-06,codex,79,1,6.31\ns0064,2026-05,codex,80,1,23.24\ns0065,2026-06,codex,8,0,16.52\ns0066,2026-08,claude-code,77,0,19.55\ns0067,2026-08,claude-code,124,1,14.03\ns0068,2026-06,codex,11,0,12.28\ns0069,2026-06,codex,77,1,15.22\ns0070,2026-08,claude-code,6,0,7.55\ns0071,2026-09,codex,159,0,18.3\ns0072,2026-05,codex,91,0,17.06\ns0073,2026-09,claude-code,11,0,6.35\ns0074,2026-08,claude-code,177,1,4.82\ns0075,2026-08,codex,154,1,17.24\ns0076,2026-08,codex,123,1,17.07\ns0077,2026-06,codex,121,0,7.63\ns0078,2026-05,codex,151,0,16.23\ns0079,2026-08,codex,38,0,11.99\ns0080,2026-09,codex,86,1,3.88\ns0081,2026-09,claude-code,19,2,5.79\ns0082,2026-05,claude-code,171,0,8.36\ns0083,2026-08,claude-code,105,2,12.19\ns0084,2026-05,claude-code,58,1,16.16\ns0085,2026-05,claude-code,76,2,22.95\ns0086,2026-06,claude-code,158,0,10.38\ns0087,2026-0"}
{"turn": 3, "response": {"id": "a1116e7a-07f7-9a37-95d9-3ae1c446e2d7", "object": "chat.completion", "created": 1792023624, "model": "grok-4-3", "choices": [{"index": 0, "message": {"role": "assistant", "content": null, "refusal": null, "reasoning_content": "The CSV contains 400 sessions.\n\n[encrypted reasoning omitted, 241 chars]", "reasoning_encrypted": true, "reasoning_details": [{"type": "reasoning.encrypted", "format": "xai-responses-v1", "index": 0, "id": "rs_a1116e7a-07f7-9a37-95d9-3ae1c446e2d7", "data": "Gjsb/gpgzQDsfk+JueVXy6PU16YYuj6QfEYUHBoBulnmOo8xplAoQ+h27V72osbq9ujdoe5gWN31O5GvSanVk7Pur52SXvWG08xBOWhzes4NtIqPvUw2I+7pro1SXJm7P5qtHqYlGJBGrEZeG907lItfXs9nGbQFD4aioD4BxhAtVcPg72zaiby/JZUvVoaATO1N9Vh1stUxuvr0kpAAeK/7JQ"}], "tool_calls": [{"id": "call-91b36c8b-9457-470b-9f72-5edd440a832c-2", "type": "function", "function": {"name": "run_shell", "arguments": "{\"command\":\"python3 -c '\\nimport csv\\nfrom collections import defaultdict\\nimport statistics\\n\\nwith open(\\\"sessions.csv\\\") as f:\\n rows = list(csv.DictReader(f))\\n\\ntotal_sessions = len(rows)\\ntotal_prs = sum(int(r[\\\"prs_opened\\\"]) for r in rows)\\ntotal_api = sum(float(r[\\\"api_equiv_usd\\\"]) for r in rows)\\ntotal_api_equiv_usd = round(total_api, 2)\\n\\nmonths = defaultdict(int)\\nfor r in rows:\\n months[r[\\\"month\\\"]] += 1\\nbusiest_month_by_sessions = max(months, key=months.get)\\n\\nminutes = [int(r[\\\"minutes\\\"]) for r in rows]\\nmedian_minutes = statistics.median(minutes)\\n\\ntools = defaultdict(lambda: {\\\"usd\\\": 0.0, \\\"prs\\\": 0})\\nfor r in rows:\\n t = r[\\\"tool\\\"]\\n tools[t][\\\"usd\\\"] += float(r[\\\"api_equiv_usd\\\"])\\n tools[t][\\\"prs\\\"] += int(r[\\\"prs_opened\\\"])\\n\\nusd_per_pr_by_tool = {}\\nfor t, d in tools.items():\\n if d[\\\"prs\\\"] > 0:\\n usd_per_pr_by_tool[t] = round(d[\\\"usd\\\"] / d[\\\"prs\\\"], 2)\\n else:\\n usd_per_pr_by_tool[t] = 0.0\\n\\nanswers = {\\n \\\"total_sessions\\\": total_sessions,\\n \\\"total_prs\\\": total_prs,\\n \\\"total_api_equiv_usd\\\": total_api_equiv_usd,\\n \\\"busiest_month_by_sessions\\\": busiest_month_by_sessions,\\n \\\"median_minutes\\\": median_minutes,\\n \\\"usd_per_pr_by_tool\\\": usd_per_pr_by_tool\\n}\\nprint(answers)\\n'\"}"}}]}, "finish_reason": "tool_calls", "logprobs": null}], "usage": {"prompt_tokens": 8644, "completion_tokens": 392, "total_tokens": 9036, "prompt_tokens_details": {"cached_tokens": 128}, "cache_read_input_tokens": 128, "completion_tokens_details": {"reasoning_tokens": 34}}, "cost": {"usd": 0, "diem": 0.01323152}, "venice_parameters": {"strip_thinking_response": false, "disable_thinking": false, "enable_e2ee": true, "enable_web_search": "off", "enable_web_scraping": false, "enable_web_citations": false, "include_search_results_in_stream": false, "include_venice_system_prompt": false, "enable_x_search": false, "web_search_citations": [], "return_search_results_as_documents": false}}}
{"turn": 3, "tool": "run_shell", "args": {"command": "python3 -c '\nimport csv\nfrom collections import defaultdict\nimport statistics\n\nwith open(\"sessions.csv\") as f:\n rows = list(csv.DictReader(f))\n\ntotal_sessions = len(rows)\ntotal_prs = sum(int(r[\"prs_opened\"]) for r in rows)\ntotal_api = sum(float(r[\"api_equiv_usd\"]) for r in rows)\ntotal_api_equiv_usd = round(total_api, 2)\n\nmonths = defaultdict(int)\nfor r in rows:\n months[r[\"month\"]] += 1\nbusiest_month_by_sessions = max(months, key=months.get)\n\nminutes = [int(r[\"minutes\"]) for r in rows]\nmedian_minutes = statistics.median(minutes)\n\ntools = defaultdict(lambda: {\"usd\": 0.0, \"prs\": 0})\nfor r in rows:\n t = r[\"tool\"]\n tools[t][\"usd\"] += float(r[\"api_equiv_usd\"])\n tools[t][\"prs\"] += int(r[\"prs_opened\"])\n\nusd_per_pr_by_tool = {}\nfor t, d in tools.items():\n if d[\"prs\"] > 0:\n usd_per_pr_by_tool[t] = round(d[\"usd\"] / d[\"prs\"], 2)\n else:\n usd_per_pr_by_tool[t] = 0.0\n\nanswers = {\n \"total_sessions\": total_sessions,\n \"total_prs\": total_prs,\n \"total_api_equiv_usd\": total_api_equiv_usd,\n \"busiest_month_by_sessions\": busiest_month_by_sessions,\n \"median_minutes\": median_minutes,\n \"usd_per_pr_by_tool\": usd_per_pr_by_tool\n}\nprint(answers)\n'"}, "result": "exit=0\nstdout:\n{'total_sessions': 400, 'total_prs': 256, 'total_api_equiv_usd': 4843.16, 'busiest_month_by_sessions': '2026-09', 'median_minutes': 88.5, 'usd_per_pr_by_tool': {'codex': 18.39, 'claude-code': 19.5}}\n\nstderr:\n"}
{"turn": 4, "response": {"id": "52a64593-e663-918c-afab-108721901a14", "object": "chat.completion", "created": 1792023628, "model": "grok-4-3", "choices": [{"index": 0, "message": {"role": "assistant", "content": null, "refusal": null, "reasoning_content": "[encrypted reasoning omitted, 87 chars]", "reasoning_encrypted": true, "reasoning_details": [{"type": "reasoning.encrypted", "format": "xai-responses-v1", "index": 0, "id": "rs_52a64593-e663-918c-afab-108721901a14", "data": "mKPKtFlnZHXZURS97S6bn51O125nemu0GC2lxpG/OwoXnXv97zUI/Zm9b8Vi3DTA"}], "tool_calls": [{"id": "call-af198058-bc5c-4e16-a98c-6ac2266ef448-3", "type": "function", "function": {"name": "write_file", "arguments": "{\"path\":\"answers.json\",\"content\":\"{\\\"total_sessions\\\": 400, \\\"total_prs\\\": 256, \\\"total_api_equiv_usd\\\": 4843.16, \\\"busiest_month_by_sessions\\\": \\\"2026-09\\\", \\\"median_minutes\\\": 88.5, \\\"usd_per_pr_by_tool\\\": {\\\"codex\\\": 18.39, \\\"claude-code\\\": 19.5}}\"}"}}, {"id": "call-af198058-bc5c-4e16-a98c-6ac2266ef448-4", "type": "function", "function": {"name": "write_file", "arguments": "{\"path\":\"REPORT.md\",\"content\":\"- 400 sessions logged over 5 months with 256 PRs opened.\\n- Total API equivalent cost reached $4843.16.\\n- September 2026 was busiest with most sessions.\\n- Median session length 88.5 minutes.\\n- Codex averaged $18.39 per PR vs $19.50 for Claude-Code.\"}"}}]}, "finish_reason": "tool_calls", "logprobs": null}], "usage": {"prompt_tokens": 9093, "completion_tokens": 177, "total_tokens": 9270, "prompt_tokens_details": {"cached_tokens": 8576}, "cache_read_input_tokens": 8576, "completion_tokens_details": {"reasoning_tokens": 5}}, "cost": {"usd": 0, "diem": 0.00320753}, "venice_parameters": {"strip_thinking_response": false, "disable_thinking": false, "enable_e2ee": true, "enable_web_search": "off", "enable_web_scraping": false, "enable_web_citations": false, "include_search_results_in_stream": false, "include_venice_system_prompt": false, "enable_x_search": false, "web_search_citations": [], "return_search_results_as_documents": false}}}
{"turn": 4, "tool": "write_file", "args": {"path": "answers.json", "content": "{\"total_sessions\": 400, \"total_prs\": 256, \"total_api_equiv_usd\": 4843.16, \"busiest_month_by_sessions\": \"2026-09\", \"median_minutes\": 88.5, \"usd_per_pr_by_tool\": {\"codex\": 18.39, \"claude-code\": 19.5}}"}, "result": "wrote 198 chars"}
{"turn": 4, "tool": "write_file", "args": {"path": "REPORT.md", "content": "- 400 sessions logged over 5 months with 256 PRs opened.\n- Total API equivalent cost reached $4843.16.\n- September 2026 was busiest with most sessions.\n- Median session length 88.5 minutes.\n- Codex averaged $18.39 per PR vs $19.50 for Claude-Code."}, "result": "wrote 247 chars"}
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