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GLM 5.3 (Venice) (thinking on) on Implement a spec exactly, with nothing extra

ZGLM 5.3 (Venice)thinking on · venice-mini-agent v1.2 · cloud · 2026-10-17 · by @bobsiopener

Trust 80%Fully autonomoussuccess · first trySuperseded
Cost
$0.01
Wall time
14s
Human step-ins
0
Outcome
Pass

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Superseded. This run was rescored on 2026-10-28 and replaced by a newer run. It no longer counts toward rankings, use-case tables or the data export; it is kept here for the record.

Summary

Exact prompt

Implement SPEC.md exactly. Then stop. Do not add anything the spec does not ask for.

Task prompt given to the agent (headless, offline, synthetic fixture inputs): Implement SPEC.md exactly. Then stop. Do not add anything the spec does not ask for. Inspired by https://x.com/mave99a/status/2096480295692460432 (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: hidden test test_flow; hidden test test_overwrite; under 60 non-blank lines; no classes; no extra files; stdlib only (no non-stdlib imports).

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 (6/6 checks). Runner notes: Adapted: 24h Codex run scaled to a minimal-spec task scored on spec adherence and over-engineering limits. Single run, no retries. Same rubric/score.py as Claude runs. Web disabled.

Metrics

Cost
$0.01
Wall time
14s
Human step-ins
0
Turns
7
Model usage
ModelInput tokOutput tokCost
ZGLM 5.3 (Venice)venice/z-ai-glm-5-3thinking on7,1561,270$0.01

Reproduce this run

  1. Use the use case prompt on the use case page.
  2. Same setup: GLM 5.3 (Venice) (venice/z-ai-glm-5-3, thinking on) via venice-mini-agent v1.2, cloud.
  3. It counts as a success only if it meets every success criterion: All automated rubric checks pass: hidden test test_flow; hidden test test_overwrite; under 60 non-blank lines; no classes; no extra files; stdlib only (no non-stdlib imports).
  4. 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

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Evidence log
{"turn": 1, "response": {"service_tier": "default", "id": "chatcmpl-R3iVnbRbtdJJnwcOpn5xQ0o2", "object": "chat.completion", "created": 1792196574, "model": "z-ai-glm-5-3", "choices": [{"index": 0, "message": {"role": "assistant", "content": "I'll start by reading the spec file.", "reasoning_content": null, "name": null, "tool_calls": [{"id": "chatcmpl-tool-b27e0ae1e016c3ae", "type": "function", "function": {"name": "read_file", "arguments": "{\"path\": \"SPEC.md\"}"}}, {"id": "chatcmpl-tool-99c7f2ef5592efb6", "type": "function", "function": {"name": "list_files", "arguments": "{\"path\": \".\"}"}}]}, "finish_reason": "tool_calls", "logprobs": null}], "usage": {"prompt_tokens": 388, "completion_tokens": 32, "total_tokens": 420, "prompt_tokens_details": {"cached_tokens": 256}, "cache_read_input_tokens": 256, "completion_tokens_details": {"reasoning_tokens": 0}}, "cost": {"usd": 0, "diem": 0.0004902}, "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": "read_file", "args": {"path": "SPEC.md"}, "result": "# kv.py spec\nA tiny key-value store CLI. Single file kv.py, Python 3 stdlib only, data persisted in kv.json in the current directory.\nCommands:\n- python3 kv.py set KEY VALUE   -> prints OK\n- python3 kv.py get KEY         -> prints VALUE, or prints \"NOT FOUND\" and exits 1\n- python3 kv.py del KEY         -> prints OK, or \"NOT FOUND\" and exits 1\n- python3 kv.py list            -> prints keys sorted, one per line\nKeep it minimal: no classes, no extra features, no extra files, under 60 non-blank lines.\n"}
{"turn": 1, "tool": "list_files", "args": {"path": "."}, "result": "./SPEC.md"}
{"turn": 2, "response": {"service_tier": "default", "id": "chatcmpl-RljSX4fxkwER6myJvH45cEqp", "object": "chat.completion", "created": 1792196578, "model": "z-ai-glm-5-3", "choices": [{"index": 0, "message": {"role": "assistant", "content": "", "reasoning_content": "Simple. Write kv.py.\n\nRequirements:\n- set KEY VALUE -> prints OK\n- get KEY -> prints VALUE or \"NOT FOUND\" exit 1\n- del KEY -> prints OK or \"NOT FOUND\" exit 1\n- list -> keys sorted, one per line\n\nUse json, sys. Keep minimal, no classes, under 60 non-blank lines.\n\nLet me write it.", "name": null, "tool_calls": [{"id": "chatcmpl-tool-bd247343308d58e5", "type": "function", "function": {"name": "write_file", "arguments": "{\"path\": \"kv.py\", \"content\": \"import json\\nimport sys\\n\\nSTORE = \\\"kv.json\\\"\\n\\n\\ndef load():\\n    try:\\n        with open(STORE) as f:\\n            return json.load(f)\\n    except (FileNotFoundError, ValueError):\\n        return {}\\n\\n\\ndef save(data):\\n    with open(STORE, \\\"w\\\") as f:\\n        json.dump(data, f)\\n\\n\\ndef main(argv):\\n    if len(argv) < 2:\\n        print(\\\"usage: kv.py set KEY VALUE | get KEY | del KEY | list\\\")\\n        return 2\\n    cmd = argv[1]\\n    data = load()\\n    if cmd == \\\"set\\\":\\n        if len(argv) != 4:\\n            print(\\\"usage: kv.py set KEY VALUE\\\")\\n            return 2\\n        data[argv[2]] = argv[3]\\n        save(data)\\n        print(\\\"OK\\\")\\n    elif cmd == \\\"get\\\":\\n        if len(argv) != 3:\\n            print(\\\"usage: kv.py get KEY\\\")\\n            return 2\\n        if argv[2] in data:\\n            print(data[argv[2]])\\n        else:\\n            print(\\\"NOT FOUND\\\")\\n            return 1\\n    elif cmd == \\\"del\\\":\\n        if len(argv) != 3:\\n            print(\\\"usage: kv.py del KEY\\\")\\n            return 2\\n        if argv[2] in data:\\n            del data[argv[2]]\\n            save(data)\\n            print(\\\"OK\\\")\\n        else:\\n            print(\\\"NOT FOUND\\\")\\n            return 1\\n    elif cmd == \\\"list\\\":\\n        for key in sorted(data):\\n            print(key)\\n    else:\\n        print(\\\"usage: kv.py set KEY VALUE | get KEY | del KEY | list\\\")\\n        return 2\\n    return 0\\n\\n\\nif __name__ == \\\"__main__\\\":\\n    sys.exit(main(sys.argv))\\n\"}"}}]}, "finish_reason": "tool_calls", "logprobs": null}], "usage": {"prompt_tokens": 562, "completion_tokens": 465, "total_tokens": 1027, "prompt_tokens_details": {"cached_tokens": 320}, "cache_read_input_tokens": 320, "completion_tokens_details": {"reasoning_tokens": 80}}, "cost": {"usd": 0, "diem": 0.0030849999999999996}, "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": "write_file", "args": {"path": "kv.py", "content": "import json\nimport sys\n\nSTORE = \"kv.json\"\n\n\ndef load():\n    try:\n        with open(STORE) as f:\n            return json.load(f)\n    except (FileNotFoundError, ValueError):\n        return {}\n\n\ndef save(data):\n    with open(STORE, \"w\") as f:\n        json.dump(data, f)\n\n\ndef main(argv):\n    if len(argv) < 2:\n        print(\"usage: kv.py set KEY VALUE | get KEY | del KEY | list\")\n        return 2\n    cmd = argv[1]\n    data = load()\n    if cmd == \"set\":\n        if len(argv) != 4:\n            print(\"usage: kv.py set KEY VALUE\")\n            return 2\n        data[argv[2]] = argv[3]\n        save(data)\n        print(\"OK\")\n    elif cmd == \"get\":\n        if len(argv) != 3:\n            print(\"usage: kv.py get KEY\")\n            return 2\n        if argv[2] in data:\n            print(data[argv[2]])\n        else:\n            print(\"NOT FOUND\")\n            return 1\n    elif cmd == \"del\":\n        if len(argv) != 3:\n            print(\"usage: kv.py del KEY\")\n            return 2\n        if argv[2] in data:\n            del data[argv[2]]\n            save(data)\n            print(\"OK\")\n        else:\n            print(\"NOT FOUND\")\n            return 1\n    elif cmd == \"list\":\n        for key in sorted(data):\n            print(key)\n    else:\n        print(\"usage: kv.py set KEY VALUE | get KEY | del KEY | list\")\n        return 2\n    return 0\n\n\nif __name__ == \"__main__\":\n    sys.exit(main(sys.argv))\n"}, "result": "wrote 1392 chars"}
{"turn": 3, "response": {"service_tier": "default", "id": "chatcmpl-RNnpwMNTz1dE7J2DB1kTRC22", "object": "chat.completion", "created": 1792196579, "model": "z-ai-glm-5-3", "choices": [{"index": 0, "message": {"role": "assistant", "content": "", "reasoning_content": "Let's test it and check the line count (non-blank lines).\n\nThe spec says no classes \u2014 there are none. But does it allow functions? \"no classes\" explicitly, so functions are fine. Let me test.", "name": null, "tool_calls": [{"id": "chatcmpl-tool-9d720b184917728b", "type": "function", "function": {"name": "run_shell", "arguments": "{\"command\": \"cd /tmp && rm -rf kvtest && mkdir kvtest && cd kvtest && cp \\\"$OLDPWD/kv.py\\\" . 2>/dev/null || cp -/kv.py . 2>/dev/null; echo hi\"}"}}, {"id": "chatcmpl-tool-9bd79c9bdf966af7", "type": "function", "function": {"name": "run_shell", "arguments": "{\"command\": \"grep -c -v '^[[:space:]]*$' kv.py\"}"}}]}, "finish_reason": "tool_calls", "logprobs": null}], "usage": {"prompt_tokens": 957, "completion_tokens": 128, "total_tokens": 1085, "prompt_tokens_details": {"cached_tokens": 448}, "cache_read_input_tokens": 448, "completion_tokens_details": {"reasoning_tokens": 46}}, "cost": {"usd": 0, "diem": 0.00174035}, "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": "cd /tmp && rm -rf kvtest && mkdir kvtest && cd kvtest && cp \"$OLDPWD/kv.py\" . 2>/dev/null || cp -/kv.py . 2>/dev/null; echo hi"}, "result": "exit=0\nstdout:\nhi\n\nstderr:\n"}
{"turn": 3, "tool": "run_shell", "args": {"command": "grep -c -v '^[[:space:]]*$' kv.py"}, "result": "exit=0\nstdout:\n54\n\nstderr:\n"}
{"turn": 4, "response": {"service_tier": "default", "id": "chatcmpl-RHWPHzfeelGfvsZQcgrkDbvv", "object": "chat.completion", "created": 1792196581, "model": "z-ai-glm-5-3", "choices": [{"index": 0, "message": {"role": "assistant", "content": "", "reasoning_content": "54 non-blank lines, under 60. Now let's actually test it properly.\n\nThe cd command had issues; let me do a clean test.", "name": null, "tool_calls": [{"id": "chatcmpl-tool-9374890e7bab5044", "type": "function", "function": {"name": "run_shell", "arguments": "{\"command\": \"rm -rf /tmp/kvtest && mkdir -p /tmp/kvtest && cp kv.py /tmp/kvtest/ && cd /tmp/kvtest && rm -f kv.json && python3 kv.py set a 1 && python3 kv.py set b 2 && python3 kv.py set c 3 && python3 kv.py list && python3 kv.py get b && python3 kv.py get missing; echo \\\"get-missing-exit=$?\\\"; python3 kv.py del b && python3 kv.py list && python3 kv.py del b; echo \\\"del-missing-exit=$?\\\"; cat kv.json\"}"}}]}, "finish_reason": "tool_calls", "logprobs": null}], "usage": {"prompt_tokens": 1065, "completion_tokens": 173, "total_tokens": 1238, "prompt_tokens_details": {"cached_tokens": 832}, "cache_read_input_tokens": 832, "completion_tokens_details": {"reasoning_tokens": 31}}, "cost": {"usd": 0, "diem": 0.00162965}, "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": "run_shell", "args": {"command": "rm -rf /tmp/kvtest && mkdir -p /tmp/kvtest && cp kv.py /tmp/kvtest/ && cd /tmp/kvtest && rm -f kv.json && python3 kv.py set a 1 && python3 kv.py set b 2 && python3 kv.py set c 3 && python3 kv.py list && python3 kv.py get b && python3 kv.py get missing; echo \"get-missing-exit=$?\"; python3 kv.py del b && python3 kv.py list && python3 kv.py del b; echo \"del-missing-exit=$?\"; cat kv.json"}, "result": "exit=0\nstdout:\nOK\nOK\nOK\na\nb\nc\n2\nNOT FOUND\nget-missing-exit=1\nOK\na\nc\nNOT FOUND\ndel-missing-exit=1\n{\"a\": \"1\", \"c\": \"3\"}\nstderr:\n"}
{"turn": 5, "response": {"service_tier": "default", "id": "chatcmpl-RvoWXKcMFb5Zjf3dTxqJWRFz", "object": "chat.completion", "created": 1792196584, "model": "z-ai-glm-5-3", "choices": [{"index": 0, "message": {"role": "assistant", "content": "", "reasoning_content": "All working. Also test persistence across separate invocations (already done, separate processes). Test empty list output, and value with spaces passed as quoted arg.\n\nLet me do a quick test on empty list and value with spaces.", "name": null, "tool_calls": [{"id": "chatcmpl-tool-8d23484e43bf8dd1", "type": "function", "function": {"name": "run_shell", "arguments": "{\"command\": \"rm -rf /tmp/kvtest2 && mkdir -p /tmp/kvtest2 && cp kv.py /tmp/kvtest2/ && cd /tmp/kvtest2 && echo \\\"--- empty list ---\\\" && python3 kv.py list; echo \\\"exit=$?\\\"; echo \\\"--- value with spaces ---\\\"; python3 kv.py set k \\\"hello world\\\" && python3 kv.py get k; echo \\\"--- get exit 0 ---\\\"; echo \\\"exit=$?\\\"; cat kv.json\"}"}}]}, "finish_reason": "tool_calls", "logprobs": null}], "usage": {"prompt_tokens": 1273, "completion_tokens": 156, "total_tokens": 1429, "prompt_tokens_details": {"cached_tokens": 960}, "cache_read_input_tokens": 960, "completion_tokens_details": {"reasoning_tokens": 45}}, "cost": {"usd": 0, "diem": 0.0017177499999999999}, "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": 5, "tool": "run_shell", "args": {"command": "rm -rf /tmp/kvtest2 && mkdir -p /tmp/kvtest2 && cp kv.py /tmp/kvtest2/ && cd /tmp/kvtest2 && echo \"--- empty list ---\" && python3 kv.py list; echo \"exit=$?\"; echo \"--- value with spaces ---\"; python3 kv.py set k \"hello world\" && python3 kv.py get k; echo \"--- get exit 0 ---\"; echo \"exit=$?\"; cat kv.json"}, "result": "exit=0\nstdout:\n--- empty list ---\nexit=0\n--- value with spaces ---\nOK\nhello world\n--- get exit 0 ---\nexit=0\n{\"k\": \"hello world\"}\nstderr:\n"}
{"turn": 6, "response": {"service_tier": "default", "id": "chatcmpl-RVXsYGnCExO8PvJT9WXd67Au", "object": "chat.completion", "created": 1792196585, "model": "z-ai-glm-5-3", "choices": [{"index": 0, "message": {"role": "assistant", "content": "", "reasoning_content": "Everything works. Spec says \"no classes, no extra features, no extra files, under 60 non-blank lines\" \u2014 54 non-blank lines. Done. Clean up temp dirs.", "name": null, "tool_calls": [{"id": "chatcmpl-tool-83cef4bec5850a40", "type": "function", "function": {"name": "run_shell", "arguments": "{\"command\": \"rm -rf /tmp/kvtest /tmp/kvtest2 && ls -a\"}"}}]}, "finish_reason": "tool_calls", "logprobs": null}], "usage": {"prompt_tokens": 1431, "completion_tokens": 69, "total_tokens": 1500, "prompt_tokens_details": {"cached_tokens": 1152}, "cache_read_input_tokens": 1152, "completion_tokens_details": {"reasoning_tokens": 40}}, "cost": {"usd": 0, "diem": 0.00124215}, "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": 6, "tool": "run_shell", "args": {"command": "rm -rf /tmp/kvtest /tmp/kvtest2 && ls -a"}, "result": "exit=0\nstdout:\n.\n..\nSPEC.md\nkv.py\n\nstderr:\n"}
{"turn": 7, "response": {"service_tier": "default", "id": "chatcmpl-RlzCK3dsw25MKePNnlYv9wv1", "object": "chat.completion", "created": 1792196588, "model": "z-ai-glm-5-3", "choices": [{"index": 0, "message": {"role": "assistant", "content": "Implemented `kv.py` exactly per SPEC.md.\n\n- **Persistence:** data stored as JSON in `kv.json` in the current working directory; created on first `set`, read on every command. Tolerates a missing/corrupt file by treating the store as empty.\n- **Commands:**\n  - `set KEY VALUE` \u2192 prints `OK` and saves\n  - `get KEY` \u2192 prints the value, or prints `NOT FOUND` and exits 1\n  - `del KEY` \u2192 prints `OK` (and saves) on success, or prints `NOT FOUND` and exits 1\n  - `list` \u2192 prints keys sorted, one per line (nothing when empty)\n- **Constraints honored:** single file, Python 3 stdlib only (`json`, `sys`), no classes, no extra features or files, 54 non-blank lines (under 60).\n\nVerified behavior end-to-end in temporary directories: set/get/del/list, sorted output, exit codes (0 on success, 1 on NOT FOUND), values containing spaces, and persistence across separate invocations. No extra files were left behind (`SPEC.md` and `kv.py` only).", "reasoning_content": null, "name": null, "tool_calls": null}, "finish_reason": "stop", "logprobs": null}], "usage": {"prompt_tokens": 1480, "completion_tokens": 247, "total_tokens": 1727, "prompt_tokens_details": {"cached_tokens": 1344}, "cache_read_input_tokens": 1344, "completion_tokens_details": {"reasoning_tokens": 0}}, "cost": {"usd": 0, "diem": 0.0020333}, "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}}}

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