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
- Cost
- $0.01
- Wall time
- 14s
- Human step-ins
- 0
- Outcome
- Pass
Compare with other models on this task →
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 | Input tok | Output tok | Cost |
|---|---|---|---|
| ZGLM 5.3 (Venice)venice/z-ai-glm-5-3thinking on | 7,156 | 1,270 | $0.01 |
Reproduce this run
- Use the use case prompt on the use case page.
- Same setup: GLM 5.3 (Venice) (venice/z-ai-glm-5-3, thinking on) via
venice-mini-agent v1.2, cloud. - 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).
- 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": {"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}}}