DeepSeek V4.1 Flash (Venice) on Implement a spec exactly, with nothing extra
DDeepSeek V4.1 Flash (Venice) · venice-mini-agent v1.0 · cloud · 2026-10-14 · by @bobsiopener
- Estimated cost
- $0.0019
- Wall time
- 2m
- Human step-ins
- 0
- Outcome
- Pass
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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 computed from Venice list prices and per-call usage (not confirmed by Venice billing for this run).
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 v1.0 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. cost_is_estimate=true: no Venice-reported billed amount recorded for this run. 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.
Estimated cost List-price estimate; not actually billed.
Metrics
- Estimated cost
- $0.0019
- Wall time
- 2m
- Human step-ins
- 0
- Turns
- 4
| Model | Input tok | Output tok | Cost |
|---|---|---|---|
| DDeepSeek V4.1 Flash (Venice)venice/deepseek-v4-1-flash | 3,741 | 1,115 | $0.0019 |
Reproduce this run
- Use the use case prompt on the use case page.
- Same setup: DeepSeek V4.1 Flash (Venice) (venice/deepseek-v4-1-flash) via
venice-mini-agent v1.0, 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": {"id": "chatcmpl-9eb1d78e7ab548b294808794818cc757", "object": "chat.completion", "created": 1792017912, "model": "deepseek-v4-1-flash", "choices": [{"index": 0, "message": {"role": "assistant", "content": "I'll start by reading the spec file.", "tool_calls": [{"index": 0, "id": "chatcmpl-tool-b9d5a8015c9f8715", "type": "function", "function": {"name": "read_file", "arguments": "{\"path\": \"SPEC.md\"}"}, "name": null}, {"index": 1, "id": "chatcmpl-tool-82fb28f0ddb67a2c", "type": "function", "function": {"name": "list_files", "arguments": "{\"path\": \".\"}"}, "name": null}], "tools": null}, "finish_reason": "tool_calls"}], "usage": {"prompt_tokens": 523, "completion_tokens": 75, "total_tokens": 598, "prompt_tokens_details": {"cached_tokens": 0}, "completion_tokens_details": {"reasoning_tokens": 0}}, "cost": {"usd": 0, "diem": 0.0002469}, "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": {"id": "chatcmpl-5168d3006fd747dd84bb07ca8f503b7b", "object": "chat.completion", "created": 1792017934, "model": "deepseek-v4-1-flash", "choices": [{"index": 0, "message": {"role": "assistant", "content": "", "reasoning_content": "Let me write kv.py. Requirements: single file, stdlib only, kv.json in current dir. Commands set/get/del/list. Under 60 non-blank lines. No classes.\n\nLet me write it.\n\nNote: \"no extra files\" \u2014 kv.json is created at runtime, that's fine.\n\nLet me write minimal code.\n\n```python\nimport json, os, sys\n\nPATH = \"kv.json\"\n\ndef load():\n if os.path.exists(PATH):\n with open(PATH) as f:\n return json.load(f)\n return {}\n\ndef save(d):\n with open(PATH, \"w\") as f:\n json.dump(d, f)\n\ndef main():\n args = sys.argv[1:]\n if not args:\n return 1\n cmd = args[0]\n data = load()\n if cmd == \"set\" and len(args) == 3:\n data[args[1]] = args[2]\n save(data)\n print(\"OK\")\n elif cmd == \"get\" and len(args) == 2:\n if args[1] in data:\n print(data[args[1]])\n else:\n print(\"NOT FOUND\")\n return 1\n elif cmd == \"del\" and len(args) == 2:\n if args[1] in data:\n del data[args[1]]\n save(data)\n print(\"OK\")\n else:\n print(\"NOT FOUND\")\n return 1\n elif cmd == \"list\" and len(args) == 1:\n for k in sorted(data):\n print(k)\n else:\n return 1\n return 0\n\nif __name__ == \"__main__\":\n sys.exit(main())\n```\n\nCount non-blank lines: let me count. That's fine, under 60.\n\nLet me write and test.", "tool_calls": [{"index": 0, "id": "chatcmpl-tool-a1f3a5e93f9d2b15", "type": "function", "function": {"name": "write_file", "arguments": "{\"path\": \"kv.py\", \"content\": \"import json, os, sys\\n\\nPATH = \\\"kv.json\\\"\\n\\ndef load():\\n if os.path.exists(PATH):\\n with open(PATH) as f:\\n return json.load(f)\\n return {}\\n\\ndef save(data):\\n with open(PATH, \\\"w\\\") as f:\\n json.dump(data, f)\\n\\ndef main():\\n args = sys.argv[1:]\\n if not args:\\n return 1\\n cmd = args[0]\\n data = load()\\n if cmd == \\\"set\\\" and len(args) == 3:\\n data[args[1]] = args[2]\\n save(data)\\n print(\\\"OK\\\")\\n elif cmd == \\\"get\\\" and len(args) == 2:\\n if args[1] in data:\\n print(data[args[1]])\\n else:\\n print(\\\"NOT FOUND\\\")\\n return 1\\n elif cmd == \\\"del\\\" and len(args) == 2:\\n if args[1] in data:\\n del data[args[1]]\\n save(data)\\n print(\\\"OK\\\")\\n else:\\n print(\\\"NOT FOUND\\\")\\n return 1\\n elif cmd == \\\"list\\\" and len(args) == 1:\\n for key in sorted(data):\\n print(key)\\n else:\\n return 1\\n return 0\\n\\nif __name__ == \\\"__main__\\\":\\n sys.exit(main())\\n\"}"}, "name": null}], "tools": null}, "finish_reason": "tool_calls"}], "usage": {"prompt_tokens": 755, "completion_tokens": 735, "total_tokens": 1490, "prompt_tokens_details": {"cached_tokens": 394}, "cache_read_input_tokens": 394, "completion_tokens_details": {"reasoning_tokens": 389}}, "cost": {"usd": 0, "diem": 0.000993255}, "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, os, sys\n\nPATH = \"kv.json\"\n\ndef load():\n if os.path.exists(PATH):\n with open(PATH) as f:\n return json.load(f)\n return {}\n\ndef save(data):\n with open(PATH, \"w\") as f:\n json.dump(data, f)\n\ndef main():\n args = sys.argv[1:]\n if not args:\n return 1\n cmd = args[0]\n data = load()\n if cmd == \"set\" and len(args) == 3:\n data[args[1]] = args[2]\n save(data)\n print(\"OK\")\n elif cmd == \"get\" and len(args) == 2:\n if args[1] in data:\n print(data[args[1]])\n else:\n print(\"NOT FOUND\")\n return 1\n elif cmd == \"del\" and len(args) == 2:\n if args[1] in data:\n del data[args[1]]\n save(data)\n print(\"OK\")\n else:\n print(\"NOT FOUND\")\n return 1\n elif cmd == \"list\" and len(args) == 1:\n for key in sorted(data):\n print(key)\n else:\n return 1\n return 0\n\nif __name__ == \"__main__\":\n sys.exit(main())\n"}, "result": "wrote 1020 chars"}
{"turn": 3, "response": {"id": "chatcmpl-6cc66b1c8bd24888a5d420ebfeeb3e40", "object": "chat.completion", "created": 1792017979, "model": "deepseek-v4-1-flash", "choices": [{"index": 0, "message": {"role": "assistant", "content": "", "tool_calls": [{"index": 0, "id": "chatcmpl-tool-b5668acbfe2dccce", "type": "function", "function": {"name": "run_shell", "arguments": "{\"command\": \"cd /tmp && rm -f kv.json && cp /dev/null /dev/null; cd - >/dev/null; d=$(mktemp -d); cp kv.py $d/; cd $d; python3 kv.py set a 1; python3 kv.py set b 2; python3 kv.py get a; python3 kv.py list; python3 kv.py del a; python3 kv.py get a; echo \\\"exit=$?\\\"; python3 kv.py del zzz; echo \\\"exit=$?\\\"; grep -c '[^[:space:]]' kv.py\"}"}, "name": null}], "tools": null}, "finish_reason": "tool_calls"}], "usage": {"prompt_tokens": 1118, "completion_tokens": 160, "total_tokens": 1278, "prompt_tokens_details": {"cached_tokens": 626}, "cache_read_input_tokens": 626, "completion_tokens_details": {"reasoning_tokens": 0}}, "cost": {"usd": 0, "diem": 0.000344295}, "venice_parameters": {"strip_thinking_response": false, "disable_thinking": false, "enable_e2ee": true, "enable_web_search": "off", "enable_web_scraping": false, "enable_web_citations": false, "include_search_results_in_stream": false, "include_venice_system_prompt": false, "enable_x_search": false, "web_search_citations": [], "return_search_results_as_documents": false}}}
{"turn": 3, "tool": "run_shell", "args": {"command": "cd /tmp && rm -f kv.json && cp /dev/null /dev/null; cd - >/dev/null; d=$(mktemp -d); cp kv.py $d/; cd $d; python3 kv.py set a 1; python3 kv.py set b 2; python3 kv.py get a; python3 kv.py list; python3 kv.py del a; python3 kv.py get a; echo \"exit=$?\"; python3 kv.py del zzz; echo \"exit=$?\"; grep -c '[^[:space:]]' kv.py"}, "result": "exit=0\nstdout:\nOK\nOK\n1\na\nb\nOK\nNOT FOUND\nexit=1\nNOT FOUND\nexit=1\n42\n\nstderr:\ncp: '/dev/null' and '/dev/null' are the same file\n"}
{"turn": 4, "response": {"id": "chatcmpl-a1ba9d5c20b043178c711feb905f8aca", "object": "chat.completion", "created": 1792017983, "model": "deepseek-v4-1-flash", "choices": [{"index": 0, "message": {"role": "assistant", "content": "Implemented `kv.py` per SPEC.md.\n\n- Single file, Python 3 stdlib only (`json`, `os`, `sys`), persists to `kv.json` in the current directory.\n- `set` \u2192 prints `OK`; `get` \u2192 prints value or `NOT FOUND` with exit 1; `del` \u2192 prints `OK` or `NOT FOUND` with exit 1; `list` \u2192 sorted keys, one per line.\n- No classes, no extra features/files; 42 non-blank lines (under 60).\n\nVerified all commands and exit codes work as specified.", "reasoning_content": "All works. 42 non-blank lines, under 60. Done.", "tools": null}, "finish_reason": "stop"}], "usage": {"prompt_tokens": 1345, "completion_tokens": 145, "total_tokens": 1490, "prompt_tokens_details": {"cached_tokens": 988}, "cache_read_input_tokens": 988, "completion_tokens_details": {"reasoning_tokens": 16}}, "cost": {"usd": 0, "diem": 0.00028851}, "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}}}