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DeepSeek V4.1 Flash (Venice) (thinking on) on Choose the value-maximising project portfolio under a budget, an hours cap, prerequisites and exclusions

DDeepSeek V4.1 Flash (Venice)thinking on · venice-mini-agent v1.3.1 · cloud · 2026-10-28 · by @bobsiopener

Trust 80%Fully autonomoussuccess · first try
Estimated cost
$0.0030
Wall time
9s
Human step-ins
0
Outcome
Pass

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Summary

Exact prompt

# Choose next quarter's project portfolio Inputs: `projects.csv` (cost, engineering hours and estimated value of each candidate project, plus prerequisites) and `constraints.json` (budget, available hours, pairs that can't both be funded). Pick the set of projects that maximises total value. - Total cost must not exceed the budget, and total hours must not exceed the available hours. - A project can only be funded if all its prerequisites are funded too. - At most one project of each mutually exclusive pair may be funded. - Then answer one what-if: if the budget were cut by 10% (hours unchanged), what is the best total value achievable? Write `out/portfolio.json`: `{"selected": [<project ids, sorted>], "total_value": <n>, "total_cost": <n>, "total_hours": <n>, "value_if_budget_cut_10pct": <n>}`. ## How this run works - Work on your own: nobody will answer questions in this task, and writing to `ask/` counts against the run. - Write only under `out/`. Create `out/` if it is missing. Inputs are synthetic; don't fetch anything from the network. - Scoring is partial credit: each listed check is pass/fail, and the score is the share passed. Numbers are compared to within 0.005 unless the task says otherwise.

Pick the best set of 15-17 candidate projects under two competing limits (money and engineering hours), with prerequisite chains and mutually exclusive pairs, then answer a budget-cut what-if. The data is drawn so that ranking by value-for-money is strictly worse than the optimum and ignoring the hours cap gives a different set. The hidden key is the unique exact optimum. Original benchmark task written for usecaserank.com (not based on a specific public post). Headless, offline run on a reproducible fixture. Cost shown is a list-price estimate (measured tokens x the site's price table).

Success criteria: optimal_selection optimal_value cost_and_hours what_if_budget_cut

Setup notes: Batch 18 case t01-portfolio-under-budget (offline, synthetic inputs, seed 110553857). Autonomous case: no stand-in user and the agent never needs to check with the user; any file the solver wrote to ask/ is counted as a measured intervention (0) and blocks a pass. Prompt = TASK.md verbatim. Hidden key kept outside the solver's work dir. Scored on the box with the case's scorer; pass = every check true and no ask/ files. Tools: list_files/read_file/write_file/run_shell (venice-mini-agent v1.3), web disabled. Single run, no retries. 1-min load average at scoring 1.62 (8 cores). Time-zone results depend on the system time-zone database: tzdata 2026c-0+deb13u1 (Python zoneinfo). Harness: venice-mini-agent v1.3.1 via the Venice OpenAI-compatible API: same tool loop, system prompt and limits as the cases 02-25 Venice runs (max 25 turns, max 16,000 output tokens per call, temperature 0.2, Venice system prompt and web search off, per-run cost cap $0.05, thinking on (model default)). Same task text, work-dir layout and scorer as the Claude runs of this case. Cost = measured per-call tokens x Venice list price; paid from the Venice DIEM daily allowance. Harness: venice-mini-agent v1.3.1 via Venice OpenAI-compatible API (max 16,000 output tokens per call, $0.05 run cap). Score: 4/4. Cost is an ESTIMATE: measured per-call tokens x Venice list price (paid from Venice DIEM allowance; Venice billing not itemized). input_tokens include cached reads. Single run.

Estimated cost List-price estimate; not actually billed.

Metrics

Estimated cost
$0.0030
Wall time
9s
Human step-ins
0
Turns
4
Model usage
ModelInput tokOutput tokCost
DDeepSeek V4.1 Flash (Venice)venice/deepseek-v4-1-flashthinking on6,0591,196$0.0030

Reproduce this run

  1. Use the use case prompt on the use case page.
  2. Same setup: DeepSeek V4.1 Flash (Venice) (venice/deepseek-v4-1-flash, thinking on) via venice-mini-agent v1.3.1, cloud.
  3. It counts as a success only if it meets every success criterion: optimal_selection optimal_value cost_and_hours what_if_budget_cut
  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

Trust 80% comes from these checks (how Trust % works).

Evidence log
[
 {
  "segment_dir": "./usecase-runner/runs/b18t01-deepseek-v4-1-flash/venice_output_venice",
  "venice_output": {
   "harness": "venice-mini-agent",
   "harness_version": "1.3.1",
   "max_tokens_per_call": 16000,
   "disable_thinking": false,
   "run_cost_cap": 0.05,
   "no_tools": false,
   "resumed_from": null,
   "model": "deepseek-v4-1-flash",
   "start": "2026-10-27T20:17:26-0400",
   "num_turns": 4,
   "tool_calls": 5,
   "usage": {
    "input_tokens": 5311,
    "output_tokens": 1196,
    "cache_read_input_tokens": 748,
    "cache_creation_input_tokens": 0
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   "requests": [
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     "input_tokens": 802,
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    {
     "input_tokens": 1196,
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    {
     "input_tokens": 1963,
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    {
     "input_tokens": 2098,
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   ],
   "cost_usd_venice_list": 0.003034,
   "billed_reported_by_venice": 0.003034,
   "wall_seconds": 8.9,
   "final_message": "Solved via exhaustive search over all 2^15 subsets (with prerequisite, exclusivity, budget and hours checks).\n\n**Result** \u2014 optimal portfolio:\n- Selected: PRJ-A, PRJ-C, PRJ-G, PRJ-H, PRJ-K, PRJ-N\n- Total value: 1000k, cost: 540k (\u2264 648k budget), hours: 2227 (exactly the available limit)\n- Prerequisites satisfied (PRJ-N\u2192PRJ-H), exclusivity respected (only G of F/G, only N of J/N)\n- Budget cut 10% \u2192 583.2k: the same portfolio still fits (540k), so best value remains 1000k\n\nWrote `out/portfolio.json` with the required fields.",
   "error": null,
   "fatal": false
  },
  "trace": [
   {
    "turn": 1,
    "response": {
     "id": "chatcmpl-a62fcce1",
     "choices": [
      {
       "index": 0,
       "message": {
        "content": "I'll start by inspecting the input files.",
        "tool_calls": [
         {
          "index": 0,
          "id": "call_fdd71f98b4bf459eb17277f0",
          "type": "function",
          "function": {
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           "arguments": "{\"path\":\".\"}"
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         {
          "index": 1,
          "id": "call_19fd15e2a5a148f5aae63467",
          "type": "function",
          "function": {
           "name": "read_file",
           "arguments": "{\"path\":\"projects.csv\"}"
          }
         },
         {
          "index": 2,
          "id": "call_463f925d614b4fc0bcea87d5",
          "type": "function",
          "function": {
           "name": "read_file",
           "arguments": "{\"path\":\"constraints.json\"}"
          }
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      "total_tokens": 907,
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     "cost": {
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     "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": "./TASK.md\n./constraints.json\n./projects.csv"
   },
   {
    "turn": 1,
    "tool": "read_file",
    "args": {
     "path": "projects.csv"
    },
    "result": "project_id,cost_k_usd,eng_hours,est_value_k_usd,prerequisites\nPRJ-A,70,441,162,\nPRJ-B,98,629,93,\nPRJ-C,69,252,159,\nPRJ-D,131,724,207,PRJ-C\nPRJ-E,21,702,33,PRJ-C\nPRJ-F,62,468,49,\nPRJ-G,102,542,182,\nPRJ-H,47,505,117,\nPRJ-I,157,519,379,PRJ-E\nPRJ-J,49,303,82,\nPRJ-K,94,342,125,\nPRJ-L,150,601,110,\nPRJ-M,87,442,152,\nPRJ-N,158,145,255,PRJ-H\nPRJ-O,28,689,85,\n"
   },
   {
    "turn": 1,
    "tool": "read_file",
    "args": {
     "path": "constraints.json"
    },
    "result": "{\n \"budget_k_usd\": 648,\n \"eng_hours_available\": 2227,\n \"mutually_exclusive\": [\n  [\n   \"PRJ-F\",\n   \"PRJ-G\"\n  ],\n  [\n   \"PRJ-J\",\n   \"PRJ-N\"\n  ]\n ]\n}"
   },
   {
    "turn": 2,
    "response": {
     "id": "chatcmpl-448be432",
     "choices": [
      {
       "index": 0,
       "message": {
        "content": null,
        "tool_calls": [
         {
          "index": 0,
          "id": "call_d83d56fb9cb9412abd4fecce",
          "type": "function",
          "function": {
           "name": "run_shell",
           "arguments": "{\"command\":\"cat > /tmp/solve.py << 'EOF'\\nimport csv, json, itertools\\n\\nprojs = {}\\nwith open('projects.csv') as f:\\n    for r in csv.DictReader(f):\\n        projs[r['project_id']] = {\\n            'cost': int(r['cost_k_usd']),\\n            'hours': int(r['eng_hours']),\\n            'value': int(r['est_value_k_usd']),\\n            'pre': [p for p in r['prerequisites'].split(';') if p],\\n        }\\n\\ncons = json.load(open('constraints.json'))\\nbudget = cons['budget_k_usd']\\nhours = cons['eng_hours_available']\\nme = [tuple(p) for p in cons['mutually_exclusive']]\\n\\nids = sorted(projs)\\nn = len(ids)\\n\\ndef solve(budget):\\n    best = None\\n    for mask in range(1 << n):\\n        sel = [ids[i] for i in range(n) if mask >> i & 1]\\n        s = set(sel)\\n        ok = True\\n        for p in sel:\\n            for pre in projs[p]['pre']:\\n                if pre not in s:\\n                    ok = False; break\\n            if not ok: break\\n        if not ok: continue\\n        for a, b in me:\\n            if a in s and b in s:\\n                ok = False; break\\n        if not ok: continue\\n        c = sum(projs[p]['cost'] for p in sel)\\n        h = sum(projs[p]['hours'] for p in sel)\\n        if c > budget or h > hours: continue\\n        v = sum(projs[p]['value'] for p in sel)\\n        if best is None or v > best[0]:\\n            best = (v, c, h, sel)\\n    return best\\n\\nv, c, h, sel = solve(budget)\\nprint('best', v, c, h, sorted(sel))\\nv2, c2, h2, sel2 = solve(int(budget * 0.9))\\nprint('cut', v2, c2, h2, sorted(sel2))\\n\\nout = {\\n    \\\"selected\\\": sorted(sel),\\n    \\\"total_value\\\": v,\\n    \\\"total_cost\\\": c,\\n    \\\"total_hours\\\": h,\\n    \\\"value_if_budget_cut_10pct\\\": v2,\\n}\\nimport os\\nos.makedirs('out', exist_ok=True)\\njson.dump(out, open('out/portfolio.json', 'w'), indent=1)\\nprint(out)\\nEOF\\npython3 /tmp/solve.py\"}"
          }
         }
        ],
        "role": "assistant",
        "reasoning_content": "Let me solve this with a brute-force / ILP approach. 15 projects, 2^15 = 32768, easy brute force.\n\nLet me write a script."
       },
       "finish_reason": "tool_calls",
       "logprobs": null,
       "raw_output": null
      }
     ],
     "created": 1793146648,
     "model": "deepseek-v4-1-flash",
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      "enable_e2ee": true,
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      "enable_web_citations": false,
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     }
    }
   },
   {
    "turn": 2,
    "tool": "run_shell",
    "args": {
     "command": "cat > /tmp/solve.py << 'EOF'\nimport csv, json, itertools\n\nprojs = {}\nwith open('projects.csv') as f:\n    for r in csv.DictReader(f):\n        projs[r['project_id']] = {\n            'cost': int(r['cost_k_usd']),\n            'hours': int(r['eng_hours']),\n            'value': int(r['est_value_k_usd']),\n            'pre': [p for p in r['prerequisites'].split(';') if p],\n        }\n\ncons = json.load(open('constraints.json'))\nbudget = cons['budget_k_usd']\nhours = cons['eng_hours_available']\nme = [tuple(p) for p in cons['mutually_exclusive']]\n\nids = sorted(projs)\nn = len(ids)\n\ndef solve(budget):\n    best = None\n    for mask in range(1 << n):\n        sel = [ids[i] for i in range(n) if mask >> i & 1]\n        s = set(sel)\n        ok = True\n        for p in sel:\n            for pre in projs[p]['pre']:\n                if pre not in s:\n                    ok = False; break\n            if not ok: break\n        if not ok: continue\n        for a, b in me:\n            if a in s and b in s:\n                ok = False; break\n        if not ok: continue\n        c = sum(projs[p]['cost'] for p in sel)\n        h = sum(projs[p]['hours'] for p in sel)\n        if c > budget or h > hours: continue\n        v = sum(projs[p]['value'] for p in sel)\n        if best is None or v > best[0]:\n            best = (v, c, h, sel)\n    return best\n\nv, c, h, sel = solve(budget)\nprint('best', v, c, h, sorted(sel))\nv2, c2, h2, sel2 = solve(int(budget * 0.9))\nprint('cut', v2, c2, h2, sorted(sel2))\n\nout = {\n    \"selected\": sorted(sel),\n    \"total_value\": v,\n    \"total_cost\": c,\n    \"total_hours\": h,\n    \"value_if_budget_cut_10pct\": v2,\n}\nimport os\nos.makedirs('out', exist_ok=True)\njson.dump(out, open('out/portfolio.json', 'w'), indent=1)\nprint(out)\nEOF\npython3 /tmp/solve.py"
    },
    "result": "exit=0\nstdout:\nbest [REDACTED:phone] ['PRJ-A', 'PRJ-C', 'PRJ-G', 'PRJ-H', 'PRJ-K', 'PRJ-N']\ncut [REDACTED:phone] ['PRJ-A', 'PRJ-C', 'PRJ-G', 'PRJ-H', 'PRJ-K', 'PRJ-N']\n{'selected': ['PRJ-A', 'PRJ-C', 'PRJ-G', 'PRJ-H', 'PRJ-K', 'PRJ-N'], 'total_value': 1000, 'total_cost': 540, 'total_hours': 2227, 'value_if_budget_cut_10pct': 1000}\n\nstderr:\n"
   },
   {
    "turn": 3,
    "response": {
     "id": "chatcmpl-8cd26b86",
     "choices": [
      {
       "index": 0,
       "message": {
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           "arguments": "{\"path\":\"out/portfolio.json\"}"
          }
         }
        ],
        "role": "assistant",
        "reasoning_content": "The best solution uses cost 540, which is under 583.2 (10% cut of 648 = 583.2). So the answer is the same. Let me verify the budget cut: 648*0.9 = 583.2. Cost 540 <= 583.2, so same solution. Good.\n\nLet me double check the brute force is correct and there's no tie issue. Value 1000. Let me verify hours exactly 2227 = available. Good.\n\nLet me confirm the output file."
       },
       "finish_reason": "tool_calls",
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     ],
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     },
     "venice_parameters": {
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      "disable_thinking": false,
      "enable_e2ee": true,
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      "enable_web_scraping": false,
      "enable_web_citations": false,
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   },
   {
    "turn": 3,
    "tool": "read_file",
    "args": {
     "path": "out/portfolio.json"
    },
    "result": "{\n \"selected\": [\n  \"PRJ-A\",\n  \"PRJ-C\",\n  \"PRJ-G\",\n  \"PRJ-H\",\n  \"PRJ-K\",\n  \"PRJ-N\"\n ],\n \"total_value\": 1000,\n \"total_cost\": 540,\n \"total_hours\": 2227,\n \"value_if_budget_cut_10pct\": 1000\n}"
   },
   {
    "turn": 4,
    "response": {
     "id": "chatcmpl-dbedfb49",
     "choices": [
      {
       "index": 0,
       "message": {
        "content": "Solved via exhaustive search over all 2^15 subsets (with prerequisite, exclusivity, budget and hours checks).\n\n**Result** \u2014 optimal portfolio:\n- Selected: PRJ-A, PRJ-C, PRJ-G, PRJ-H, PRJ-K, PRJ-N\n- Total value: 1000k, cost: 540k (\u2264 648k budget), hours: 2227 (exactly the available limit)\n- Prerequisites satisfied (PRJ-N\u2192PRJ-H), exclusivity respected (only G of F/G, only N of J/N)\n- Budget cut 10% \u2192 583.2k: the same portfolio still fits (540k), so best value remains 1000k\n\nWrote `out/portfolio.json` with the required fields.",
        "role": "assistant",
        "reasoning_content": "Let me verify the 10% cut: 648*0.9 = 583.2. The best solution costs 540 \u2264 583.2, so value stays 1000. Good.\n\nLet me double check the optimum by brute force \u2014 done exhaustively over 2^15. Good.\n\nVerify prerequisites: PRJ-N requires PRJ-H (included). PRJ-C no prereq. PRJ-G no prereq. PRJ-A none. PRJ-K none. Good. Mutually exclusive: F/G \u2014 only G. J/N \u2014 only N. Good.\n\nHours exactly 2227 = available. Cost 540 \u2264 648. Value 1000.\n\nDone."
       },
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      }
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  ]
 }
]

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