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DeepSeek V4.1 Flash (Venice) (thinking on) on Read a synthetic annual-report excerpt and compute financial ratios

DDeepSeek V4.1 Flash (Venice)thinking on · venice-mini-agent v1.3.1 · cloud · 2026-10-23 · by @bobsiopener

Trust 80%Fully autonomoussuccess · first try
Estimated cost
$0.0042
Wall time
14s
Human step-ins
0
Outcome
Pass

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Rescored on 2026-10-28. Previous score: 93.3 / 100, outcome: success. See the previous run.

Summary

Exact prompt

# Read an annual-report excerpt and compute financial ratios `annual_report_excerpt.md` is an excerpt from a **fictional** company's annual report (statements plus notes). Read it and write `ratios.json` with the 16 values below. You may compute by hand or with a script (Python 3 standard library only). Use only this document. Watch the units and the notes. ## Rules 1. Dollar amounts in the statements are in thousands unless a line says otherwise. Notes can state amounts in millions; convert them to thousands. 2. Where a note restates a prior-year amount, use the restated amount everywhere that amount (or a total that includes it) is used. "Average X" = (FY2025 year-end X + FY2024 year-end X) / 2. 3. Total debt = current portion of long-term debt + long-term debt (net of current portion) + finance lease obligations (Note 7). Operating lease liabilities are not debt. 4. Free cash flow = net cash provided by operating activities - purchases of property and equipment - capitalized internal-use software. 5. Definitions (FY2025 unless stated): - `current_ratio` = total current assets / total current liabilities - `quick_ratio` = (cash and equivalents + short-term investments + accounts receivable) / total current liabilities - `gross_margin`, `operating_margin`, `net_margin` = gross profit, operating income, net income / net sales - `effective_tax_rate` = provision for income taxes / income before income taxes - `roe` = net income / average stockholders' equity - `total_debt_thousands` (rule 3, at Dec 31, 2025), `debt_to_equity` = total debt / Dec 31, 2025 equity - `interest_coverage` = operating income / interest expense - `fcf_thousands` (rule 4), `fcf_margin` = free cash flow / net sales - `inventory_turnover` = cost of sales / average inventory - `dso_days` = average accounts receivable / net sales * 365 - `revenue_growth` = FY2025 net sales / FY2024 net sales - 1 - `eps_diluted` = net income / diluted weighted-average shares (dollars per share) 6. Ratios and margins are plain fractions (0.25, not 25%). ## Output `ratios.json`: one JSON object with exactly these keys: `current_ratio`, `quick_ratio`, `gross_margin`, `operating_margin`, `net_margin`, `effective_tax_rate`, `roe`, `total_debt_thousands`, `debt_to_equity`, `interest_coverage`, `fcf_thousands`, `fcf_margin`, `inventory_turnover`, `dso_days`, `revenue_growth`, `eps_diluted`. (That is 16 keys: the 15 ratios plus total debt.) ## Scoring Hidden checks (partial credit = fraction passed; all must pass). Tolerances: fractions and ratios within 0.0005; `total_debt_thousands` and `fcf_thousands` within 0.5; `dso_days` within 0.05; `eps_diluted` within 0.005. - `liquidity`: current_ratio, quick_ratio - `margins_and_tax`: gross_margin, operating_margin, net_margin, effective_tax_rate - `return_on_equity`: roe (needs the restated equity) - `debt_and_coverage`: total_debt_thousands, debt_to_equity, interest_coverage (needs the note in millions) - `free_cash_flow`: fcf_thousands, fcf_margin - `efficiency`: inventory_turnover (needs the restated inventory), dso_days - `growth_and_eps`: revenue_growth, eps_diluted

A restated prior-year inventory and equity in a note, finance-lease debt stated in millions inside a note, a non-GAAP distractor, and averages that need the restated column. 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).

These are synthetic test cases for comparing AI models, not financial advice.

Success criteria: 1. liquidity 2. margins_and_tax 3. return_on_equity 4. debt_and_coverage 5. free_cash_flow 6. efficiency 7. growth_and_eps

Setup notes: Use Case Scout batch 9 case j09-10k-ratio-extraction (offline fixture). Prepared with the case's setup script; hidden key/tests kept outside the agent's work dir. Prompt = TASK.md verbatim. Scored automatically with the scout's scorer. Tools: list_files/read_file/write_file/run_shell (venice-mini-agent v1.3), web disabled. Single run, no retries. 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 $0.0237, 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 (16000 max tokens/call, $0.0237 run cap). Score: 7/7. Cost is an ESTIMATE: measured per-call tokens x the site's list-price table (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
$0.0042
Wall time
14s
Human step-ins
0
Turns
4
Model usage
ModelInput tokOutput tokCost
DDeepSeek V4.1 Flash (Venice)venice/deepseek-v4-1-flashthinking on10,9201,680$0.0042

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: 1. liquidity 2. margins_and_tax 3. return_on_equity 4. debt_and_coverage 5. free_cash_flow 6. efficiency 7. growth_and_eps
  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
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   "start": "2026-10-23T01:12:40-0400",
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   "final_message": "Done. I read the excerpt and computed all 16 values, writing `ratios.json`.\n\nKey judgment calls applied:\n- **Restated FY2024 inventory** ($127,905k, not $131,455k) used for average inventory \u2192 inventory turnover 3.7237.\n- **Restated FY2024 equity** ($248,200k \u2212 $3,550k = $244,650k) used for average equity \u2192 ROE 0.26285.\n- **Total debt** = $12,500k current LTD + $148,000k LTD + $6,400k finance leases (Note 7, converted from $6.4M) = **$166,900k**; operating leases excluded.\n- **FCF** = $112,640k \u2212 $38,975k \u2212 $4,100k = **$69,565k**.\n- Ignored the non-GAAP adjusted operating income and segment figures.\n\nFinal values: current_ratio 2.40005, quick_ratio 1.24874, gross_margin 0.40189, operating_margin 0.11664, net_margin 0.08299, effective_tax_rate 0.22000, roe 0.26285, total_debt_thousands 166900, debt_to_equity 0.58072, interest_coverage 9.95362, fcf_thousands 69565, fcf_margin 0.08256, inventory_turnover 3.72372, dso_days 36.39582, revenue_growth 0.09246, eps_diluted 1.66290.",
   "error": null,
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        "content": "I'll start by reading the annual report excerpt.",
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    "result": "# Larkspur Outdoor Goods, Inc. - Annual Report excerpt (fiscal year ended December 31, 2025)\n\n*Fictional company. All figures are synthetic and were made up for this exercise.*\n\n## Item 7. Management's Discussion and Analysis (excerpt)\n\nNet sales grew on the strength of the trail-footwear line and the reopening of two distribution centers. Management also tracks a non-GAAP \"adjusted operating income\" of $112,400 thousand, which adds back restructuring and brand amortization; this measure is not used anywhere in the GAAP statements below.\n\nSegment net sales (in thousands): Footwear 391,220; Apparel 286,905; Equipment 164,490. Segment figures are shown for context only.\n\n## Item 8. Financial Statements\n\n### Consolidated Statements of Operations\n(in thousands, except per-share amounts)\n\n| | FY2025 | FY2024 |\n|---|---:|---:|\n| Net sales | 842,615 | 771,302 |\n| Cost of sales | 503,977 | 468,215 |\n| Gross profit | 338,638 | 303,087 |\n| Selling, general and administrative | 221,450 | 204,118 |\n| Research and development | 18,906 | 17,240 |\n| Operating income | 98,282 | 81,729 |\n| Interest expense | (9,874) | (10,512) |\n| Other income, net | 1,240 | 655 |\n| Income before income taxes | 89,648 | 71,872 |\n| Provision for income taxes | 19,723 | 15,812 |\n| Net income | 69,925 | 56,060 |\n| Weighted-average shares, basic (thousands) | 41,200 | 41,650 |\n| Weighted-average shares, diluted (thousands) | 42,050 | 42,300 |\n\n### Consolidated Balance Sheets\n(in thousands; FY2024 column as originally reported, see Note 4)\n\n| | Dec 31, 2025 | Dec 31, 2024 |\n|---|---:|---:|\n| Cash and cash equivalents | 61,340 | 48,905 |\n| Short-term investments | 15,000 | 22,500 |\n| Accounts receivable, net | 88,412 | 79,630 |\n| Inventories | 142,780 | 131,455 |\n| Prepaid expenses and other | 9,118 | 8,240 |\n| **Total current assets** | 316,650 | 290,730 |\n| Property and equipment, net | 204,500 | 196,300 |\n| Operating lease right-of-use assets | 38,200 | 41,000 |\n| Goodwill | 55,000 | 55,000 |\n| **Total assets** | 614,350 | 583,030 |\n| Accounts payable | 70,215 | 66,980 |\n| Accrued liabilities | 41,320 | 38,770 |\n| Current portion of long-term debt | 12,500 | 12,500 |\n| Current operating lease liabilities | 7,900 | 7,600 |\n| **Total current liabilities** | 131,935 | 125,850 |\n| Long-term debt, net of current portion | 148,000 | 160,500 |\n| Noncurrent operating lease liabilities | 32,400 | 35,600 |\n| Other long-term liabilities | 14,615 | 12,880 |\n| **Total stockholders' equity** | 287,400 | 248,200 |\n| **Total liabilities and equity** | 614,350 | 583,030 |\n\n### Consolidated Statement of Cash Flows (summary)\n(in thousands)\n\n| | FY2025 |\n|---|---:|\n| Net cash provided by operating activities | 112,640 |\n| Purchases of property and equipment | (38,975) |\n| Capitalized internal-use software | (4,100) |\n| Purchases of short-term investments, net of maturities | 7,500 |\n| Repayment of long-term debt | (12,500) |\n| Share repurchases | (29,580) |\n| Dividends paid | (14,920) |\n\n## Notes to th"
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           "name": "run_shell",
           "arguments": "{\"command\":\"cat > /tmp/calc.py << 'EOF'\\nimport json\\n# FY2025\\nca25=316650; cl25=131935\\ncash=61340; sti=15000; ar25=88412\\ngp=338638; oi=98282; ni=69925; sales25=842615; sales24=771302\\ntax=19723; pretax=89648\\neq25=287400; eq24=248200-3550\\ndebt=12500+148000+6400\\ninterest=9874\\ncfo=112640; capex=38975; sw=4100\\ncos=503977; inv25=142780; inv24=127905\\nar24=79630\\ndiluted=42050\\n\\nr={}\\nr['current_ratio']=ca25/cl25\\nr['quick_ratio']=(cash+sti+ar25)/cl25\\nr['gross_margin']=gp/sales25\\nr['operating_margin']=oi/sales25\\nr['net_margin']=ni/sales25\\nr['effective_tax_rate']=tax/pretax\\nr['roe']=ni/((eq25+eq24)/2)\\nr['total_debt_thousands']=debt\\nr['debt_to_equity']=debt/eq25\\nr['interest_coverage']=oi/interest\\nr['fcf_thousands']=cfo-capex-sw\\nr['fcf_margin']=(cfo-capex-sw)/sales25\\nr['inventory_turnover']=cos/((inv25+inv24)/2)\\nr['dso_days']=((ar25+ar24)/2)/sales25*365\\nr['revenue_growth']=sales25/sales24-1\\nr['eps_diluted']=ni/diluted\\nprint(json.dumps(r,indent=2))\\nwith open('ratios.json','w') as f: json.dump(r,f,indent=2)\\nEOF\\npython3 /tmp/calc.py\"}"
          }
         }
        ],
        "role": "assistant",
        "reasoning_content": "Let me compute carefully.\n\nRestated FY2024 inventory: 127,905 (down 3,550 from 131,455).\nRestated FY2024 total current assets: 290,730 - 3,550 = 287,180.\nRestated FY2024 total assets: 583,030 - 3,550 = 579,480.\nRestated FY2024 equity: 248,200 - 3,550 = 244,650.\n\nFY2025:\n- Total current assets = 316,650\n- Total current liabilities = 131,935\n- current_ratio = 316,650 / 131,935 = ?\n\nLet me compute with script.\n\nquick_ratio = (61,340 + 15,000 + 88,412) / 131,935 = 164,752 / 131,935.\n\ngross_margin = 338,638 / 842,615\noperating_margin = 98,282 / 842,615\nnet_margin = 69,925 / 842,615\neffective_tax_rate = 19,723 / 89,648\nroe = 69,925 / ((287,400 + 244,650)/2) = 69,925 / 266,025\n\ntotal_debt = 12,500 + 148,000 + finance lease 6,400 = 166,900\ndebt_to_equity = 166,900 / 287,400\ninterest_coverage = 98,282 / 9,874\nfcf = 112,640 - 38,975 - 4,100 = 69,565\nfcf_margin = 69,565 / 842,615\ninventory_turnover = 503,977 / ((142,780 + 127,905)/2) = 503,977 / 135,342.5\ndso_days = ((88,412 + 79,630)/2) / 842,615 * 365 = 84,021 / 842,615 * 365\nrevenue_growth = 842,615 / 771,302 - 1\neps_diluted = 69,925 / 42,050\n\nLet me compute."
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   {
    "turn": 2,
    "tool": "run_shell",
    "args": {
     "command": "cat > /tmp/calc.py << 'EOF'\nimport json\n# FY2025\nca25=316650; cl25=131935\ncash=61340; sti=15000; ar25=88412\ngp=338638; oi=98282; ni=69925; sales25=842615; sales24=771302\ntax=19723; pretax=89648\neq25=287400; eq24=248200-3550\ndebt=12500+148000+6400\ninterest=9874\ncfo=112640; capex=38975; sw=4100\ncos=503977; inv25=142780; inv24=127905\nar24=79630\ndiluted=42050\n\nr={}\nr['current_ratio']=ca25/cl25\nr['quick_ratio']=(cash+sti+ar25)/cl25\nr['gross_margin']=gp/sales25\nr['operating_margin']=oi/sales25\nr['net_margin']=ni/sales25\nr['effective_tax_rate']=tax/pretax\nr['roe']=ni/((eq25+eq24)/2)\nr['total_debt_thousands']=debt\nr['debt_to_equity']=debt/eq25\nr['interest_coverage']=oi/interest\nr['fcf_thousands']=cfo-capex-sw\nr['fcf_margin']=(cfo-capex-sw)/sales25\nr['inventory_turnover']=cos/((inv25+inv24)/2)\nr['dso_days']=((ar25+ar24)/2)/sales25*365\nr['revenue_growth']=sales25/sales24-1\nr['eps_diluted']=ni/diluted\nprint(json.dumps(r,indent=2))\nwith open('ratios.json','w') as f: json.dump(r,f,indent=2)\nEOF\npython3 /tmp/calc.py"
    },
    "result": "exit=0\nstdout:\n{\n  \"current_ratio\": 2.400045476939402,\n  \"quick_ratio\": 1.24873612005912,\n  \"gross_margin\": 0.401889356348985,\n  \"operating_margin\": 0.11663927179079414,\n  \"net_margin\": 0.08298570521531186,\n  \"effective_tax_rate\": 0.2200049080849545,\n  \"roe\": 0.2628512357861103,\n  \"total_debt_thousands\": 166900,\n  \"debt_to_equity\": 0.580723729993041,\n  \"interest_coverage\": 9.953615556005671,\n  \"fcf_thousands\": 69565,\n  \"fcf_margin\": 0.08255846382986298,\n  \"inventory_turnover\": 3.7237157581690896,\n  \"dso_days\": 36.395821341893985,\n  \"revenue_growth\": 0.09245794772994231,\n  \"eps_diluted\": 1.6629013079667063\n}\n\nstderr:\n"
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        "reasoning_content": "Let me verify the file was written and check a few things. Note 4: restated inventory 127,905, equity reduced by 3,550 \u2192 244,650. Also current assets and total assets restated, but we only use FY2025 current assets for current ratio. Good.\n\nLet me verify ratios.json exists."
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   {
    "turn": 3,
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    "args": {
     "path": "ratios.json"
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    "result": "{\n  \"current_ratio\": 2.400045476939402,\n  \"quick_ratio\": 1.24873612005912,\n  \"gross_margin\": 0.401889356348985,\n  \"operating_margin\": 0.11663927179079414,\n  \"net_margin\": 0.08298570521531186,\n  \"effective_tax_rate\": 0.2200049080849545,\n  \"roe\": 0.2628512357861103,\n  \"total_debt_thousands\": 166900,\n  \"debt_to_equity\": 0.580723729993041,\n  \"interest_coverage\": 9.953615556005671,\n  \"fcf_thousands\": 69565,\n  \"fcf_margin\": 0.08255846382986298,\n  \"inventory_turnover\": 3.7237157581690896,\n  \"dso_days\": 36.395821341893985,\n  \"revenue_growth\": 0.09245794772994231,\n  \"eps_diluted\": 1.6629013079667063\n}"
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       "message": {
        "content": "Done. I read the excerpt and computed all 16 values, writing `ratios.json`.\n\nKey judgment calls applied:\n- **Restated FY2024 inventory** ($127,905k, not $131,455k) used for average inventory \u2192 inventory turnover 3.7237.\n- **Restated FY2024 equity** ($248,200k \u2212 $3,550k = $244,650k) used for average equity \u2192 ROE 0.26285.\n- **Total debt** = $12,500k current LTD + $148,000k LTD + $6,400k finance leases (Note 7, converted from $6.4M) = **$166,900k**; operating leases excluded.\n- **FCF** = $112,640k \u2212 $38,975k \u2212 $4,100k = **$69,565k**.\n- Ignored the non-GAAP adjusted operating income and segment figures.\n\nFinal values: current_ratio 2.40005, quick_ratio 1.24874, gross_margin 0.40189, operating_margin 0.11664, net_margin 0.08299, effective_tax_rate 0.22000, roe 0.26285, total_debt_thousands 166900, debt_to_equity 0.58072, interest_coverage 9.95362, fcf_thousands 69565, fcf_margin 0.08256, inventory_turnover 3.72372, dso_days 36.39582, revenue_growth 0.09246, eps_diluted 1.66290.",
        "role": "assistant",
        "reasoning_content": "Let me verify a few key items.\n\n- Restated equity FY2024: 248,200 - 3,550 = 244,650. Average = (287,400+244,650)/2 = 266,025. ROE = 69,925/266,025 = 0.26285. \u2713\n- Total debt: 12,500 + 148,000 + 6,400 = 166,900. \u2713\n- Inventory turnover: 503,977 / ((142,780+127,905)/2) = 503,977/135,342.5 = 3.7237. \u2713\n- DSO: avg AR = (88,412+79,630)/2 = 84,021; /842,615*365 = 36.396. \u2713\n- FCF: 112,640 - 38,975 - 4,100 = 69,565. \u2713\n\nAll good."
       },
       "finish_reason": "stop",
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       "raw_output": null
      }
     ],
     "created": 1792732371,
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     "venice_parameters": {
      "strip_thinking_response": false,
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      "enable_e2ee": true,
      "enable_web_search": "off",
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]

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