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Qwen3 Coder 480B Turbo (Venice) (thinking on) on Scale a recipe to a new serving count and convert it to metric

QQwen3 Coder 480B Turbo (Venice)thinking on · venice-mini-agent v1.3.1 · cloud · 2026-10-28 · by @bobsiopener

Trust 80%Fully autonomousfail · 0 retries
Estimated cost
$0.0018
Wall time
19s
Human step-ins
0
Outcome
Fail

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Summary

Exact prompt

# Scale a recipe and convert it to metric Inputs: `recipe.json` (original servings and ingredients), `request.json` (target servings), `conversions.json` (unit factors). Rules: - Scale every quantity by target servings / original servings. - Quantities may be written as fractions or mixed numbers such as "1 1/2". - Convert volume units to ml and weight units to g using conversions.json; amounts already in g or ml keep their unit. - Round metric amounts of 10 or more to a whole number, and amounts below 10 to 1 decimal place, half-up. Decide using the exact scaled, converted amount. - Count items (unit "each") are rounded UP to a whole number and keep the unit "each". - total_g is the sum of the rounded g amounts and total_ml the sum of the rounded ml amounts. Write `out/scaled.json`: `{"servings": <target>, "ingredients": {"<name>": {"amount": <number>, "unit": "g" | "ml" | "each"}, ...}, "total_g": <number>, "total_ml": <number>}` with every ingredient from recipe.json, keyed by its name. ## 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.

Scale a 9-12 ingredient recipe written in cups, spoons, ounces, sticks and fractions to a new number of servings and convert it to grams and millilitres. Amounts follow a two-tier half-up rounding rule and count items round up. Inputs are drawn fresh per seed, with draws near rounding ties or the 10-unit threshold rejected. 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: all_ingredients_and_units volume_amounts_ml weight_amounts_g small_amounts_one_decimal count_items_rounded_up fraction_quantities_parsed totals

Setup notes: Batch 16 case r01-recipe-scaling (offline, synthetic inputs, seed 2838018176). 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 0.71 (8 cores). 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: 2/7. 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
$0.0018
Wall time
19s
Human step-ins
0
Turns
6
Model usage
ModelInput tokOutput tokCost
QQwen3 Coder 480B Turbo (Venice)venice/qwen3-coder-480b-a35b-instruct-turbothinking on7,802699$0.0018

Reproduce this run

  1. Use the use case prompt on the use case page.
  2. Same setup: Qwen3 Coder 480B Turbo (Venice) (venice/qwen3-coder-480b-a35b-instruct-turbo, thinking on) via venice-mini-agent v1.3.1, cloud.
  3. It counts as a success only if it meets every success criterion: all_ingredients_and_units volume_amounts_ml weight_amounts_g small_amounts_one_decimal count_items_rounded_up fraction_quantities_parsed totals
  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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   "error": null,
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        "content": "I'll solve this step by step, scaling the recipe and converting units to metric.\n\nFirst, let me check what files are available:\n\n",
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    "turn": 3,
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    "result": "{\n \"servings\": 7\n}"
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    "result": "{\n \"volume_ml\": {\n  \"tsp\": 5,\n  \"tbsp\": 15,\n  \"cup\": 240,\n  \"fl oz\": 30\n },\n \"weight_g\": {\n  \"oz\": 28,\n  \"lb\": 454,\n  \"stick\": 113\n }\n}"
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        "role": "assistant",
        "content": "Now I'll create the solution. First, let me parse the recipe and convert all quantities to metric units, then scale them according to the requested servings.\n\n",
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           "arguments": "{\"path\": \"out/scaled.json\", \"content\": \"{\\n  \\\"servings\\\": 7,\\n  \\\"ingredients\\\": {\\n    \\\"lemon juice\\\": {\\n      \\\"amount\\\": 105,\\n      \\\"unit\\\": \\\"ml\\\"\\n    },\\n    \\\"parmesan\\\": {\\n      \\\"amount\\\": 66,\\n      \\\"unit\\\": \\\"g\\\"\\n    },\\n    \\\"brown sugar\\\": {\\n      \\\"amount\\\": 1120,\\n      \\\"unit\\\": \\\"ml\\\"\\n    },\\n    \\\"yeast\\\": {\\n      \\\"amount\\\": 265,\\n      \\\"unit\\\": \\\"g\\\"\\n    },\\n    \\\"butter\\\": {\\n      \\\"amount\\\": 9.3,\\n      \\\"unit\\\": \\\"g\\\"\\n    },\\n    \\\"rolled oats\\\": {\\n      \\\"amount\\\": 292,\\n      \\\"unit\\\": \\\"ml\\\"\\n    },\\n    \\\"water\\\": {\\n      \\\"amount\\\": 2.3,\\n      \\\"unit\\\": \\\"ml\\\"\\n    },\\n    \\\"olive oil\\\": {\\n      \\\"amount\\\": 3.5,\\n      \\\"unit\\\": \\\"ml\\\"\\n    },\\n    \\\"rice\\\": {\\n      \\\"amount\\\": 9,\\n      \\\"unit\\\": \\\"ml\\\"\\n    },\\n    \\\"salt\\\": {\\n      \\\"amount\\\": 9,\\n      \\\"unit\\\": \\\"ml\\\"\\n    },\\n    \\\"lemons\\\": {\\n      \\\"amount\\\": 3,\\n      \\\"unit\\\": \\\"each\\\"\\n    }\\n  },\\n  \\\"total_g\\\": 340,\\n  \\\"total_ml\\\": 1540\\n}\"}"
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   {
    "turn": 5,
    "tool": "write_file",
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     "path": "out/scaled.json",
     "content": "{\n  \"servings\": 7,\n  \"ingredients\": {\n    \"lemon juice\": {\n      \"amount\": 105,\n      \"unit\": \"ml\"\n    },\n    \"parmesan\": {\n      \"amount\": 66,\n      \"unit\": \"g\"\n    },\n    \"brown sugar\": {\n      \"amount\": 1120,\n      \"unit\": \"ml\"\n    },\n    \"yeast\": {\n      \"amount\": 265,\n      \"unit\": \"g\"\n    },\n    \"butter\": {\n      \"amount\": 9.3,\n      \"unit\": \"g\"\n    },\n    \"rolled oats\": {\n      \"amount\": 292,\n      \"unit\": \"ml\"\n    },\n    \"water\": {\n      \"amount\": 2.3,\n      \"unit\": \"ml\"\n    },\n    \"olive oil\": {\n      \"amount\": 3.5,\n      \"unit\": \"ml\"\n    },\n    \"rice\": {\n      \"amount\": 9,\n      \"unit\": \"ml\"\n    },\n    \"salt\": {\n      \"amount\": 9,\n      \"unit\": \"ml\"\n    },\n    \"lemons\": {\n      \"amount\": 3,\n      \"unit\": \"each\"\n    }\n  },\n  \"total_g\": 340,\n  \"total_ml\": 1540\n}"
    },
    "result": "wrote 780 chars"
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 }
]

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