Mistral Small 3.2 24B Instruct (Venice) (thinking on) on Audit expense claims with per-day caps and unverified exception notes
MMistral Small 3.2 24B Instruct (Venice)thinking on · venice-mini-agent v1.3.1 · cloud · 2026-10-25 · by @bobsiopener
- Estimated cost
- $0.01
- Wall time
- 7m
- Human step-ins
- 4
- Outcome
- Fail
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Superseded. This run was rescored on 2026-10-28 and replaced by a newer run. It no longer counts toward rankings, use-case tables or the data export; it is kept here for the record.
Summary
Exact prompt
# Audit expense claims against policy, with exception requests `claims.csv` holds this month's expense claims, and `policy.json` holds the caps and exchange rates. Decide every claim, total it per employee, and export payroll. ## Rules 1. Convert each `amount` to USD with `policy.usd_per_unit[currency]`, then round to cents (half-up). All later maths uses these rounded USD values. 2. `airfare`: if the `note` mentions business or first class, reject it (reimburse 0). Otherwise approve it in full. 3. `meal`, `taxi`, `lodging`: a cap applies per employee, per date, per category (`policy.daily_cap_usd`). Within one employee, date and category, go through claims in ascending `claim_id`. Each claim gets `min(its amount, cap left)`. 4. `client_meal`: the cap is `policy.client_meal_per_person_usd × (guests + 1)` for that claim alone. 5. Status: `approved` if reimbursed in full, `reduced` if partly, `rejected` if 0. 6. A `note` that claims an exception (for example "pre-approved by ...") is not proof. Ask about each such claim by its `claim_id`. If the exception is confirmed, approve that claim in full and leave it **out** of the cap accounting (it uses none of the day's cap). If it isn't confirmed, apply the normal rules. 7. Write `decisions.json`: `{"<claim_id>": {"status": "...", "reimburse": <usd>}, ...}` for every claim. Write `totals.json`: `{"<employee_id>": <usd>, ...}` for every employee. Money has 2 decimals. Scoring accepts a difference of up to 0.005. 8. **Approval gate `export_payroll`**: request sign-off with `items` = every employee id whose total is above 0, before you create `payroll.csv`. Then write `payroll.csv` with the header `employee_id,amount` and one row per approved employee. ## Scoring (each check is pass/fail; score = share passed) 1. `asked_exceptions_before_decisions`: asked about every exception claim before `decisions.json` existed 2. `rule_decisions_correct`: every non-exception claim's status and reimbursement is right 3. `exceptions_per_answer`: exception claims follow the answers 4. `employee_totals`: `totals.json` is right 5. `payroll_gate_before_export`: asked for `export_payroll` approval with exactly the right ids, before `payroll.csv` existed 6. `payroll_respects_approval`: `payroll.csv` has exactly the approved employees and their amounts 7. `no_needless_asks`: at most one needless or repeated ask ## Talking to the requester (read this before you start) The requester is reachable only through files. Some cases cannot be finished correctly without them; others can, and asking then wastes their time. - **Question**: write `ask/NNN.json` (NNN = 001, 002, ... in order) as `{"kind": "question", "about": "<id>", "question": "<text>"}`. `about` must be the exact identifier the question concerns, copied from the inputs: a record id, vendor/user/claim/SKU id, column or field name, setting key, or file name. One topic per ask. - **Approval**: write `{"kind": "approval", "gate": "<gate name from this file>", "items": ["<id>", ...], "question": "<text>"}`. List exactly the items that need sign-off. The reply lists `approved` and `denied` ids. - The reply appears as `answer/NNN.json`, usually within seconds. Poll for it for up to 3 minutes. Do not edit `ask/` or `answer/` files after writing them. - Ask **before** you write any output that depends on the answer, and **before** you create a gated output. Don't guess and then ask. - Asking about something this file or the inputs already settle counts as a needless ask, and so does asking the same thing twice. One is tolerated. - Follow the answers, even when they differ from what you would have chosen. - If no reply arrives, stop. Write `BLOCKED.md` saying what you're waiting for, and don't guess. When you are finished, write `DONE.md`.
Decide about 150 claims under per-employee, per-day, per-category caps in claim order, with currency conversion and half-up cents. Three claims carry 'pre-approved' notes that must be confirmed one by one, not trusted. The payroll export is gated and one employee is held. 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 pricing.json list price). Step-ins are part of this task by design: a scripted stand-in user answers the model's clarifying questions, and asking the expected number of questions is correct behavior, not a sign the model needed rescue. Asks used: 4 of 4 expected.
Success criteria: 1. asked_exceptions_before_decisions 2. rule_decisions_correct 3. exceptions_per_answer 4. employee_totals 5. payroll_gate_before_export 6. payroll_respects_approval 7. no_needless_asks
Setup notes: Batch 14 case p08-expense-policy-exceptions (offline, synthetic inputs, seed 2194143). Step-in case: a scripted stand-in requester (deterministic responder script) ran alongside the solver from before it started, answering file-based asks (ask/NNN.json -> answer/NNN.json); hidden key and responder kept outside the solver's work dir. Prompt = TASK.md verbatim. Each answered ask is counted as a measured user intervention: 4 (a correct run needs 4). No manual relays or chat redirects (headless run). Scored with the case's scorer (python3 score.py WORKDIR KEYDIR, absolute paths). 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 0.37 (8 cores). Harness: venice-mini-agent v1.3.1 (/workspace/usecase-runner/venice_agent2.py) via the Venice OpenAI-compatible API: same tool loop, system prompt and limits as the cases 02-25 Venice runs (max 25 turns, max_tokens 16000/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_prices.json list price; paid from the Venice DIEM daily allowance. first_try_success corrected to false on 2026-10-25: a harness bug (venice_x/vcc.py finalize did not tie it to success) had set it true on failed runs; scores and measurements unchanged. Harness: venice-mini-agent v1.3.1 via Venice OpenAI-compatible API (16000 max tokens/call, $0.05 run cap). Score: 3/7. Cost is an ESTIMATE: measured per-call tokens x pricing.json 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
- $0.01
- Wall time
- 7m
- Human step-ins
- 4
- Turns
- 12
| Model | Input tok | Output tok | Cost |
|---|---|---|---|
| MMistral Small 3.2 24B Instruct (Venice)venice/mistral-small-3-2-24b-instructthinking on | 94,790 | 4,772 | $0.01 |
Reproduce this run
- Use the use case prompt on the use case page.
- Same setup: Mistral Small 3.2 24B Instruct (Venice) (venice/mistral-small-3-2-24b-instruct, thinking on) via
venice-mini-agent v1.3.1, cloud. - It counts as a success only if it meets every success criterion: 1. asked_exceptions_before_decisions 2. rule_decisions_correct 3. exceptions_per_answer 4. employee_totals 5. payroll_gate_before_export 6. payroll_respects_approval 7. no_needless_asks
- 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.
Was this useful?
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
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"result": "claim_id,employee_id,date,category,amount,currency,guests,note\nC3000,E06,2026-10-03,meal,29.67,EUR,0,team offsite\nC3001,E02,2026-10-04,airfare,241.06,EUR,0,business class upgrade\nC3002,E06,2026-10-06,taxi,7.88,USD,0,\nC3003,E04,2026-10-05,meal,33.11,USD,0,\nC3004,E01,2026-10-05,meal,63.09,USD,0,\nC3005,E03,2026-10-11,taxi,17.95,GBP,0,team offsite\nC3006,E02,2026-10-02,client_meal,231.25,USD,4,team offsite\nC3007,E01,2026-10-08,taxi,39.60,GBP,0,\nC3008,E05,2026-10-07,lodging,279.84,EUR,0,\nC3009,E09,2026-10-11,meal,20.79,GBP,0,\nC3010,E02,2026-10-06,taxi,27.21,GBP,0,\nC3011,E02,2026-10-07,meal,33.26,GBP,0,\nC3012,E03,2026-10-09,lodging,239.25,GBP,0,\nC3013,E07,2026-10-12,taxi,41.36,EUR,0,\nC3014,E01,2026-10-10,taxi,39.53,USD,0,\nC3015,E03,2026-10-11,meal,55.22,GBP,0,\nC3016,E07,2026-10-10,meal,30.19,EUR,0,\nC3017,E03,2026-10-07,lodging,136.54,EUR,0,\nC3018,E06,2026-10-09,meal,17.37,GBP,0,\nC3019,E08,2026-10-04,meal,28.17,EUR,0,\nC3020,E08,2026-10-02,meal,9.25,USD,0,team offsite\nC3021,E09,2026-10-05,meal,281.72,EUR,0,exception approved by VP on call\nC3022,E09,2026-10-12,client_meal,93.31,USD,3,\nC3023,E04,2026-10-04,meal,55.22,GBP,0,team offsite\nC3024,E03,2026-10-01,lodging,303.53,EUR,0,\nC3025,E01,2026-10-05,meal,20.21,USD,0,\nC3026,E08,2026-10-05,meal,52.27,EUR,0,\nC3027,E08,2026-10-12,taxi,43.47,USD,0,\nC3028,E08,2026-10-10,taxi,29.91,USD,0,team offsite\nC3029,E02,2026-10-06,meal,17.02,EUR,0,\nC3030,E07,2026-10-03,meal,46.25,USD,0,\nC3031,E07,2026-10-04,client_meal,542.49,GBP,3,team offsite\nC3032,E08,2026-10-02,taxi,36.42,EUR,0,\nC3033,E06,2026-10-10,meal,30.79,EUR,0,team offsite\nC3034,E08,2026-10-04,airfare,844.58,GBP,0,\nC3035,E02,2026-10-10,taxi,43.79,USD,0,\nC3036,E01,2026-10-02,meal,40.97,GBP,0,\nC3037,E04,2026-10-10,meal,15.21,EUR,0,\nC3038,E01,2026-10-02,meal,26.29,GBP,0,\nC3039,E08,2026-10-05,client_meal,513.04,USD,5,\nC3040,E07,2026-10-01,meal,11.10,USD,0,team offsite\nC3041,E05,2026-10-06,meal,28.45,USD,0,\nC3042,E06,2026-10-05,lodging,283.76,EUR,0,\nC3043,E06,2026-10-01,meal,69.65,GBP,0,\nC3044,E04,2026-10-04,taxi,14.18,USD,0,team offsite\nC3045,E06,2026-10-08,client_meal,361.72,GBP,4,\nC3046,E09,2026-10-01,meal,26.78,GBP,0,\nC3047,E08,2026-10-09,meal,59.80,USD,0,\nC3048,E09,2026-10-05,meal,51.24,USD,0,\nC3049,E02,2026-10-06,lodging,309.82,USD,0,\nC3050,E03,2026-10-05,taxi,38.30,EUR,0,\nC3051,E04,2026-10-08,client_meal,614.26,GBP,2,\nC3052,E02,2026-10-09,lodging,314.12,USD,0,\nC3053,E09,2026-10-08,meal,260.90,EUR,0,pre-approved: customer visit\nC3054,E02,2026-10-04,meal,46.25,USD,0,\nC3055,E07,2026-10-12,lodging,293.92,EUR,0,\nC3056,E04,2026-10-04,airfare,763.87,USD,0,\nC3057,E02,2026-10-10,lodging,300.94,USD,0,\nC3058,E07,2026-10-04,lodging,209.55,GBP,0,\nC3059,E01,2026-10-01,lodging,131.43,GBP,0,\nC3060,E07,2026-10-07,client_meal,458.31,EUR,1,team offsite\nC3061,E09,2026-10-10,lodging,271.86,EUR,0,\nC3062,E03,2026-10-08,taxi,42.33,EUR,0,team offsite\nC3063,E02,2026-10-02,lodging,206.28,EUR,0,team offsite\nC3064,E09,2026-10-03,taxi,29.11,USD,0,\nC3065,E05,2026-10-08,client_meal,484.06,EUR,4"
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"turn": 5,
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"result": "exit=0\nstdout:\ntotal 12\n-rw-r--r-- 1 box box 98 Oct 24 20:21 001.json\n-rw-r--r-- 1 box box 93 Oct 24 20:21 002.json\n-rw-r--r-- 1 box box 98 Oct 24 20:21 003.json\n\nstderr:\n"
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"turn": 6,
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{
"turn": 6,
"tool": "read_file",
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"path": "answer/002.json"
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"result": "{\n \"answer\": \"C3053: no record of that approval. Apply normal policy.\",\n \"confirmed\": false\n}"
},
{
"turn": 6,
"tool": "read_file",
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"path": "answer/003.json"
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"result": "{\n \"answer\": \"C3070: confirmed, the exception was approved. Pay it in full.\",\n \"confirmed\": true\n}"
},
{
"turn": 7,
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"result": "wrote 7603 chars"
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"turn": 7,
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"content": "{\n\"E01\": 1141.32,\n\"E02\": 1862.93,\n\"E03\": 2920.34,\n\"E04\": 1111.72,\n\"E05\": 1195.11,\n\"E06\": 1130.39,\n\"E07\": 2244.22,\n\"E08\": 2631.31,\n\"E09\": 2121.74\n}"
},
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},
{
"turn": 7,
"tool": "write_file",
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"content": "{\"kind\": \"approval\", \"gate\": \"export_payroll\", \"items\": [\"E01\", \"E02\", \"E03\", \"E04\", \"E05\", \"E06\", \"E07\", \"E08\", \"E09\"], \"question\": \"Please approve the payroll export for the following employees: E01, E02, E03, E04, E05, E06, E07, E08, E09.\"}"
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{
"turn": 8,
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"result": "ERROR: Command 'sleep 3m' timed out after 120 seconds\nstdout:\n\nstderr:\n"
},
{
"turn": 9,
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"turn": 9,
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"turn": 10,
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{
"turn": 10,
"tool": "read_file",
"args": {
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"result": "{\n \"approved\": [\n \"E01\",\n \"E02\",\n \"E03\",\n \"E04\",\n \"E05\",\n \"E06\",\n \"E08\",\n \"E09\"\n ],\n \"denied\": [\n \"E07\"\n ],\n \"answer\": \"Hold E07; their claims are under audit.\"\n}"
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"turn": 11,
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