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Spreadsheet-grade loan amortization for 8 loans incl. rate reset and extra payments

Exact prompt

# Task: loan amortization (spreadsheet-grade precision) `loans.csv` lists 8 loans: principal, annual_rate_pct (nominal, compounded monthly), years, extra_monthly (extra principal paid each month from `extra_from_month` on, 1-based), optional `rate_reset_month` + `new_rate_pct`. Rules (follow exactly, use decimal arithmetic, round HALF-UP to cents at each step): 1. Scheduled payment = P·i/(1−(1+i)^−n) with i = rate/12/100, n = years·12, rounded to cents. If rate is 0, payment = P/n rounded. 2. Each month: interest = round(balance·i); principal part = payment − interest; plus the extra payment if active. 3. If principal part + extra ≥ remaining balance, the final payment = interest + remaining balance (no extra that month) and the loan ends. 4. At `rate_reset_month` (before computing that month's interest), switch to the new rate and recompute the payment on the current balance over the ORIGINAL remaining term (n − reset_month + 1 months). Write `results.json`: {"L1": {"monthly_payment": "1234.56" (the initial scheduled payment, string), "total_interest": "…" (string, 2dp), "payoff_month": int}, ...} and `L3_schedule.csv` with header `month,payment,interest,principal,balance` (payment includes extra; principal includes extra; strings with 2dp). No network.

Exact-to-the-cent with HALF_UP per-step rounding, 0% loans, final-payment adjustment (one 60-month loan pays off in month 61 due to rounding), payment recompute at rate reset. Original benchmark task written for usecaserank.com (not based on a specific public post). Headless, offline run on a reproducible fixture. Each run's notes say how its cost was measured (estimates are marked).

Success criteria: 1. For each of the 8 loans: monthly_payment and total_interest must equal the key exactly to the cent (Decimal compare), and payoff_month must be exactly right. 2. L3_schedule.csv must have header month,payment,interest,principal,balance and the exact number of rows, with every month and every amount matching exactly.

Best model for this task so far: Claude Haiku 5.5 (effort default (no --effort flag) · thinking on) (success, $0.0061, 23s).

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All runs (4)

100% pass rate across 4 eligible runs: 4 pass, 0 partial, 0 fail. Partial and failed runs are listed below with everything else.ⓘ

Runs for this use case
ModelCostTimeStep-insⓘAutonomyOutcomeTrustⓘDateCompare
OGPT-6.1 Soldefault · thinking off$0.0338s0Fully autonomouspassTrust 80%2026-10-22
AClaude Haiku 5.5default · thinking on$0.006123s0Fully autonomouspassTrust 80%2026-10-16
AClaude Opus 5.5default · thinking on$0.1427s0Fully autonomouspassTrust 80%2026-10-16
AClaude Sonnet 5.5default · thinking on$0.0519s0Fully autonomouspassTrust 80%2026-10-16

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