Lease Termination → New Lease → Lender Consent
Analyze an early lease termination, replacement lease economics, and whether lender consent conditions are satisfied.
What This Benchmark Tests
A real asset management problem: a tenant wants to terminate a Class A office lease early. Can the model calculate remaining obligations, evaluate a replacement tenant LOI, run NER on both leases, and determine whether a specific 2-of-3 lender consent test from the loan agreement is satisfied? Requires reading across five documents and chaining five analytical steps.
The Prompt
The Prompt
The exact system + user prompt every model runs against.
Reference Documents
Executed Lease (Class A Office)
Original tenant · remaining term · rent schedule
Termination Request Emails
Tenant counsel · proposed termination timeline
Replacement Tenant LOI
Proposed new lease economics
Loan Agreement Excerpt
Lender consent conditions and covenants
Manhattan Commission Schedule
Tiered commission rates with abatement treatment
Task Structure
- 1
Calculate remaining lease obligations
Remaining rent through expiration, unamortized TI, leasing commissions, free rent.
- 2
Calculate replacement tenant costs
Downtime rent, free rent, TI, landlord work, commissions for the replacement tenant.
- 3
Calculate net effective rent
NER for both leases using the methodology prescribed in the loan agreement.
- 4
Apply lender consent conditions
Test whether at least 2 of 3 loan covenant conditions are satisfied.
- 5
Make a recommendation
Should the landlord proceed with the termination?
How It's Scored
Eighteen numeric outputs across the five steps are compared to a hand-validated answer key. Dollar figures must fall within tight tolerances; the lender-consent conclusion must match both the binary outcome and the supporting test logic. Completion rate is tracked separately — some models refuse or fail mid-workflow.
See full methodology →Results Snapshot (Top 5)
| Model | Score | Notes |
|---|---|---|
| Gemini 3.1 Pro | 100.0% | 5 of 5 runs perfect |
| Claude Opus 4.6 | 100.0% | 2 of 2 completed perfect · 40% completion rate |
| GPT-5 Mini | 90.0% | 2 of 5 perfect · 100% completion |
| GPT-5.4 | 88.9% | 2 of 5 perfect · 100% completion |
| GPT-5 | 86.1% | 1 of 3 completed perfect |
Run it yourself
Pick a model, run the benchmark, and see where it holds up and where it breaks.