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Lease accounting · September 2026 Edition

iLeasePro vs SOFT4Lessee

One of twelve models named iLeasePro first on the direct prompt; two named SOFT4Lessee. iLeasePro was named by nine of the twelve models and SOFT4Lessee by seven and iLeasePro carries 17 labels and SOFT4Lessee 10, so the shares are not directly comparable.

iLeasePro

accepted challenger

Named in one category this edition.

SOFT4Lessee

accepted challenger

Named in one category this edition.

First-choice share12%6%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate6%0%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#2#5A position in a field of 12; printed, not drawn.
Labels1710A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, iLeasePro reading right to left. Rank and label count are printed, not drawn.FinQuery was named alongside these two in eleven of the twelve direct answers. FinQuery vs iLeasePro · FinQuery vs SOFT4Lessee · iLeasePro vs Visual Lease

Share is the count of first choices across the direct, paraphrase, budget and scale prompts over all twelve models, for a mid-market B2B company; rank is within the category; every quote names the model and the prompt it came from. Both figures come from the lease accounting page.

By framing

How many of the twelve models made each the first choice, per way of asking, and how many argued against it.
iLeaseProFirst choices, of twelve modelsSOFT4Lessee
Direct12
Paraphrase101 against iLeasePro
Comparative00
Budget-constrained40
Scale-constrained01
Negative00
Bars are first choices, 0 to 12 each sideModels that argued againstA model can name both, so the two sides of a row do not sum to twelve.

Every model, every framing

The seventy-two answers behind the chart above, one cell each: where iLeasePro and SOFT4Lessee stood in it.
ModelDirectParaphraseComparativeBudget-constrainedScale-constrainedNegative
Claude Haiku 4.5
GPT-5.4 mini
Gemini 3.5 Flash
Perplexity Sonar
Grok 4.1 Fast
Mistral Small
DeepSeek V4 Flash
Llama 4 Maverick
Qwen 3.7 Flash
Kimi K2
GLM 4.7 FlashX
MiniMax M2.5
iLeasePro SOFT4Lessee first choice named as an alternative argued againstblank: not namedEach cell is one answer, iLeasePro on the left and SOFT4Lessee on the right.

The direct prompt

The plain question, one answer per model, grouped by where iLeasePro and SOFT4Lessee stood in it.

iLeasePro first, SOFT4Lessee an alternative

1 of 12 modelsSOFT4Lessee was named in the answer but not as the choice, or not at all.
Llama 4 MaverickiLeasePro alternatives: EZLease, LeaseAccelerator, Leasecake, SOFT4Lessee

SOFT4Lessee first, iLeasePro not the choice

2 of 12 modelsiLeasePro was named in the answer but not as the choice, or not at all.
Claude Haiku 4.5SOFT4Lessee alternatives: EZLease, FinQuery, Trullion, Visual Lease
Mistral SmallFinQuery, SOFT4Lessee alternatives: EZLease, Trullion, Visual Lease

Neither was the first choice, one was named

6 of 12 modelsThe answer put something else first and named one of the two as an alternative.
GPT-5.4 miniFinQuery alternatives: Nakisa Lease Administration, Sage Intacct, UGAAP, Yardi Corom, iLeasePro
Gemini 3.5 FlashFinQuery alternatives: NetLease, SOFT4Lessee, Trullion, Visual Lease
Perplexity SonarFinQuery, Spacebase alternatives: EZLease, SOFT4Lessee, Visual Lease
Qwen 3.7 FlashFinQuery alternatives: EZLease, Spacebase, iLeasePro
Kimi K2FinQuery alternatives: EZLease, iLeasePro
GLM 4.7 FlashXFinQuery, Visual Lease alternatives: DebtBook, SOFT4Lessee, iLeasePro

Neither was named

3 of 12 modelsThe answer made no first choice from these two in this category.
Grok 4.1 FastFinQuery alternatives: EZLease, Visual Lease
DeepSeek V4 FlashFinQuery alternatives: Crunchafi, LeaseCrunch, NetLease, Visual Lease
MiniMax M2.5FinQuery, Visual Lease alternatives: Spacebase

Bold names in an answer are the products the judge labeled a first choice; a model naming several gives each of them that label. The full answer text for every row is in the record.

By buyer segment

The same question asked on behalf of a different buyer. Each standing is computed within its segment and they are never added together. The figures above are the mid-market standing, which is the one the category orders by.
Small business
iLeasePro leads by nineteen points.
iLeasePro19%#2 of 9
SOFT4Lessee0%#– of 9
The full small business standing →
Mid-marketThe figures above
iLeasePro leads by six points.
iLeasePro12%#2 of 12
SOFT4Lessee6%#5 of 12
The full mid-market standing →
Enterprise
Level: the same share of first choices.
iLeasePro0%#– of 10
SOFT4Lessee0%#– of 10
The full enterprise standing →

What the models said about iLeasePro

Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Four of five in this category shown.

“Avoid for Dual Standards: iLeasePro or EZLease—excellent for pure ASC 842 in US-only mid-market setups but lack robust IFRS 16/multi-currency support.” Grok 4.1 Fast · paraphrase prompt · hard negative
“iLeasePro - a cloud-based lease management and lease accounting software that helps mid-market companies comply with the FASB ASC 842 lease accounting changes” Llama 4 Maverick · direct prompt · first choice
“iLeasePro (specifically its iLeaseXpress tier) stands out as one of the best and most affordable dedicated lease accounting software options” Grok 4.1 Fast · budget prompt · first choice
“iLeaseXpress and iLeasePro are excellent choices, especially if you have a small number of leases” Mistral Small · budget prompt · first choice

What the models said about SOFT4Lessee

Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Three of four in this category shown.

“Overall best for mid‑sized companies ... SOFT4Lessee for a balanced mid‑market choice” GLM 4.7 FlashX · scale prompt · first choice
“FinQuery (LeaseQuery) and SOFT4Lessee are the top recommendations” Mistral Small · direct prompt · first choice
“SOFT4Lessee is the best first shortlist option” Claude Haiku 4.5 · direct prompt · first choice
Also compared

Comparisons are drawn for the top eight products in each category, each against each. The output is the models' output; nothing here is a recommendation by the index.