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Lease accounting · November 2026 Edition

LeaseGuru vs Sage Intacct

Zero of fourteen models named LeaseGuru first on the direct prompt; three named Sage Intacct. LeaseGuru was named by eleven of the fourteen models and Sage Intacct by nine and LeaseGuru carries 13 labels and Sage Intacct 17, so the shares are not directly comparable.

LeaseGuru

accepted challenger

Named in one category this edition.

Sage Intacct

accepted challenger

Named in twenty categories this edition.

First-choice share8%6%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate8%12%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#5#6A position in a field of 18; printed, not drawn.
Labels1317A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, LeaseGuru reading right to left. Rank and label count are printed, not drawn.FinQuery was named alongside these two in twelve of the fourteen direct answers. FinQuery vs LeaseGuru · FinQuery vs Sage Intacct · NetLease vs LeaseGuru

Share is the count of first choices across the direct, paraphrase, budget and scale prompts over all fourteen 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 fourteen models made each the first choice, per way of asking, and how many argued against it.
LeaseGuruFirst choices, of fourteen modelsSage Intacct
Direct031 against LeaseGuru
Paraphrase00
Comparative001 against Sage Intacct
Budget-constrained401 against Sage Intacct
Scale-constrained00
Negative00
Bars are first choices, 0 to 14 each sideModels that argued againstA model can name both, so the two sides of a row do not sum to fourteen.

Every model, every framing

The eighty-four answers behind the chart above, one cell each: where LeaseGuru and Sage Intacct stood in it.
ModelDirectParaphraseComparativeBudget-constrainedScale-constrainedNegative
Claude Haiku 4.5
GPT-5.4 mini
Gemini 3.5 Flash
Perplexity Sonar
Grok 4.20
Mistral Small
DeepSeek V4 Flash
Llama 4 Maverick
Qwen 3.7 Flash
Kimi K2
GLM 4.7 FlashX
MiniMax M2.5
GPT-6 Luna
Muse Glimmer 30B
LeaseGuru Sage Intacct first choice named as an alternative argued againstblank: not namedEach cell is one answer, LeaseGuru on the left and Sage Intacct on the right.

The direct prompt

The plain question, one answer per model, grouped by where LeaseGuru and Sage Intacct stood in it.

Sage Intacct first, LeaseGuru not the choice

3 of 14 modelsLeaseGuru was named in the answer but not as the choice, or not at all.
Mistral SmallSage Intacct alternatives: FinQuery, SOFT4Lessee, Visual Lease, Yardi Corom
MiniMax M2.5FinQuery, Sage Intacct alternatives: Visual Lease
Muse Glimmer 30BSOFT4Lessee, Sage Intacct alternatives: FinQuery, Visual Lease, Yardi Corom

Neither was the first choice, one was named

4 of 14 modelsThe answer put something else first and named one of the two as an alternative.
GPT-5.4 miniFinQuery alternatives: NetLease, Occupier, Sage Intacct
Grok 4.20FinQuery alternatives: LeaseCrunch, Nakisa Lease Administration, Sage Intacct, Visual Lease
DeepSeek V4 FlashFinQuery alternatives: EZLease, Sage Intacct, Trullion
Kimi K2FinQuery alternatives: EZLease, Sage Intacct, Visual Lease

Neither was named

7 of 14 modelsThe answer made no first choice from these two in this category.
Claude Haiku 4.5FinQuery, SOFT4Lessee alternatives: EZLease, Spacebase, Visual Lease
Gemini 3.5 FlashFinQuery alternatives: EZLease, NetLease, Occupier, Trullion, Visual Lease
Perplexity SonarFinQuery alternatives: EZLease, Envoria, Nakisa Lease Administration, Prophix One Lease Accounting, Visual Lease
Llama 4 Maverickno first choice
Qwen 3.7 FlashFinQuery alternatives: Crown Lease Accounting, Leasium, Trullion
GLM 4.7 FlashXFinQuery alternatives: Trullion, Visual Lease, iLeasePro
GPT-6 LunaLeaseQuery, powered by FinQuery alternatives: Crunchafi, Occupier, Visual Lease

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
LeaseGuru leads by thirteen points.
LeaseGuru13%#4 of 14
Sage Intacct0%#– of 14
The full small business standing →
Mid-marketThe figures above
LeaseGuru leads by two points.
LeaseGuru8%#5 of 18
Sage Intacct6%#6 of 18
The full mid-market standing →
Enterprise
Level: the same share of first choices.
LeaseGuru0%#– of 11
Sage Intacct0%#10 of 11
The full enterprise standing →

What the models said about LeaseGuru

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

“FinQuery's separate product for very small portfolios—up to 15 leases—so don't confuse it with the broader LeaseQuery offering” GPT-6 Luna · direct prompt · soft negative
“Best Overall Value: LeaseGuru (FinQuery) ... likely your best option if you are looking for the most transparent pricing and a very generous free tier.” GLM 4.7 FlashX · budget prompt · first choice
“The best lease accounting software for a company with a limited budget is Cradle, iLeaseXpress, NetLease, or FinQuery LeaseGuru” Llama 4 Maverick · budget prompt · first choice
“0-2 leases: FinQuery LeaseGuru free tier is effectively $0 to start, with a self-serve paid tier when you grow.” Muse Glimmer 30B · budget prompt · first choice

What the models said about Sage Intacct

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

“Avoid for Limited Budgets: Full enterprise tools like Visual Lease, Occupier, or Sage Intacct” Grok 4.20 · budget prompt · hard negative
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.