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AI accounting assistants · November 2026 Edition

Sage Intacct vs Vic.ai

Five of fourteen models named Sage Intacct first on the direct prompt; one named Vic.ai. Both were named by all fourteen models and Sage Intacct carries 27 labels and Vic.ai 33, so the shares are not directly comparable.

Sage Intacct

accepted challenger

Named in twenty categories this edition.

Vic.ai

accepted challenger

Named in two categories this edition.

First-choice share12%4%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate7%6%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#3#6A position in a field of 15; printed, not drawn.
Labels2733A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, Sage Intacct reading right to left. Rank and label count are printed, not drawn.Rillet was named alongside these two in ten of the fourteen direct answers. Zoho Books vs Sage Intacct · Zoho Books vs Vic.ai · Rillet vs Sage Intacct

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 AI accounting assistants page.

By framing

How many of the fourteen models made each the first choice, per way of asking, and how many argued against it.
Sage IntacctFirst choices, of fourteen modelsVic.ai
Direct511 against Sage Intacct
Paraphrase111 against Sage Intacct
Comparative01
Budget-constrained002 against Vic.ai
Scale-constrained00
Negative10
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 Sage Intacct and Vic.ai 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
Sage Intacct Vic.ai first choice named as an alternative argued againstblank: not namedEach cell is one answer, Sage Intacct on the left and Vic.ai on the right.

The direct prompt

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

Sage Intacct first, Vic.ai an alternative

5 of 14 modelsVic.ai was named in the answer but not as the choice, or not at all.
Perplexity SonarSage Intacct alternatives: Booke AI, Rillet, Vic.ai, Zeni
Mistral SmallRillet, Sage Intacct alternatives: Microsoft Dynamics 365 Business Central
Llama 4 MaverickSage Intacct alternatives: Microsoft Dynamics 365 Business Central, Rillet, Zeni
GPT-6 LunaSage Intacct alternatives: Numeric, Oracle NetSuite
Muse Glimmer 30BSage Intacct alternatives: Microsoft Dynamics 365 Business Central, Rillet

Vic.ai first, Sage Intacct not the choice

1 of 14 modelsSage Intacct was named in the answer but not as the choice, or not at all.
Gemini 3.5 FlashVic.ai alternatives: Numeric, Ramp Accounting Agent, Stampli, Tabs, Trullion, Zone & Co

Neither was the first choice, one was named

6 of 14 modelsThe answer put something else first and named one of the two as an alternative.
Claude Haiku 4.5DualEntry alternatives: Campfire, Rillet, Sage Intacct
GPT-5.4 miniIntuit Enterprise Suite, QuickBooks Online alternatives: BILL, Botkeeper, Campfire, Vic.ai
Grok 4.20Rillet alternatives: Sage Intacct
Qwen 3.7 FlashRillet alternatives: Vic.ai, Zeni
Kimi K2Rillet alternatives: QuickBooks with AI, Ramp Accounting Agent, Sage Intacct
MiniMax M2.5QuickBooks Online alternatives: DualEntry, Netgain, Vic.ai

Neither was named

2 of 14 modelsThe answer made no first choice from these two in this category.
DeepSeek V4 FlashRillet alternatives: Digits, Zeni
GLM 4.7 FlashXRillet alternatives: Booke AI, Docyt

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
Vic.ai leads by two points.
Vic.ai2%#8 of 16
Sage Intacct0%#– of 16
The full small business standing →
Mid-marketThe figures above
The order flips: Sage Intacct leads at mid-market.
Sage Intacct12%#3 of 15
Vic.ai4%#6 of 15
The full mid-market standing →
Enterprise
The order flips: Vic.ai leads at enterprise.
Vic.ai15%#1 of 13
Sage Intacct4%#4 of 13
The full enterprise standing →

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.

“Sage Intacct is the safest overall choice when you need mature controls, multi-entity consolidation, dimensional reporting, and AI-assisted automation at scale.” Perplexity Sonar · direct prompt · first choice

What the models said about Vic.ai

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

“avoid expensive, fully managed AI bookkeeping services (like Zeni or Vic.ai, which cost $200–$500+ per month)” Gemini 3.5 Flash · budget prompt · hard negative
“Avoid purely free trials (like some from Botkeeper or Vic.ai) for ongoing use” Grok 4.20 · budget prompt · hard negative
“Best For: Mid-market companies with high invoice volume (1,000+ invoices/month) and multi-entity structures.” Gemini 3.5 Flash · paraphrase prompt · first choice
“Start with a free trial based on your pain points (e.g., Vic.ai for AP headaches).” Grok 4.20 · comparative prompt · first choice
“Best for AP & Autonomous Invoice Processing: Vic.ai” Gemini 3.5 Flash · 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.