Finance AI Index
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AI accounting assistants · September 2026 Edition

Vic.ai vs Numeric

One of twelve models named Vic.ai first on the direct prompt; one named Numeric. Vic.ai was named by eleven of the twelve models and Numeric by nine and Vic.ai carries 34 labels and Numeric 17, so the shares are not directly comparable.

Vic.ai

accepted challenger

Named in three categories this edition.

Numeric

accepted challenger

Named in three categories this edition.

First-choice share7%7%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#4#6A position in a field of 14; printed, not drawn.
Labels3417A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, Vic.ai reading right to left. Rank and label count are printed, not drawn.Sage Intacct was named alongside these two in eleven of the twelve direct answers. Sage Intacct vs Vic.ai · Sage Intacct vs Numeric · Zoho Books vs Vic.ai

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 AI accounting assistants page.

By framing

How many of the twelve models made each the first choice, per way of asking, and how many argued against it.
Vic.aiFirst choices, of twelve modelsNumeric
Direct11
Paraphrase22
Comparative001 against Vic.ai
Budget-constrained00
Scale-constrained00
Negative001 against Vic.ai
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.

Across every category in the September 2026 Edition, Vic.ai and Numeric were named in the same answer thirty-six times, of the 97 answers naming Vic.ai and the 202 naming Numeric. In those answers Numeric took the first choice eight times and Vic.ai two.

Every model, every framing

The seventy-two answers behind the chart above, one cell each: where Vic.ai and Numeric 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
Vic.ai Numeric first choice named as an alternative argued againstblank: not namedEach cell is one answer, Vic.ai on the left and Numeric on the right.

The direct prompt

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

Vic.ai first, Numeric not the choice

1 of 12 modelsNumeric was named in the answer but not as the choice, or not at all.
Claude Haiku 4.5Vic.ai alternatives: Booke AI, DualEntry, Integra Balance AI, Sage Intacct

Numeric first, Vic.ai an alternative

1 of 12 modelsVic.ai was named in the answer but not as the choice, or not at all.
Gemini 3.5 FlashLedge, Numeric alternatives: Ramp, Tabs, Vic.ai

Neither was the first choice, one was named

7 of 12 modelsThe answer put something else first and named one of the two as an alternative.
Perplexity SonarSage Intacct alternatives: DualEntry, Numeric, Vic.ai
Mistral SmallSage Intacct alternatives: Truewind, Vic.ai
DeepSeek V4 FlashRho, Sage Intacct alternatives: Oracle NetSuite, Vic.ai, Zeni
Llama 4 MaverickSage Intacct alternatives: Truewind, Vic.ai
Qwen 3.7 FlashDualEntry alternatives: Sage Intacct, Vic.ai
Kimi K2Sage Intacct alternatives: DualEntry, Numeric, Vic.ai
MiniMax M2.5Sage Intacct alternatives: DualEntry, Truewind, Vic.ai

Neither was named

3 of 12 modelsThe answer made no first choice from these two in this category.
GPT-5.4 miniSage Intacct alternatives: FloQast, Hyperbots A/P Suite, Microsoft Dynamics 365 Business Central, Oracle NetSuite
Grok 4.1 FastSage Intacct alternatives: Docyt, Oracle NetSuite, QuickBooks Online, Xero
GLM 4.7 FlashXSage Intacct alternatives: Docyt, Zeni

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
Level: the same share of first choices.
Vic.ai0%#10 of 11
Numeric0%#– of 11
The full small business standing →
Mid-marketThe figures above
Level: the same share of first choices.
Vic.ai7%#4 of 14
Numeric7%#6 of 14
The full mid-market standing →
Enterprise
Vic.ai leads by five points.
Vic.ai12%#1 of 8
Numeric7%#6 of 8
The full enterprise standing →

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 five in this category shown.

“Ranked low in privacy audits ... they train AI on customer data without easy opt-out” Grok 4.1 Fast · negative prompt · soft negative
“Vic.ai requires significant invoice volume to justify its cost” Qwen 3.7 Flash · comparative prompt · soft negative
“Vic.ai is recommended for mid-market or enterprise AP teams, as it's autonomous invoice processing for organizations processing thousands of bills every month” Claude Haiku 4.5 · direct prompt · first choice
“For most mid-sized B2B companies, Vic.ai is the top recommendation due to its specialized focus on AP automation and proven scalability.” Mistral Small · paraphrase prompt · first choice
“I recommend starting with Vic.ai for accounts payable and Docyt for end‑to‑end bookkeeping.” GLM 4.7 FlashX · paraphrase prompt · first choice

What the models said about Numeric

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

“Best For: Mid-market finance teams looking to dramatically compress close times.... It is built for audit scrutiny.” Gemini 3.5 Flash · paraphrase 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.