GTM AI Index
Index Revenue operations Territory planning › QuotaPath vs Varicent
Territory and quota planning · September 2026 Edition

QuotaPath vs Varicent

One of twelve models named QuotaPath first on the direct prompt; zero named Varicent. QuotaPath was named by eight of the twelve models and Varicent by twelve and QuotaPath carries 23 labels and Varicent 36, so the shares are not directly comparable.

QuotaPath

accepted challenger

Named in two categories this edition.

Varicent

criticized challenger

Named in two categories this edition.

First-choice share4%2%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate4%44%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#3#7A position in a field of 11; printed, not drawn.
Labels2336A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, QuotaPath reading right to left. Rank and label count are printed, not drawn.Fullcast was named alongside these two in nine of the twelve direct answers. CaptivateIQ vs QuotaPath · CaptivateIQ vs Varicent · Fullcast vs QuotaPath

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 territory and quota planning page.

By framing

How many of the twelve models made each the first choice, per way of asking, and how many argued against it.
QuotaPathFirst choices, of twelve modelsVaricent
Direct101 against QuotaPath · 6 against Varicent
Paraphrase103 against Varicent
Comparative01
Budget-constrained003 against Varicent
Scale-constrained011 against Varicent
Negative003 against Varicent
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, QuotaPath and Varicent were named in the same answer sixty-four times, of the 181 answers naming QuotaPath and the 173 naming Varicent. In those answers Varicent took the first choice four times and QuotaPath seventeen.

Every model, every framing

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

The direct prompt

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

QuotaPath first, Varicent an alternative

1 of 12 modelsVaricent was named in the answer but not as the choice, or not at all.
Mistral SmallFullcast, QuotaPath alternatives: Anaplan Territory & Quota Planning, Everstage, Varicent

Neither was the first choice, one was named

2 of 12 modelsThe answer put something else first and named one of the two as an alternative.
Gemini 3.5 FlashFullcast alternatives: CaptivateIQ, Pigment, QuotaPath, Salesforce Maps, Salesforce Sales Planning
MiniMax M2.5CaptivateIQ alternatives: Fullcast, SalesRabbit, Varicent

Neither was named

9 of 12 modelsThe answer made no first choice from these two in this category.
Claude Haiku 4.5CaptivateIQ Planning alternatives: Clari Align, Fullcast, eSpatial
GPT-5.4 miniCaptivateIQ Planning alternatives: Salesforce Sales Planning / Territory Planning, Xactly
Perplexity SonarFullcast alternatives: CaptivateIQ
Grok 4.1 FastCaptivateIQ alternatives: Everstage, Fullcast, Salesforce Maps, Salesforce Sales Planning, eSpatial
DeepSeek V4 FlashFullcast alternatives: CaptivateIQ, Salesforce Sales Planning + Territory Management
Llama 4 Maverickno first choice
Qwen 3.7 FlashCaptivateIQ alternatives: SalesRabbit, Territory Helper
Kimi K2Fullcast, Pigment alternatives: CaptivateIQ
GLM 4.7 FlashXFullcast alternatives: Salesforce Sales Planning / Territory Planning Add-On, Vena

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
QuotaPath leads by twenty-two points.
QuotaPath22%#1 of 13
Varicent0%#12 of 13
The full small business standing →
Mid-marketThe figures above
QuotaPath leads by two points.
QuotaPath4%#3 of 11
Varicent2%#7 of 11
The full mid-market standing →
Enterprise
The order flips: Varicent leads at enterprise.
Varicent35%#1 of 10
QuotaPath2%#– of 10
The full enterprise standing →

What the models said about QuotaPath

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

“Accessible pricing (~$35/user/mo) ... but light on territory design/capacity modeling.” DeepSeek V4 Flash · direct prompt · soft negative
“Fullcast (if Salesforce-native) or QuotaPath (for best value and flexibility) would be the strongest choices” Mistral Small · direct prompt · first choice
“I'd recommend QuotaPath or CaptivateIQ for a mid-sized B2B company” GLM 4.7 FlashX · paraphrase prompt · first choice

What the models said about Varicent

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

“What to avoid for mid-market ... Varicent / Xactly / Oracle SPM — Full sales-performance suites costing $50K–$100K+/year” DeepSeek V4 Flash · direct prompt · hard negative
“Skip these (too expensive for a limited budget)” DeepSeek V4 Flash · budget prompt · hard negative
“Varicent Territory Sales Planning supports complex territory modeling, robust scenario modeling, and AI-assisted planning” Claude Haiku 4.5 · comparative prompt · first choice
“Varicent - Strongest for complex orgs needing linked territory/quota planning with AI insights” Mistral Small · scale prompt · first choice
“Best for: Enterprises linking territory/quota to incentive compensation (ICM), with AI whitespace analysis.” Grok 4.1 Fast · comparative prompt · alternative
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.