AI Indexes
GTM AI Index
Index › Revenue operations › Commissions › Qobra vs Visdum
Sales commissions and incentive compensation · October 2026 Edition

Qobra vs Visdum

Two of fourteen models named Qobra first on the direct prompt; three named Visdum. Qobra was named by nine of the fourteen models and Visdum by eight and Qobra carries 24 labels and Visdum 14, so the shares are not directly comparable.

Qobra

accepted challenger

Named in three categories this edition.

Visdum

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 rate0%0%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#5#6A position in a field of 10; printed, not drawn.
Labels2414A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, Qobra reading right to left. Rank and label count are printed, not drawn.CaptivateIQ was named alongside these two in twelve of the fourteen direct answers. CaptivateIQ vs Qobra · CaptivateIQ vs Visdum · Everstage vs Qobra

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 sales commissions and incentive compensation page.

By framing

How many of the fourteen models made each the first choice, per way of asking, and how many argued against it.
QobraFirst choices, of fourteen modelsVisdum
Direct23
Paraphrase11
Comparative00
Budget-constrained10
Scale-constrained00
Negative01
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.

Across every category in the October 2026 Edition, Qobra and Visdum were named in the same answer seventeen times, of the 72 answers naming Qobra and the 41 naming Visdum. In those answers Visdum took the first choice one time and Qobra three.

Every model, every framing

The eighty-four answers behind the chart above, one cell each: where Qobra and Visdum 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
Qobra Visdum first choice named as an alternative argued againstblank: not namedEach cell is one answer, Qobra on the left and Visdum on the right.

The direct prompt

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

Qobra first, Visdum an alternative

2 of 14 modelsVisdum was named in the answer but not as the choice, or not at all.
Claude Haiku 4.5CaptivateIQ, Qobra alternatives: EasyComp, Everstage, Visdum
Grok 4.20Everstage, Qobra alternatives: CaptivateIQ, Salesforce Spiff, Visdum

Visdum first, Qobra not the choice

3 of 14 modelsQobra was named in the answer but not as the choice, or not at all.
Mistral SmallVisdum, Xactly Incent alternatives: CaptivateIQ, Forma.ai, QuotaPath
Kimi K2Everstage, Visdum alternatives: CaptivateIQ, QuotaPath
MiniMax M2.5Visdum alternatives: CaptivateIQ

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.
Perplexity SonarQuotaPath alternatives: CaptivateIQ, Performio, Qobra
DeepSeek V4 FlashEverstage, QuotaPath alternatives: Performio, Qobra
GLM 4.7 FlashXQuotaPath alternatives: CaptivateIQ, Everstage, Performio, Qobra
Muse Glimmer 30BQuotaPath alternatives: CaptivateIQ, Everstage, Qobra, Salesforce Spiff

Neither was named

5 of 14 modelsThe answer made no first choice from these two in this category.
GPT-5.4 miniCaptivateIQ, Everstage alternatives: Salesforce Spiff, Xactly Incent
Gemini 3.5 FlashCaptivateIQ alternatives: Everstage, Performio, QuotaPath, Salesforce Spiff
Llama 4 MaverickQuotaPath
Qwen 3.7 FlashCaptivateIQ, Everstage
GPT-6 LunaEverstage alternatives: CaptivateIQ, Salesforce Spiff

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
Visdum leads by four points.
Visdum4%#5 of 11
Qobra0%#6 of 11
The full small business standing →
Mid-marketThe figures above
Level: the same share of first choices.
Qobra7%#5 of 10
Visdum7%#6 of 10
The full mid-market standing →
Enterprise
The order flips: Qobra leads at enterprise.
Qobra6%#5 of 11
Visdum4%#– of 11
The full enterprise standing →

What the models said about Qobra

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

“Qobra leads in implementation speed (7-14 days) and sales rep adoption (95%+), making it ideal for growth-stage B2B companies” Claude Haiku 4.5 · direct prompt · first choice
“is likely to be one of the following options: 1. Qobra” Llama 4 Maverick · budget prompt · first choice
“I'd recommend starting with Qobra or Everstage” GLM 4.7 FlashX · paraphrase prompt · first choice

What the models said about Visdum

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

“Everstage or Visdum offer the best combination of modern features, mid-market pricing, and fast implementation” Kimi K2 · direct prompt · first choice
“Visdum appears to offer the best balance of speed-to-value, ease of use, and mid-market specialization” MiniMax M2.5 · direct prompt · first choice
“Visdum and Xactly Incent are top choices due to their automation, integration, and scalability.” Mistral Small · 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.