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Employee engagement surveys · November 2026 Edition

15Five Engage vs Leapsome

Eight of fourteen models named 15Five Engage first on the direct prompt; one named Leapsome. 15Five Engage was named by fourteen of the fourteen models and Leapsome by twelve and 15Five Engage carries 44 labels and Leapsome 21, so the shares are not directly comparable.

15Five Engage

endorsed leader

Named in two categories this edition.

Leapsome

accepted challenger

Named in seventeen categories this edition.

First-choice share39%4%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate2%14%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#1#5A position in a field of 10; printed, not drawn.
Labels4421A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, 15Five Engage reading right to left. Rank and label count are printed, not drawn.Workleap Officevibe was named alongside these two in nine of the fourteen direct answers. 15Five Engage vs Culture Amp · 15Five Engage vs Workleap Officevibe · 15Five Engage vs Lattice Engagement

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 employee engagement surveys page.

By framing

How many of the fourteen models made each the first choice, per way of asking, and how many argued against it.
15Five EngageFirst choices, of fourteen modelsLeapsome
Direct81
Paraphrase701 against Leapsome
Comparative00
Budget-constrained511 against 15Five Engage · 2 against Leapsome
Scale-constrained10
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 15Five Engage and Leapsome 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
15Five Engage Leapsome first choice named as an alternative argued againstblank: not namedEach cell is one answer, 15Five Engage on the left and Leapsome on the right.

The direct prompt

The plain question, one answer per model, grouped by where 15Five Engage and Leapsome stood in it.

Both were the first choice

1 of 14 modelsThe answer named them together, and the judge labeled each a first choice.
Mistral Small15Five Engage, Leapsome, Workleap Officevibe alternatives: Lattice Engagement

15Five Engage first, Leapsome an alternative

7 of 14 modelsLeapsome was named in the answer but not as the choice, or not at all.
Grok 4.2015Five Engage alternatives: Leapsome, Workleap Officevibe
DeepSeek V4 Flash15Five Engage alternatives: Leapsome, Workleap Officevibe
Qwen 3.7 Flash15Five Engage alternatives: Culture Amp, Lattice Engagement, Leapsome
Kimi K215Five Engage alternatives: Leapsome
GLM 4.7 FlashX15Five Engage alternatives: Leapsome, Workleap Officevibe
MiniMax M2.515Five Engage alternatives: Culture Amp, Leapsome, Workleap Officevibe
Muse Glimmer 30B15Five Engage alternatives: Culture Amp, Leapsome, ThriveSparrow Engage, Workleap Officevibe

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.
Claude Haiku 4.5Culture Amp alternatives: 15Five Engage, Lattice Engagement, Quantum Workplace, WorkTango
Gemini 3.5 FlashLattice Engagement alternatives: 15Five Engage, Culture Amp, Leapsome, Workleap Officevibe
Perplexity SonarCulture Amp alternatives: 15Five Engage, Lattice Engagement, Workleap Officevibe
GPT-6 LunaCulture Amp alternatives: 15Five Engage, Lattice Engagement, Workleap Officevibe

Neither was named

2 of 14 modelsThe answer made no first choice from these two in this category.
GPT-5.4 miniCulture Amp alternatives: Betterworks, Lattice Engagement, Workvivo
Llama 4 Maverickno first choice

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
15Five Engage leads by twenty-one points.
15Five Engage21%#2 of 11
Leapsome0%#10 of 11
The full small business standing →
Mid-marketThe figures above
15Five Engage leads by thirty-five points.
15Five Engage39%#1 of 10
Leapsome4%#5 of 10
The full mid-market standing →
Enterprise
15Five Engage leads by six points.
15Five Engage6%#5 of 7
Leapsome0%#– of 7
The full enterprise standing →

What the models said about 15Five Engage

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

“Avoid for Tight Budgets: ... 15Five” Grok 4.20 · budget prompt · hard negative
“15Five - Best for mid-market and enterprise HR teams that want performance reviews, OKRs, and engagement surveys in one per-user platform.” Llama 4 Maverick · paraphrase prompt · first choice
“Popular starting points include Culture Amp for insights depth or 15Five for integrated performance/engagement.” Grok 4.20 · scale prompt · first choice
“Top Overall Value: 15Five ... Start with 15Five if you want a balance of price and robust features.” Qwen 3.7 Flash · budget prompt · first choice

What the models said about Leapsome

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 Tight Budgets: ... or Leapsome” 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.