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Learning experience platforms · November 2026 Edition

Absorb LMS vs Docebo

Three of fourteen models named Absorb LMS first on the direct prompt; zero named Docebo. Absorb LMS was named by fourteen of the fourteen models and Docebo by thirteen and Absorb LMS carries 34 labels and Docebo 46, so the shares are not directly comparable.

Absorb LMS

accepted challenger

Named in five categories this edition.

Docebo

accepted challenger

Named in nine categories this edition.

First-choice share6%2%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate6%15%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#3#7A position in a field of 12; printed, not drawn.
Labels3446A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, Absorb LMS reading right to left. Rank and label count are printed, not drawn.360Learning was named alongside these two in eleven of the fourteen direct answers. 360Learning vs Absorb LMS · 360Learning vs Docebo · TalentLMS vs Absorb LMS

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 learning experience platforms page.

By framing

How many of the fourteen models made each the first choice, per way of asking, and how many argued against it.
Absorb LMSFirst choices, of fourteen modelsDocebo
Direct30
Paraphrase012 against Docebo
Comparative00
Budget-constrained001 against Absorb LMS · 2 against Docebo
Scale-constrained001 against Absorb LMS
Negative003 against Docebo
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 November 2026 Edition, Absorb LMS and Docebo were named in the same answer 214 times, of the 257 answers naming Absorb LMS and the 407 naming Docebo. In those answers Docebo took the first choice fifty times and Absorb LMS nineteen.

Every model, every framing

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

The direct prompt

The plain question, one answer per model, grouped by where Absorb LMS and Docebo stood in it.

Absorb LMS first, Docebo an alternative

3 of 14 modelsDocebo was named in the answer but not as the choice, or not at all.
Grok 4.20Absorb LMS alternatives: Docebo, LearnUpon, TalentLMS
Qwen 3.7 FlashAbsorb LMS alternatives: Degreed, Docebo, Learn Upon, TalentLMS
MiniMax M2.5Absorb LMS, LearnUpon alternatives: 360Learning, Adobe Learning Manager, Docebo

Neither was the first choice, one was named

11 of 14 modelsThe answer put something else first and named one of the two as an alternative.
Claude Haiku 4.5Learn Amp alternatives: 360Learning, Absorb LMS, Docebo
GPT-5.4 miniLearnUpon alternatives: 360Learning, Docebo, Intellum
Gemini 3.5 FlashWorkRamp alternatives: 360Learning, Absorb LMS, Continu, Docebo
Perplexity SonarThinkific alternatives: Absorb LMS, Docebo, TalentLMS
Mistral Small360Learning, TalentLMS alternatives: Absorb LMS, GoSkills
DeepSeek V4 Flash360Learning alternatives: Absorb LMS, Docebo, LearnUpon
Llama 4 MaverickLearn Amp alternatives: 360Learning, Absorb LMS, Degreed, GoSkills
Kimi K2360Learning alternatives: Docebo, LearnUpon, TalentLMS
GLM 4.7 FlashX360Learning alternatives: Absorb LMS, Docebo, TalentLMS, iSpring Learn
GPT-6 Luna360Learning alternatives: Absorb LMS, Degreed, Docebo
Muse Glimmer 30B360Learning alternatives: Absorb LMS, Docebo, Learn Amp, LearnUpon, TalentLMS

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.
Absorb LMS2%#– of 13
Docebo2%#7 of 13
The full small business standing →
Mid-marketThe figures above
Absorb LMS leads by four points.
Absorb LMS6%#3 of 12
Docebo2%#7 of 12
The full mid-market standing →
Enterprise
The order flips: Docebo leads at enterprise.
Docebo39%#1 of 11
Absorb LMS2%#5 of 11
The full enterprise standing →

What the models said about Absorb LMS

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

“significantly cheaper than enterprise options like Docebo or Absorb LMS” Grok 4.20 · budget prompt · soft negative
“Absorb LMS | Compliance features | May be over-featured” Kimi K2 · scale prompt · soft negative
“The Best All-Rounder: Absorb LMS ... widely considered the "Goldilocks" option for the mid-market B2B sector.” Qwen 3.7 Flash · direct prompt · first choice

What the models said about Docebo

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

“Some enterprise-focused LXPs (like Degreed, Docebo, and Learnerbly) are only practical for very large organizations (250+ learners) and are not cost-effective for smaller teams.” Mistral Small · negative prompt · soft negative
“may be impractical when you have fewer than roughly 100 learners because pricing and implementation can be disproportionate” Perplexity Sonar · negative prompt · soft 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.