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Skills intelligence · October 2026 Edition

iMocha vs MuchSkills

Three of fourteen models named iMocha first on the direct prompt; zero named MuchSkills. iMocha was named by twelve of the fourteen models and MuchSkills by eight and iMocha carries 19 labels and MuchSkills 11, so the shares are not directly comparable.

iMocha

accepted challenger

Named in four categories this edition.

MuchSkills

accepted challenger

Named in one category this edition.

First-choice share9%5%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate5%0%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#3#6A position in a field of 16; printed, not drawn.
Labels1911A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, iMocha reading right to left. Rank and label count are printed, not drawn.Skills Base vs iMocha · Skills Base vs MuchSkills · TalentGuard vs iMocha

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 skills intelligence page.

By framing

How many of the fourteen models made each the first choice, per way of asking, and how many argued against it.
iMochaFirst choices, of fourteen modelsMuchSkills
Direct30
Paraphrase201 against iMocha
Comparative10
Budget-constrained02
Scale-constrained01
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 iMocha and MuchSkills 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
GPT-6 Luna
Muse Glimmer 30B
iMocha MuchSkills first choice named as an alternative argued againstblank: not namedEach cell is one answer, iMocha on the left and MuchSkills on the right.

The direct prompt

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

iMocha first, MuchSkills not the choice

3 of 14 modelsMuchSkills was named in the answer but not as the choice, or not at all.
Gemini 3.5 FlashiMocha alternatives: Fuel50, Retrain.ai, TalentGuard
Grok 4.1 FastTalentGuard, iMocha alternatives: 365Talents, Engagedly, Fuel50, Gloat
GLM 4.7 FlashXiMocha alternatives: 365Talents, Fuel50

Neither was the first choice, one was named

3 of 14 modelsThe answer put something else first and named one of the two as an alternative.
DeepSeek V4 FlashTalentGuard alternatives: Lightcast Open Skills, iMocha
Qwen 3.7 FlashTalentGuard, TechWolf alternatives: AG5, Eightfold AI, Gloat, iMocha
Kimi K2TalentGuard alternatives: 365Talents, Fuel50, TechWolf, iMocha

Neither was named

8 of 14 modelsThe answer made no first choice from these two in this category.
Claude Haiku 4.5INOP alternatives: Fuel50, Skillsoft Percipio
GPT-5.4 mini365Talents alternatives: Eightfold AI, SkillPanel
Perplexity Sonar365Talents alternatives: Docebo, Workday Skills Cloud
Mistral SmallFuel50, Neobrain alternatives: TalentGuard, TechWolf
Llama 4 Maverickno first choice
MiniMax M2.5Fuel50, iMocha Skills Intelligence Cloud alternatives: Bryq, Engagedly, TalentGuard WorkforceGPT
GPT-6 LunaWorkday Skills Cloud alternatives: TechWolf
Muse Glimmer 30BTalentGuard alternatives: Eightfold AI, SAP SuccessFactors Skills, Skills Base, Workday Skills Cloud

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
iMocha leads by five points.
iMocha7%#3 of 11
MuchSkills2%#5 of 11
The full small business standing →
Mid-marketThe figures above
iMocha leads by four points.
iMocha9%#3 of 16
MuchSkills5%#6 of 16
The full mid-market standing →
Enterprise
iMocha leads by two points.
iMocha2%#8 of 14
MuchSkills0%#– of 14
The full enterprise standing →

What the models said about iMocha

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

“overkill and cost-prohibitive for most mid-sized B2B firms” DeepSeek V4 Flash · paraphrase prompt · soft negative
“look at Degreed, 360Learning, Cornerstone, iMocha, or Acorn; ... if you want skills verification, look at iMocha” Perplexity Sonar · comparative prompt · first choice
“combined with iMocha or Textkernel Skills Intelligence API for inference capabilities” Grok 4.1 Fast · paraphrase prompt · first choice
“I'd recommend starting with iMocha ... Best all-around choice: iMocha” GPT-5.4 mini · paraphrase prompt · first choice

What the models said about MuchSkills

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

“MuchSkills: Excellent for professional services, engineering, or project-heavy companies needing beautiful, easy-to-read skill matrices and CV builders.” Gemini 3.5 Flash · scale prompt · first choice
“I'd recommend starting with a free trial from Pin or MuchSkills to evaluate which features best match your organization's needs.” Claude Haiku 4.5 · budget prompt · first choice
“Skills Base or MuchSkills are particularly recommended” Mistral Small · budget 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.