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Skills intelligence · October 2026 Edition

TechWolf vs MuchSkills

One of fourteen models named TechWolf first on the direct prompt; zero named MuchSkills. TechWolf was named by eight of the fourteen models and MuchSkills by eight and both carry 11 labels, so the shares below are directly comparable.

TechWolf

accepted challenger

Named in one category this edition.

MuchSkills

accepted challenger

Named in one category this edition.

First-choice share7%5%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 16; printed, not drawn.
Labels1111Equal, which is what makes the shares comparable.
The two percentage rows are drawn on one 0 to 100 track, TechWolf reading right to left. Rank and label count are printed, not drawn.Skills Base vs TechWolf · Skills Base vs MuchSkills · TalentGuard vs TechWolf

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.
TechWolfFirst choices, of fourteen modelsMuchSkills
Direct10
Paraphrase20
Comparative00
Budget-constrained02
Scale-constrained11
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 TechWolf 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
TechWolf MuchSkills first choice named as an alternative argued againstblank: not namedEach cell is one answer, TechWolf on the left and MuchSkills on the right.

The direct prompt

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

TechWolf first, MuchSkills not the choice

1 of 14 modelsMuchSkills was named in the answer but not as the choice, or not at all.
Qwen 3.7 FlashTalentGuard, TechWolf alternatives: AG5, Eightfold AI, Gloat, iMocha

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.
Mistral SmallFuel50, Neobrain alternatives: TalentGuard, TechWolf
Kimi K2TalentGuard alternatives: 365Talents, Fuel50, TechWolf, iMocha
GPT-6 LunaWorkday Skills Cloud alternatives: TechWolf

Neither was named

10 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
Gemini 3.5 FlashiMocha alternatives: Fuel50, Retrain.ai, TalentGuard
Perplexity Sonar365Talents alternatives: Docebo, Workday Skills Cloud
Grok 4.1 FastTalentGuard, iMocha alternatives: 365Talents, Engagedly, Fuel50, Gloat
DeepSeek V4 FlashTalentGuard alternatives: Lightcast Open Skills, iMocha
Llama 4 Maverickno first choice
GLM 4.7 FlashXiMocha alternatives: 365Talents, Fuel50
MiniMax M2.5Fuel50, iMocha Skills Intelligence Cloud alternatives: Bryq, Engagedly, TalentGuard WorkforceGPT
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
MuchSkills leads by two points.
MuchSkills2%#5 of 11
TechWolf0%#– of 11
The full small business standing →
Mid-marketThe figures above
The order flips: TechWolf leads at mid-market.
TechWolf7%#5 of 16
MuchSkills5%#6 of 16
The full mid-market standing →
Enterprise
TechWolf leads by ten points.
TechWolf10%#2 of 14
MuchSkills0%#– of 14
The full enterprise standing →

What the models said about TechWolf

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

“TalentGuard or TechWolf offer the best balance of functionality, ease of use, and cost.” Qwen 3.7 Flash · direct prompt · first choice
“TechWolf or 365Talents: Highly regarded for "skills inference"” Gemini 3.5 Flash · scale prompt · first choice
“## Recommended Inference Tool: TechWolf” GLM 4.7 FlashX · 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.