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Coaching platforms · October 2026 Edition

15Five vs CoachHub

Two of fourteen models named 15Five first on the direct prompt; zero named CoachHub. 15Five was named by nine of the fourteen models and CoachHub by thirteen and 15Five carries 11 labels and CoachHub 40, so the shares are not directly comparable.

15Five

accepted challenger

Named in ten categories this edition.

CoachHub

criticized challenger

Named in two categories this edition.

First-choice share9%4%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate0%30%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#4#8A position in a field of 13; printed, not drawn.
Labels1140A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, 15Five reading right to left. Rank and label count are printed, not drawn.Growthspace was named alongside these two in ten of the fourteen direct answers. Growthspace vs 15Five · Growthspace vs CoachHub · Exec vs 15Five

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 coaching 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.
15FiveFirst choices, of fourteen modelsCoachHub
Direct202 against CoachHub
Paraphrase02
Comparative01
Budget-constrained307 against CoachHub
Scale-constrained00
Negative003 against CoachHub
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 and CoachHub 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
15Five CoachHub first choice named as an alternative argued againstblank: not namedEach cell is one answer, 15Five on the left and CoachHub on the right.

The direct prompt

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

15Five first, CoachHub an alternative

2 of 14 modelsCoachHub was named in the answer but not as the choice, or not at all.
Kimi K215Five, Lattice alternatives: Betterworks, CoachHub, Growthspace
GPT-6 Luna15Five alternatives: BetterUp, Gong, Mindtickle, Torch

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.
GPT-5.4 miniLattice alternatives: CoachHub, Culture Amp, Torch, Valence
Grok 4.1 FastLattice alternatives: 15Five, Betterworks, CoachHub, Jiminny, Leapsome, Showpad Coach
GLM 4.7 FlashXBetterUp alternatives: CoachHub, Growthspace
MiniMax M2.5no first choice alternatives: BetterUp, CoachHub, Growthspace

Neither was named

8 of 14 modelsThe answer made no first choice from these two in this category.
Claude Haiku 4.5Boon Health, Torch alternatives: Avoma, Coachello, Gong, Growthspace, Risely, Sounding Board
Gemini 3.5 FlashGrowthspace, Jiminny alternatives: Avoma, Boon Health, Cloverleaf
Perplexity SonarTorch alternatives: Betterworks, Cloverleaf, Lattice
Mistral SmallGrowthspace alternatives: Coachello, Motivosity
DeepSeek V4 FlashGrowthspace, Lattice alternatives: Betterworks
Llama 4 MaverickTorch alternatives: Growthspace, Lattice, Motivosity
Qwen 3.7 FlashLattice alternatives: Growthspace, Motivosity
Muse Glimmer 30BTorch alternatives: Boon Health, Exec, Growthspace

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 leads by four points.
15Five11%#1 of 10
CoachHub7%#2 of 10
The full small business standing →
Mid-marketThe figures above
15Five leads by five points.
15Five9%#4 of 13
CoachHub4%#8 of 13
The full mid-market standing →
Enterprise
The order flips: CoachHub leads at enterprise.
CoachHub17%#2 of 12
15Five0%#– of 12
The full enterprise standing →

What the models said about 15Five

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

“Winner: 15Five 15Five is widely considered the gold standard for affordable, user-friendly continuous coaching.” Qwen 3.7 Flash · budget prompt · first choice
“I'd recommend starting with 15Five given its extremely low starting price of $4/user/month” Claude Haiku 4.5 · budget prompt · first choice

What the models said about CoachHub

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

“CoachHub - Employee concerns include: - Low salaries and pay transparency issues - Leadership concerns and "gaslighting" in business reviews” GLM 4.7 FlashX · negative prompt · hard negative
“Enterprise platforms to avoid (for tight budgets): BetterUp, CoachHub, Torch, and EZRA” MiniMax M2.5 · budget prompt · hard negative
“Avoid These (Due to Cost)... Enterprise-focused with volume pricing and high minimums.” DeepSeek V4 Flash · budget prompt · hard negative
“I would recommend CoachHub as the strongest default choice for a digital coaching marketplace” Perplexity Sonar · paraphrase prompt · first choice
“Large organization (1000+ employees) → BetterUp or CoachHub” Kimi K2 · comparative prompt · first choice
“CoachHub is the conventional mid-market choice” Muse Glimmer 30B · paraphrase 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.