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Workforce planning · October 2026 Edition

TeamOhana vs HiBob

One of fourteen models named TeamOhana first on the direct prompt; three named HiBob. TeamOhana was named by eight of the fourteen models and HiBob by ten and TeamOhana carries 13 labels and HiBob 11, so the shares are not directly comparable.

TeamOhana

accepted challenger

Named in two categories this edition.

HiBob

accepted challenger

Named in twenty-four categories this edition.

First-choice share5%5%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate0%9%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#5#7A position in a field of 15; printed, not drawn.
Labels1311A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, TeamOhana reading right to left. Rank and label count are printed, not drawn.ChartHop was named alongside these two in ten of the fourteen direct answers. ChartHop vs TeamOhana · ChartHop vs HiBob · Homebase vs TeamOhana

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 workforce planning page.

By framing

How many of the fourteen models made each the first choice, per way of asking, and how many argued against it.
TeamOhanaFirst choices, of fourteen modelsHiBob
Direct13
Paraphrase20
Comparative00
Budget-constrained00
Scale-constrained00
Negative001 against HiBob
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 TeamOhana and HiBob 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
TeamOhana HiBob first choice named as an alternative argued againstblank: not namedEach cell is one answer, TeamOhana on the left and HiBob on the right.

The direct prompt

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

TeamOhana first, HiBob not the choice

1 of 14 modelsHiBob was named in the answer but not as the choice, or not at all.
GPT-6 LunaTeamOhana alternatives: Pigment, Workday Adaptive Planning

HiBob first, TeamOhana not the choice

3 of 14 modelsTeamOhana was named in the answer but not as the choice, or not at all.
Claude Haiku 4.5ChartHop, HiBob alternatives: Paylocity, Planful, Visier
Grok 4.1 FastHiBob, Rippling alternatives: ChartHop
MiniMax M2.5HiBob alternatives: ChartHop, Paylocity, Rippling

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.
GPT-5.4 miniWorkday Adaptive Planning alternatives: Anaplan, HiBob, Rippling
Gemini 3.5 FlashChartHop alternatives: Aleph, Cube, Lative, Mosaic, Pigment, Runn, TeamOhana
Perplexity SonarPaylocity alternatives: ChartHop, Drivetrain, HiBob, Workday Adaptive Planning

Neither was named

7 of 14 modelsThe answer made no first choice from these two in this category.
Mistral SmallChartHop alternatives: Anaplan, Paylocity, Visier
DeepSeek V4 FlashAbacum, Planful alternatives: ADP Workforce Now, Workday Adaptive Planning
Llama 4 Maverickno first choice
Qwen 3.7 FlashChartHop alternatives: Planful, Rippling, Visier
Kimi K2ChartHop alternatives: Abacum, Paylocity, Planful, Workday Adaptive Planning
GLM 4.7 FlashXChartHop alternatives: Anaplan, Paylocity, Visier, Workday Adaptive Planning
Muse Glimmer 30BAbacum, Planful alternatives: ChartHop, Paylocity, Vena, Visier, Workday Adaptive Planning

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
TeamOhana leads by two points.
TeamOhana2%#8 of 13
HiBob0%#– of 13
The full small business standing →
Mid-marketThe figures above
Level: the same share of first choices.
TeamOhana5%#5 of 15
HiBob5%#7 of 15
The full mid-market standing →
Enterprise
TeamOhana leads by four points.
TeamOhana4%#– of 10
HiBob0%#– of 10
The full enterprise standing →

What the models said about TeamOhana

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

“I'd start with TeamOhana. It's purpose-built to connect Finance, HR, and Talent around a shared hiring plan” GPT-6 Luna · direct prompt · first choice
“My default recommendation: TeamOhana” GPT-6 Luna · paraphrase prompt · first choice
“## Top Recommendation: TeamOhana” MiniMax M2.5 · paraphrase prompt · first choice

What the models said about HiBob

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

“HiBob is best for mid-market people analytics and engagement, combining customizable reporting, performance management, and culture-building features” Claude Haiku 4.5 · direct 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.