Workforce planning · October 2026 Edition
Abacum vs HiBob
Two of fourteen models named Abacum first on the direct prompt; three named HiBob. Abacum was named by eight of the fourteen models and HiBob by ten and Abacum carries 12 labels and HiBob 11, so the shares are not directly comparable.
Named in one category this edition.
Named in twenty-four categories this edition.
First-choice share9%5%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate8%9%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#3#7A position in a field of 15; printed, not drawn.
Labels1211A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, Abacum 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 Abacum · ChartHop vs HiBob · Homebase vs Abacum
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.
AbacumFirst choices, of fourteen modelsHiBob
Direct23
Paraphrase20
Comparative00
Budget-constrained00
Scale-constrained10
Negative001 against Abacum · 1 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 Abacum and HiBob stood in it.
| Model | Direct | Paraphrase | Comparative | Budget-constrained | Scale-constrained | Negative |
|---|---|---|---|---|---|---|
| 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 | | |
Abacum HiBob first choice named as an alternative argued againstblank: not namedEach cell is one answer, Abacum on the left and HiBob on the right.The direct prompt
The plain question, one answer per model, grouped by where Abacum and HiBob stood in it.
Abacum first, HiBob not the choice
2 of 14 modelsHiBob was named in the answer but not as the choice, or not at all.DeepSeek V4 FlashAbacum, Planful alternatives: ADP Workforce Now, Workday Adaptive Planning
Muse Glimmer 30BAbacum, Planful alternatives: ChartHop, Paylocity, Vena, Visier, Workday Adaptive Planning
HiBob first, Abacum not the choice
3 of 14 modelsAbacum 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
Perplexity SonarPaylocity alternatives: ChartHop, Drivetrain, HiBob, Workday Adaptive Planning
Kimi K2ChartHop alternatives: Abacum, Paylocity, Planful, Workday Adaptive Planning
Neither was named
6 of 14 modelsThe answer made no first choice from these two in this category.Gemini 3.5 FlashChartHop alternatives: Aleph, Cube, Lative, Mosaic, Pigment, Runn, TeamOhana
Mistral SmallChartHop alternatives: Anaplan, Paylocity, Visier
Llama 4 Maverickno first choice
Qwen 3.7 FlashChartHop alternatives: Planful, Rippling, Visier
GLM 4.7 FlashXChartHop alternatives: Anaplan, Paylocity, Visier, Workday Adaptive Planning
GPT-6 LunaTeamOhana alternatives: Pigment, 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
Level: the same share of first choices.
Abacum0%#– of 13HiBob0%#– of 13Mid-marketThe figures above
Enterprise
Level: the same share of first choices.
Abacum0%#– of 10HiBob0%#– of 10What the models said about Abacum
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Four of five in this category shown.
“avoid Abacum/Rippling for large enterprises” Grok 4.1 Fast · negative prompt · soft negative
“If you need Finance and HR to plan in the same model with scenario what-ifs and budget alignment, start with Abacum.” Muse Glimmer 30B · paraphrase prompt · first choice
“I'd recommend Abacum as the top pick if you need cross-functional planning with solid finance integration” DeepSeek V4 Flash · paraphrase prompt · first choice
“Planful or Abacum will deliver the strongest value without enterprise-level costs and complexity.” DeepSeek V4 Flash · direct 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
ChartHop vs AbacumChartHop vs HiBobHomebase vs AbacumHomebase vs HiBobAbacum vs Workday Adaptive PlanningAbacum vs TeamOhanaAbacum vs PlanfulAbacum vs RipplingWorkday Adaptive Planning vs HiBobTeamOhana vs HiBobPlanful vs HiBobHiBob vs RipplingAll twenty-eight head-to-head pages and the full workforce planning standing
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.