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HR AI assistants · November 2026 Edition

Leena AI vs HiBob

Three of fourteen models named Leena AI first on the direct prompt; seven named HiBob. Leena AI was named by fourteen of the fourteen models and HiBob by eleven and Leena AI carries 42 labels and HiBob 12, so the shares are not directly comparable.

Leena AI

accepted challenger

Named in two categories this edition.

HiBob

accepted challenger

Named in twenty-two categories this edition.

First-choice share12%12%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate10%0%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#2#3A position in a field of 14; printed, not drawn.
Labels4212A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, Leena AI reading right to left. Rank and label count are printed, not drawn.Rippling was named alongside these two in eleven of the fourteen direct answers. MeBeBot vs Leena AI · MeBeBot vs HiBob · Leena AI vs ChatGPT

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 HR AI assistants page.

By framing

How many of the fourteen models made each the first choice, per way of asking, and how many argued against it.
Leena AIFirst choices, of fourteen modelsHiBob
Direct37
Paraphrase403 against Leena AI
Comparative60
Budget-constrained001 against Leena AI
Scale-constrained00
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 Leena AI and HiBob stood in it.
ModelDirectParaphraseComparativeBudget-constrainedScale-constrainedNegative
Claude Haiku 4.5
GPT-5.4 mini
Gemini 3.5 Flash
Perplexity Sonar
Grok 4.20
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
Leena AI HiBob first choice named as an alternative argued againstblank: not namedEach cell is one answer, Leena AI on the left and HiBob on the right.

The direct prompt

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

Leena AI first, HiBob an alternative

3 of 14 modelsHiBob was named in the answer but not as the choice, or not at all.
Claude Haiku 4.5Leena AI alternatives: ChatGPT, HiBob, Lattice, Workable
GPT-5.4 miniLeena AI, Zendesk Employee Service Suite alternatives: HiBob, Rippling
Perplexity SonarLeena AI alternatives: Ask BambooHR, Harmony, Lattice, Rippling, Workativ Assistant

HiBob first, Leena AI an alternative

7 of 14 modelsLeena AI was named in the answer but not as the choice, or not at all.
Gemini 3.5 FlashHiBob alternatives: Ask BambooHR, Lattice, Leena AI, Metaview, Moveworks, Paradox, Rippling, Workativ Assistant
Grok 4.20HiBob alternatives: Leena AI, Microsoft Copilot, Moveworks, Workativ Assistant
Qwen 3.7 FlashHiBob alternatives: Harmony, Leena AI, Rippling, eesel AI
Kimi K2HiBob alternatives: BambooHR with Bamboo AI, Leena AI, Paradox
GLM 4.7 FlashXHiBob, Wisq Harper alternatives: Leena AI, MeBeBot, Rippling
MiniMax M2.5HiBob, MeBeBot alternatives: Leena AI, Rippling, Workativ Assistant
Muse Glimmer 30BHiBob, MeBeBot alternatives: Atomicwork, Harmony, Leena AI, Paradox, Rippling, Workday Illuminate

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 SmallMeBeBot alternatives: Harmony, HiBob, Leena AI, Rippling, eesel AI
DeepSeek V4 FlashRippling alternatives: HiBob, Leena AI, MeBeBot
Llama 4 MaverickMeBeBot alternatives: Atomicwork, Harmony, HiBob's Bob, Leena AI, Rippling, Wisq Harper

Neither was named

1 of 14 modelsThe answer made no first choice from these two in this category.
GPT-6 LunaWorkativ Assistant alternatives: MeBeBot, Moveworks, Rippling

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
Leena AI leads by two points.
Leena AI2%#8 of 12
HiBob0%#– of 12
The full small business standing →
Mid-marketThe figures above
Level: the same share of first choices.
Leena AI12%#2 of 14
HiBob12%#3 of 14
The full mid-market standing →
Enterprise
HiBob is not named for this buyer.
Leena AI24%#2 of 7
HiBob—not named
The full enterprise standing →

What the models said about Leena AI

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

“Avoid Leena AI unless you have enterprise-scale complexity and budget” Kimi K2 · paraphrase prompt · hard negative
“Avoid Leena AI unless you're approaching 1,000+ employees” MiniMax M2.5 · paraphrase prompt · hard negative
“consider Leena AI, but be aware it's designed with larger enterprises in mind and may be overkill for your size” DeepSeek V4 Flash · paraphrase prompt · soft negative
“Best for: Enterprise employee self-service and helpdesk deflection ... Uses WorkLM, a proprietary LLM trained specifically on enterprise HR content” DeepSeek V4 Flash · comparative prompt · first choice
“Leena AI and ServiceNow are leading this transition with promises of 70%+ ticket auto-resolution and proactive automation.” MiniMax M2.5 · comparative prompt · first choice
“the best overall choice for a mid-market B2B company is usually Leena AI or Zendesk Employee Service” GPT-5.4 mini · direct prompt · first choice

What the models said about HiBob

No label in this category carried a quote.

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.