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Recognition and rewards · September 2026 Edition

Bonusly vs Achievers

Three of twelve models named Bonusly first on the direct prompt; one named Achievers. Both were named by all twelve models and Bonusly carries 48 labels and Achievers 27, so the shares are not directly comparable.

Bonusly

accepted challenger

Named in four categories this edition.

Achievers

accepted challenger

Named in one category this edition.

First-choice share22%5%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate2%22%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#1#8A position in a field of 12; printed, not drawn.
Labels4827A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, Bonusly reading right to left. Rank and label count are printed, not drawn.Nectar was named alongside these two in eleven of the twelve direct answers. Bonusly vs Nectar · Bonusly vs Matter · Bonusly vs Motivosity

Share is the count of first choices across the direct, paraphrase, budget and scale prompts over all twelve 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 recognition and rewards page.

By framing

How many of the twelve models made each the first choice, per way of asking, and how many argued against it.
BonuslyFirst choices, of twelve modelsAchievers
Direct311 against Achievers
Paraphrase311 against Achievers
Comparative001 against Achievers
Budget-constrained30
Scale-constrained00
Negative001 against Bonusly · 3 against Achievers
Bars are first choices, 0 to 12 each sideModels that argued againstA model can name both, so the two sides of a row do not sum to twelve.

Across every category in the September 2026 Edition, Bonusly and Achievers were named in the same answer fifty-three times, of the 166 answers naming Bonusly and the 89 naming Achievers. In those answers Achievers took the first choice eight times and Bonusly eight.

Every model, every framing

The seventy-two answers behind the chart above, one cell each: where Bonusly and Achievers 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
Bonusly Achievers first choice named as an alternative argued againstblank: not namedEach cell is one answer, Bonusly on the left and Achievers on the right.

The direct prompt

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

Bonusly first, Achievers an alternative

3 of 12 modelsAchievers was named in the answer but not as the choice, or not at all.
GPT-5.4 miniBonusly alternatives: Achievers, Awardco, Motivosity, Workhuman
Gemini 3.5 FlashBonusly alternatives: Awardco, Nectar, WorkTango
Kimi K2Bonusly alternatives: Awardco, Motivosity, Nectar, WorkTango

Achievers first, Bonusly an alternative

1 of 12 modelsBonusly was named in the answer but not as the choice, or not at all.
MiniMax M2.5Achievers alternatives: Awardco, Bonusly, Nectar, Workhuman

Neither was the first choice, one was named

6 of 12 modelsThe answer put something else first and named one of the two as an alternative.
Claude Haiku 4.5Nectar alternatives: Achievers, Awardco, Bonusly, Motivosity
Perplexity SonarNectar alternatives: Achievers
Grok 4.1 FastAwardco alternatives: Bonusly, Nectar
DeepSeek V4 FlashNectar alternatives: Bonusly, Workhuman
Qwen 3.7 FlashNectar alternatives: Achievers, Bonusly, Tremendous
GLM 4.7 FlashXNectar, Workhuman alternatives: Achievers, Bonusly, Vantage Circle

Neither was named

2 of 12 modelsThe answer made no first choice from these two in this category.
Mistral SmallMotivosity, Nectar alternatives: Snappy, Workhuman
Llama 4 MaverickNectar alternatives: Motivosity, Recognize

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
Bonusly leads by sixty points.
Bonusly60%#1 of 8
Achievers0%#– of 8
The full small business standing →
Mid-marketThe figures above
Bonusly leads by seventeen points.
Bonusly22%#1 of 12
Achievers5%#8 of 12
The full mid-market standing →
Enterprise
The order flips: Achievers leads at enterprise.
Achievers38%#1 of 10
Bonusly2%#5 of 10
The full enterprise standing →

What the models said about Bonusly

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

“Desktop-focused, limited custom rewards, basic analytics, and required monthly point caps that can add unexpected costs.” Mistral Small · negative prompt · soft negative
“start with Matter (free or $1/user/month) or Bonusly (free plan available). Both are highly rated” Mistral Small · budget prompt · first choice
“For most small companies with limited budgets, Bonusly offers the best balance” DeepSeek V4 Flash · budget prompt · first choice
“Bonusly — *Best Overall for High Adoption and B2B Tech Cultures*” Gemini 3.5 Flash · direct prompt · first choice

What the models said about Achievers

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

“Limited points/rewards budgets: Frequent complaints (e.g., in Motivosity, Kudos, Achievers)... custom reports delayed in others like Achievers.” Grok 4.1 Fast · negative prompt · soft negative
“Scaling penalties, add-on modules, and professional service fees can significantly increase costs.” Mistral Small · negative prompt · soft negative
“Platforms like *O.C. Tanner* or *Achievers* require 1–3 months of custom implementation” Gemini 3.5 Flash · comparative prompt · soft negative
“If I had to pick one default recommendation for a mid-sized B2B org, I'd choose Achievers” Perplexity Sonar · paraphrase prompt · first choice
“### 1. Achievers (Best for Scaling Culture)” MiniMax M2.5 · direct prompt · first choice
“Best for large-scale/global enterprise-style recognition: Workhuman or Achievers” GPT-5.4 mini · direct prompt · alternative
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.