Matter vs Achievers
Zero of fourteen models named Matter first on the direct prompt; zero named Achievers. Matter was named by ten of the fourteen models and Achievers by fourteen and Matter carries 17 labels and Achievers 27, so the shares are not directly comparable.
Named in three categories this edition.
Named in two categories this edition.
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 recognition and rewards page.
By framing
MatterFirst choices, of fourteen modelsAchievers
Across every category in the November 2026 Edition, Matter and Achievers were named in the same answer fourteen times, of the 52 answers naming Matter and the 115 naming Achievers. In those answers Achievers took the first choice three times and Matter one.
Every model, every framing
| Model | Direct | Paraphrase | Comparative | Budget-constrained | Scale-constrained | Negative |
|---|---|---|---|---|---|---|
| Claude Haiku 4.5 | | | | | ||
| GPT-5.4 mini | | | | |||
| Gemini 3.5 Flash | | | ||||
| Perplexity Sonar | | | | |||
| Grok 4.20 | | | ||||
| 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 | |
Matter Achievers first choice named as an alternative argued againstblank: not namedEach cell is one answer, Matter on the left and Achievers on the right.The direct prompt
Neither was the first choice, one was named
2 of 14 modelsThe answer put something else first and named one of the two as an alternative.Neither was named
12 of 14 modelsThe answer made no first choice from these two in this category.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
Matter11%#2 of 13Achievers0%#12 of 13Achievers21%#3 of 10Matter2%#– of 10What the models said about Matter
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Three of four in this category shown.
“1. Matter *(Best for Slack & Microsoft Teams)* ... Free plan available; Paid plans start around $1–$2 per user/month.” Gemini 3.5 Flash · budget prompt · first choice
“A recognition platform designed to work inside Slack and Microsoft Teams, with a free plan available” Claude Haiku 4.5 · budget prompt · first choice
“or Matter if you want to move quickly with an existing Slack/Teams integration” Claude Haiku 4.5 · paraphrase 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 seven in this category shown.
“Enterprise-grade platforms (like older versions of Achievers or smaller boutique providers) that charge high setup fees or lock you into annual contracts” Qwen 3.7 Flash · negative prompt · soft negative
“but it may be overkill (and pricier) for pure mid-sized use” Grok 4.20 · paraphrase prompt · soft negative
“Not overly enterprise-heavy like Achievers or Workhuman” Grok 4.20 · direct prompt · soft negative
“Choose Workhuman/Achievers if you need deep analytics, global scalability, and alignment with formal performance goals.” Qwen 3.7 Flash · comparative prompt · first choice
“Best Overall: Achievers” Claude Haiku 4.5 · paraphrase prompt · first choice
“Large or multinational organizations | More structured, enterprise-oriented programs... Likely more platform and setup than a smaller team needs.” GPT-6 Luna · comparative prompt · alternative
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.