Four of fourteen models named Absorb LMS first on the direct prompt; zero named Emtrain. Absorb LMS was named by eleven of the fourteen models and Emtrain by eight and Absorb LMS carries 17 labels and Emtrain 12, so the shares are not directly comparable.
Named in six categories this edition.
Named in one category 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 compliance training page.
| 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 |
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.
No label in this category carried a quote.
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Three of four in this category shown.
“Emtrain and TechClass are often highlighted for their balance of quality, scalability, and value.” Mistral Small · paraphrase prompt · first choice
“Best For: Organizations seeking to use compliance training to actively diagnose and fix toxic workplace culture.” Gemini 3.5 Flash · comparative prompt · alternative
“Reputable alternatives often cited positively: Traliant, Emtrain, LRN, Everfi, BizLibrary, Skillsoft” Grok 4.1 Fast · negative 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.