Five of fourteen models named Microsoft Power Automate Process Mining first on the direct prompt; three named UiPath Process Mining. Both were named by all fourteen models and Microsoft Power Automate Process Mining carries 47 labels and UiPath Process Mining 56, so the shares are not directly comparable.
Named in one category 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 process mining page.
Across every category in the November 2026 Edition, Microsoft Power Automate Process Mining and UiPath Process Mining were named in the same answer eighty-nine times, of the 124 answers naming Microsoft Power Automate Process Mining and the 164 naming UiPath Process Mining. In those answers UiPath Process Mining took the first choice one time and Microsoft Power Automate Process Mining twenty-five.
| Model | DirectMP | ParaphraseMP | ComparativeMP | Budget-constrainedMP | Scale-constrainedMP | NegativeMP |
|---|---|---|---|---|---|---|
| Claude Haiku 4.5 | MP | MP | MP | |||
| GPT-5.4 mini | MP | |||||
| Gemini 3.5 Flash | MP | MP | MP | MP | MP | |
| Perplexity Sonar | MP | MP | MP | |||
| Grok 4.20 | MP | MP | MP | MP | ||
| Mistral Small | MP | MP | MP | |||
| DeepSeek V4 Flash | MP | MP | MP | |||
| Llama 4 Maverick | MP | MP | ||||
| Qwen 3.7 Flash | MP | MP | MP | |||
| Kimi K2 | MP | MP | MP | MP | ||
| GLM 4.7 FlashX | MP | MP | MP | |||
| MiniMax M2.5 | MP | MP | MP | |||
| GPT-6 Luna | MP | MP | MP | MP | ||
| Muse Glimmer 30B | MP | MP |
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.
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of eight in this category shown.
“Frequently called "terrible" in user forums for poor UX ... Alternatives if avoiding: Look at more robust options like Celonis or Apromore” Grok 4.20 · negative prompt · hard negative
“the most frequently criticized process mining tool in user communities” DeepSeek V4 Flash · negative prompt · hard negative
“check capacity and licensing carefully if you expect large analyses or many users” GPT-6 Luna · negative prompt · soft negative
“Best budget-friendly default: Microsoft Power Automate Process Mining—if your company already uses Microsoft’s Power Platform.” GPT-6 Luna · budget prompt · first choice
“Microsoft Power Automate Process Mining (part of the Power Platform) is often the best fit for a mid-market B2B company.” Grok 4.20 · direct prompt · first choice
“Microsoft Power Automate Process Mining and Apromore are widely considered the most cost-effective solutions.” Qwen 3.7 Flash · budget prompt · first choice
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of eight in this category shown.
“mid-to-high cost and overkill for limited budgets” Grok 4.20 · budget prompt · hard negative
“shallower analytics depth than pure process mining leaders; challenges with large datasets, data integration ... Pricing and complexity can overwhelm.” Grok 4.20 · negative prompt · soft negative
“UiPath can connect mining to RPA, but rule-based automation may become brittle when processes change frequently” Perplexity Sonar · negative prompt · soft negative
“Microsoft Power Automate (Process Mining) and UiPath generally offer the strongest balance of capability, price, and ease of implementation” Qwen 3.7 Flash · direct prompt · first choice
“generally considered to be Apromore, UiPath Process Mining, and ABBYY Timeline” Mistral Small · direct prompt · first choice
“Best Overall for Most Mid-Market Companies: UiPath Process Mining” GLM 4.7 FlashX · paraphrase prompt · first choice
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.