Four of fourteen models named Microsoft Power Automate Process Mining first on the direct prompt; zero named IBM Process Mining. Microsoft Power Automate Process Mining was named by eleven of the fourteen models and IBM Process Mining by fourteen and Microsoft Power Automate Process Mining carries 21 labels and IBM Process Mining 37, 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 October 2026 Edition, Microsoft Power Automate Process Mining and IBM Process Mining were named in the same answer thirty-seven times, of the 62 answers naming Microsoft Power Automate Process Mining and the 107 naming IBM Process Mining. In those answers IBM Process Mining took the first choice one time and Microsoft Power Automate Process Mining fourteen.
| Model | DirectMPIP | ParaphraseMPIP | ComparativeMPIP | Budget-constrainedMPIP | Scale-constrainedMPIP | NegativeMPIP |
|---|---|---|---|---|---|---|
| Claude Haiku 4.5 | MPIP | IP | ||||
| GPT-5.4 mini | IP | |||||
| Gemini 3.5 Flash | MP | MP | MPIP | MP | IP | MPIP |
| Perplexity Sonar | MP | IP | MP | MP | ||
| Grok 4.1 Fast | IP | MPIP | IP | |||
| Mistral Small | IP | MPIP | ||||
| DeepSeek V4 Flash | MPIP | IP | MP | IP | IP | |
| Llama 4 Maverick | IP | |||||
| Qwen 3.7 Flash | IP | IP | IP | |||
| Kimi K2 | MP | IP | MPIP | IP | ||
| GLM 4.7 FlashX | MPIP | |||||
| MiniMax M2.5 | MPIP | IP | IP | |||
| GPT-6 Luna | MP | MP | MP | |||
| Muse Glimmer 30B | MP | IP | IP | IP |
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 seven in this category shown.
“Avoid or be cautious with Microsoft Power Automate Process Mining if you expect high volumes” Mistral Small · negative prompt · hard negative
“I wouldn’t start with Microsoft Power Automate Process Mining if the budget is especially tight” GPT-6 Luna · budget prompt · soft negative
“it can carry heavy add-on licensing costs (such as a $5,000/month tenant capacity add-on)” Gemini 3.5 Flash · negative prompt · soft negative
“Best for Microsoft-Centric Companies: Microsoft Power Automate Process Mining ... this is the most seamless and cost-effective commercial option.” Gemini 3.5 Flash · budget prompt · first choice
“Best Overall & Best for Microsoft Ecosystems: Microsoft Power Automate Process Mining (formerly Minit)” Gemini 3.5 Flash · direct prompt · first choice
“UiPath Process Mining or Microsoft Power Automate Process Mining are the safest bets” DeepSeek V4 Flash · direct 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.
“What I would avoid on a limited budget: Celonis, IBM Process Mining, and similar enterprise suites” GPT-5.4 mini · budget prompt · hard negative
“~$4,250/month and enterprise-governance-focused — overkill for most mid-market teams.” DeepSeek V4 Flash · direct prompt · hard negative
“IBM Process Mining starts at ~$4,250/month — still expensive for SMBs” DeepSeek V4 Flash · budget prompt · hard negative
“I would recommend IBM Process Mining if you want a process intelligence platform that is explicitly described as *tailored more to midsize organizations*” Perplexity Sonar · paraphrase prompt · first choice
“For most mid-sized B2B companies, IBM Process Mining or SAP Signavio are the best recommendations.” Mistral Small · paraphrase prompt · first choice
“Mid-Market & Agile Specialized Tools (e.g., Apromore, Fluxicon Disco, IBM Process Mining)” Gemini 3.5 Flash · scale 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.