Minoa vs ValueCore
Two of fourteen models named Minoa first on the direct prompt; one named ValueCore. Minoa was named by thirteen of the fourteen models and ValueCore by twelve and Minoa carries 27 labels and ValueCore 26, so the shares are not directly comparable.
Named in one category this edition.
ValueCore
accepted challengerNamed 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 value selling tools page.
By framing
MinoaFirst choices, of fourteen modelsValueCoreAcross every category in the October 2026 Edition, Minoa and ValueCore were named in the same answer thirty-four times, of the 55 answers naming Minoa and the 69 naming ValueCore. In those answers ValueCore took the first choice three times and Minoa five.
Every model, every framing
| Model | DirectVA | ParaphraseVA | ComparativeVA | Budget-constrainedVA | Scale-constrainedVA | NegativeVA |
|---|---|---|---|---|---|---|
| Claude Haiku 4.5 | VA | |||||
| GPT-5.4 mini | | |||||
| Gemini 3.5 Flash | | | VA | |||
| Perplexity Sonar | VA | VA | VA | |||
| Grok 4.1 Fast | | VA | VA | | VA | |
| Mistral Small | VA | | ||||
| DeepSeek V4 Flash | | | | |||
| Llama 4 Maverick | | |||||
| Qwen 3.7 Flash | VA | |||||
| Kimi K2 | | VA | VA | |||
| GLM 4.7 FlashX | VA | VA | ||||
| MiniMax M2.5 | VA | VA | ||||
| GPT-6 Luna | VA | VA | ||||
| Muse Glimmer 30B | | VA |
MinoaVA ValueCore first choice named as an alternative argued againstblank: not namedEach cell is one answer, Minoa on the left and ValueCore on the right.The direct prompt
Minoa first, ValueCore not the choice
2 of 14 modelsValueCore was named in the answer but not as the choice, or not at all.ValueCore first, Minoa not the choice
1 of 14 modelsMinoa was named in the answer but not as the choice, or not at all.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
9 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
Minoa21%#1 of 10What the models said about Minoa
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Three of four in this category shown.
“For most mid-sized B2B teams without a full value-selling team, Minoa gives the best balance of CRM-linked ROI/TCO modeling + AI-assisted case creation” Muse Glimmer 30B · paraphrase prompt · first choice
“Choose Minoa if you sell B2B SaaS, want deep CRM integration, and want AI to help your AEs write the business case narrative.” Gemini 3.5 Flash · paraphrase prompt · first choice
“Choose Minoa or The ROI Shop ... if you are selling high-contract-value B2B software/services and need a sales-first tool” Gemini 3.5 Flash · budget prompt · first choice
What the models said about ValueCore
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Four of five in this category shown.
“ValueCore: Limited functionality/integrations, non-intuitive backend (hard for live meetings), poor multi-offer support.” Grok 4.1 Fast · negative prompt · soft negative
“This is a veteran in ROI modeling... making it a robust choice for mid-sized B2B sales teams that need flexibility and depth in their business cases.” Mistral Small · paraphrase prompt · first choice
“I'd recommend ValueCore (formerly VisualizeROI) as a strong starting point for an ROI calculator and business case platform.” Grok 4.1 Fast · paraphrase prompt · first choice
“I'd recommend ValueCore (formerly VisualizeROI) as the strongest first choice” Perplexity Sonar · 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.