ValueCore vs LeveragePoint
One of fourteen models named ValueCore first on the direct prompt; two named LeveragePoint. ValueCore was named by twelve of the fourteen models and LeveragePoint by eight and ValueCore carries 26 labels and LeveragePoint 12, so the shares are not directly comparable.
ValueCore
accepted challengerNamed 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 value selling tools page.
By framing
Across every category in the October 2026 Edition, ValueCore and LeveragePoint were named in the same answer eleven times, of the 69 answers naming ValueCore and the 31 naming LeveragePoint. In those answers LeveragePoint took the first choice one time and ValueCore one.
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 |
LeveragePointVA first choiceVA named as an alternativeVA argued againstblank: not namedEach cell is one answer, ValueCore on the left and LeveragePoint on the right.The direct prompt
ValueCore first, LeveragePoint not the choice
1 of 14 modelsLeveragePoint was named in the answer but not as the choice, or not at all.LeveragePoint first, ValueCore not the choice
2 of 14 modelsValueCore 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
LeveragePoint3%#– of 11LeveragePoint4%#6 of 10LeveragePoint2%#8 of 11What 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
What the models said about LeveragePoint
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Four of five in this category shown.
“enterprise-focused pricing and complexity” DeepSeek V4 Flash · direct prompt · soft negative
“mid-market teams that want a purpose-built quantification engine with collaborative Value Models often start with LeveragePoint” Muse Glimmer 30B · direct prompt · first choice
“my mid-market pick is LeveragePoint for a team building a repeatable value-selling process” GPT-6 Luna · direct prompt · first choice
“Choose LeveragePoint if you want to align product, pricing, and sales teams around a unified value narrative.” Kimi K2 · 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.