incentX vs Flintfox
One of fourteen models named incentX first on the direct prompt; zero named Flintfox. incentX was named by nine of the fourteen models and Flintfox by eleven and incentX carries 15 labels and Flintfox 24, 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 rebate management page.
By framing
incentXFirst choices, of fourteen modelsFlintfox
Across every category in the October 2026 Edition, incentX and Flintfox were named in the same answer seven times, of the 51 answers naming incentX and the 42 naming Flintfox. In those answers Flintfox took the first choice zero times and incentX one.
Every model, every framing
| 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 | |
incentX Flintfox first choice named as an alternative argued againstblank: not namedEach cell is one answer, incentX on the left and Flintfox on the right.The direct prompt
incentX first, Flintfox not the choice
1 of 14 modelsFlintfox was named in the answer but not as the choice, or not at all.Neither was the first choice, one was named
6 of 14 modelsThe answer put something else first and named one of the two as an alternative.Neither was named
7 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
incentX13%#4 of 11Flintfox2%#6 of 11incentX0%#– of 7Flintfox0%#– of 7What the models said about incentX
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Three of four in this category shown.
“incentX (Best for Traditional B2B Rebates & Trade Spend) ... frequently cited as a top contender for SMBs” Qwen 3.7 Flash · budget prompt · first choice
“incentX – Best for sales-driven rebate automation and transaction-aware incentive programs.” Mistral Small · direct prompt · first choice
“Best Overall for B2B Rebates & Commissions: incentX” Gemini 3.5 Flash · budget prompt · first choice
What the models said about Flintfox
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of seven in this category shown.
“Flintfox | Enterprise-focused with custom pricing” Kimi K2 · budget prompt · hard negative
“Having multiple non-standard documents will affect how your organisation passes rebates onto customers and is likely to cause issues down the line” Claude Haiku 4.5 · negative prompt · soft negative
“Flintfox by Enable — ask for recent, comparable customer references.” GPT-6 Luna · negative prompt · soft negative
“Recognized as a global leader in trade revenue management... particularly well-suited for mid-size businesses with complex rebate structures” Mistral Small · paraphrase prompt · first choice
“Flintfox excels in managing retrospective discounts, tiered incentives, and performance-based rebates with precision and transparency” Claude Haiku 4.5 · direct prompt · alternative
“if you have particularly complex pricing structures or multi-channel requirements, Flintfox would be the stronger choice” MiniMax M2.5 · paraphrase 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.