PancakeSwap vs Curve Finance
Zero of fourteen models named PancakeSwap first on the direct prompt; zero named Curve Finance. PancakeSwap was named by fourteen of the fourteen models and Curve Finance by ten and PancakeSwap carries 31 labels and Curve Finance 13, so the shares are not directly comparable.
Named in one category this edition.
Curve Finance
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 digital employee experience page.
By framing
PancakeSwapFirst choices, of fourteen modelsCurve FinanceAcross every category in the November 2026 Edition, PancakeSwap and Curve Finance were named in the same answer twenty-four times, of the 78 answers naming PancakeSwap and the 32 naming Curve Finance. In those answers Curve Finance took the first choice one time and PancakeSwap three.
Every model, every framing
| Model | DirectCF | ParaphraseCF | ComparativeCF | Budget-constrainedCF | Scale-constrainedCF | NegativeCF |
|---|---|---|---|---|---|---|
| Claude Haiku 4.5 | | CF | ||||
| GPT-5.4 mini | ||||||
| Gemini 3.5 Flash | CF | |||||
| Perplexity Sonar | | |||||
| Grok 4.20 | CF | | | CF | ||
| Mistral Small | CF | |||||
| DeepSeek V4 Flash | | CF | | | ||
| Llama 4 Maverick | CF | | ||||
| Qwen 3.7 Flash | CF | CF | | |||
| Kimi K2 | CF | | ||||
| GLM 4.7 FlashX | CF | | ||||
| MiniMax M2.5 | CF | | ||||
| GPT-6 Luna | | |||||
| Muse Glimmer 30B | |
PancakeSwapCF Curve Finance first choice named as an alternative argued againstblank: not namedEach cell is one answer, PancakeSwap on the left and Curve Finance on the right.The direct prompt
Neither was named
14 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
PancakeSwap7%#2 of 8PancakeSwap8%#3 of 11PancakeSwap0%#9 of 9What the models said about PancakeSwap
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of eight in this category shown.
“PancakeSwap - 100% of labels are negative, with 5 out of 5 labels being negative” Llama 4 Maverick · negative prompt · hard negative
“More than 58% of rug pulls in 2024 happened on decentralized exchanges (DEXs) like Uniswap and PancakeSwap.” Muse Glimmer 30B · negative prompt · soft negative
“you are vulnerable to sandwich attacks... like older versions of PancakeSwap or SushiSwap” Qwen 3.7 Flash · negative prompt · soft negative
“PancakeSwap (Binance Smart Chain) or Quickswap (Polygon) are often recommended due to their combination of low trading fees AND significantly lower network transaction costs” MiniMax M2.5 · budget prompt · first choice
“PancakeSwap is often recommended for startups and budget-conscious users.” Claude Haiku 4.5 · budget prompt · first choice
“ranks Uniswap, PancakeSwap, and Aero highest over the preceding 30 days” GPT-6 Luna · comparative prompt · first choice
What the models said about Curve Finance
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Four of five in this category shown.
“Focused on stablecoins; lower risk for volatility but check for smart contract bugs.” Grok 4.20 · negative prompt · soft negative
“For most companies with limited budgets, Curve Finance for stablecoins and 1inch for general trading offer the best combination of low fees and reliability.” GLM 4.7 FlashX · budget prompt · first choice
“Specializes in stablecoins, making it ideal for users seeking minimal price impact on large stablecoin trades.” Mistral Small · comparative prompt · alternative
“If you're dealing with stablecoins specifically, Curve Finance offers the deepest stablecoin pools in DeFi” Claude Haiku 4.5 · budget 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.