VWO vs Mutiny
Seven of fourteen models named VWO first on the direct prompt; zero named Mutiny. VWO was named by fourteen of the fourteen models and Mutiny by ten and VWO carries 65 labels and Mutiny 16, so the shares are not directly comparable.
Named in two categories this edition.
Named in seven categories 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 experimentation and personalization page.
By framing
VWOFirst choices, of fourteen modelsMutiny
Across every category in the November 2026 Edition, VWO and Mutiny were named in the same answer thirty-six times, of the 167 answers naming VWO and the 78 naming Mutiny. In those answers Mutiny took the first choice two times and VWO fifteen.
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 4.20 | | | | | | |
| 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 | | | | |
VWO Mutiny first choice named as an alternative argued againstblank: not namedEach cell is one answer, VWO on the left and Mutiny on the right.The direct prompt
VWO first, Mutiny an alternative
7 of 14 modelsMutiny 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
1 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
What the models said about VWO
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of eight in this category shown.
“Avoid VWO if page speed and user trust are critical, or if you have limited technical support.” GLM 4.7 FlashX · negative prompt · hard negative
“the reliability and support issues make it risky for serious experimentation” DeepSeek V4 Flash · negative prompt · hard negative
“its current pricing page directs buyers to request a demo rather than showing a price, so it may be harder to budget for upfront” GPT-6 Luna · budget prompt · soft negative
“platforms like VWO or Optimizely are commonly considered in this middle market, depending on whether you prioritize faster time-to-value (VWO)” Claude Haiku 4.5 · scale prompt · first choice
“The Best All-Rounder: VWO (Visual Website Optimizer) ... widely considered the best balance of power and usability for mid-sized companies” Qwen 3.7 Flash · paraphrase prompt · first choice
“Tight budget, marketer-led, low traffic, needs CRM bucketing: Convert Experiences or VWO Experience Optimization.” Muse Glimmer 30B · paraphrase prompt · first choice
What the models said about Mutiny
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Four of five in this category shown.
“don't shortlist Mutiny for website experimentation: it says its former website-personalization product is no longer what it offers” GPT-6 Luna · direct prompt · hard negative
“Mutiny — avoid for new website-personalization projects: its personalization product was discontinued” Perplexity Sonar · negative prompt · hard negative
“Mutiny (due to its discontinued website personalization product and relaunch as an AI tool)” Llama 4 Maverick · negative prompt · hard negative
“Best Overall for B2B Inbound & ABM: Mutiny” Gemini 3.5 Flash · 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.