Level Access Accessibility Platform vs Deque axe Platform
Zero of fourteen models named Level Access Accessibility Platform first on the direct prompt; zero named Deque axe Platform. Level Access Accessibility Platform was named by fourteen of the fourteen models and Deque axe Platform by nine and Level Access Accessibility Platform carries 30 labels and Deque axe Platform 12, so the shares are not directly comparable.
Level Access Accessibility Platform
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 website governance and accessibility page.
By framing
Across every category in the November 2026 Edition, Level Access Accessibility Platform and Deque axe Platform were named in the same answer thirty-two times, of the 99 answers naming Level Access Accessibility Platform and the 39 naming Deque axe Platform. In those answers Deque axe Platform took the first choice one time and Level Access Accessibility Platform seven.
Every model, every framing
| Model | DirectLA | ParaphraseLA | ComparativeLA | Budget-constrainedLA | Scale-constrainedLA | NegativeLA |
|---|---|---|---|---|---|---|
| Claude Haiku 4.5 | LA | |||||
| GPT-5.4 mini | LA | LA | ||||
| Gemini 3.5 Flash | LA | LA | LA | LA | ||
| Perplexity Sonar | LA | LA | LA | |||
| Grok 4.20 | LA | LA | LA | |||
| Mistral Small | ||||||
| DeepSeek V4 Flash | LA | | LA | |||
| Llama 4 Maverick | ||||||
| Qwen 3.7 Flash | LA | | LA | |||
| Kimi K2 | LA | |||||
| GLM 4.7 FlashX | LA | |||||
| MiniMax M2.5 | LA | LA | ||||
| GPT-6 Luna | LA | |||||
| Muse Glimmer 30B | LA |
Deque axe PlatformLA first choiceLA named as an alternativeLA argued againstblank: not namedEach cell is one answer, Level Access Accessibility Platform on the left and Deque axe Platform on the right.The direct prompt
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
8 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
Deque axe Platform0%#– of 15Deque axe Platform2%#8 of 15Deque axe Platform0%#6 of 10What the models said about Level Access Accessibility Platform
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Three of four in this category shown.
“The leaders to start with in your evaluation are Level Access, Deque, Siteimprove, and Silktide” DeepSeek V4 Flash · scale prompt · first choice
“Many 500-person companies succeed with Silktide, Siteimprove, or Level Access as starting points.” Grok 4.20 · scale prompt · first choice
“Full‑suite with automated scanning, manual testing, training, and remediation guidance. | Focus on legal defensibility; more expensive but better suited for highly regulated environments.” GLM 4.7 FlashX · comparative prompt · alternative
What the models said about Deque axe Platform
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Four of five in this category shown.
“or Deque (starting around $5K/year)” DeepSeek V4 Flash · budget prompt · soft negative
“The leaders to start with in your evaluation are Level Access, Deque, Siteimprove, and Silktide” DeepSeek V4 Flash · scale prompt · first choice
“Need stronger developer testing, manual audits, or help running an accessibility program? Look at Deque axe or Level Access.” GPT-6 Luna · comparative prompt · alternative
“Industry-standard automated tools—such as Deque Axe, Siteimprove, Pope Tech, Level Access, or WAVE” Gemini 3.5 Flash · negative 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.