Three of fourteen models named Ardoq first on the direct prompt; one named Sparx Systems Enterprise Architect. Ardoq was named by thirteen of the fourteen models and Sparx Systems Enterprise Architect by thirteen and Ardoq carries 47 labels and Sparx Systems Enterprise Architect 29, 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 enterprise architecture tools page.
Across every category in the October 2026 Edition, Ardoq and Sparx Systems Enterprise Architect were named in the same answer fifty-seven times, of the 145 answers naming Ardoq and the 77 naming Sparx Systems Enterprise Architect. In those answers Sparx Systems Enterprise Architect took the first choice fourteen times and Ardoq seven.
| 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 |
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.
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 high-end tools like LeanIX, Bizzdesign, or Ardoq” Grok 4.1 Fast · budget prompt · hard negative
“High Risk: Pricing/Packaging Changes ... Ardoq if you have a very large application portfolio (>1,000 apps) and budget sensitivity.” DeepSeek V4 Flash · negative prompt · soft negative
“Ardoq is an example often flagged for this: ... exclusively a cloud-hosted SaaS platform — there is no on-premises deployment option” Muse Glimmer 30B · negative prompt · soft negative
“Dynamic visualization & linking complex relationships. Very user-friendly for non-architects. | Great for "living repository" approach.” Qwen 3.7 Flash · scale prompt · first choice
“Ardoq is the most cited "modern" option for teams that want browser-based real-time collaboration and automated dependency mapping.” Muse Glimmer 30B · direct prompt · first choice
“LeanIX and Ardoq are usually the strongest fits because they prioritize portfolio views, impact analysis, and change planning” Perplexity Sonar · comparative prompt · first choice
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of eight in this category shown.
“Highest Caution/Steepest Learning Curve ... Frequently cited as one of the most problematic” Grok 4.1 Fast · negative prompt · hard negative
“Avoid: - Sparx Enterprise Architect if you need business-friendly EA” DeepSeek V4 Flash · negative prompt · hard negative
“The learning curve is steep with nested menus and features hidden in dialogs... Users report outdated design, poor UI, difficulty understanding and finding required tools, and performance issues” Claude Haiku 4.5 · negative prompt · soft negative
“It maintains a dominant 18% market share in the defense and aerospace sectors and remains the most cost-effective solution for large-scale deployments” Claude Haiku 4.5 · comparative prompt · first choice
“Choose Sparx EA when you need deep, standards-based architecture modeling, full control of the repository, and the lowest cost at scale” Muse Glimmer 30B · comparative prompt · first choice
“If you want a powerful, cost-effective, on-premise tool with deep modeling, choose Sparx Enterprise Architect.” Mistral Small · direct 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.