Three of fourteen models named LeanIX first on the direct prompt; one named Sparx Systems Enterprise Architect. LeanIX was named by ten of the fourteen models and Sparx Systems Enterprise Architect by thirteen and LeanIX carries 20 labels and Sparx Systems Enterprise Architect 29, so the shares are not directly comparable.
Named in two categories 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, LeanIX and Sparx Systems Enterprise Architect were named in the same answer twenty-one times, of the 73 answers naming LeanIX and the 77 naming Sparx Systems Enterprise Architect. In those answers Sparx Systems Enterprise Architect took the first choice six times and LeanIX zero.
| 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 (enterprise pricing, often $10K+ annually).” Grok 4.1 Fast · budget prompt · hard negative
“Modern SaaS platforms like LeanIX, Ardoq, and BiZZdesign frequently cost upwards of $10,000 to $50,000+ per year, placing them far out of reach” Gemini 3.5 Flash · budget prompt · soft negative
“SaaS Platforms with "Asset-Based" Pricing (e.g., LeanIX, Ardoq) ... Unpredictable, ballooning licensing costs.” Gemini 3.5 Flash · negative prompt · soft negative
“For most mid-market B2B companies, LeanIX or Ardoq offer the best balance of cloud-native architecture, modern UX, and scalability.” Claude Haiku 4.5 · direct prompt · first choice
“SaaS options like LeanIX, Bizzdesign, Ardoq, or Sparx Enterprise Architect, which support mid-sized orgs managing 50-500+ apps” Grok 4.1 Fast · scale prompt · first choice
“Widely considered the gold standard for modern Application Portfolio Management. It is incredibly user-friendly” Gemini 3.5 Flash · scale 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.