Zero of fourteen models named OWASP Dependency-Check first on the direct prompt; three named Mend.io – Mend SCA. Both were named by all fourteen models and OWASP Dependency-Check carries 37 labels and Mend.io – Mend SCA 41, 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 software composition analysis page.
Across every category in the November 2026 Edition, OWASP Dependency-Check and Mend.io – Mend SCA were named in the same answer thirty-seven times, of the 106 answers naming OWASP Dependency-Check and the 117 naming Mend.io – Mend SCA. In those answers Mend.io – Mend SCA took the first choice one time and OWASP Dependency-Check three.
| 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 |
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.
“generally not recommended for modern pipelines due to high false-positive rates and slow build times” Gemini 3.5 Flash · paraphrase prompt · hard negative
“OWASP Dependency-Check as your sole scanner: It's an actively maintained project, not one I'd dismiss. But its approach relies in part on matching components to vulnerability records” GPT-6 Luna · negative prompt · soft negative
“it is commonly used with caution because it is CPE and metadata driven, has historically high false-positive rates, lacks built-in reachability / exploitability prioritization” Muse Glimmer 30B · negative prompt · soft negative
“For budget-conscious teams or open-source projects, OWASP Dependency-Check is recommended” Claude Haiku 4.5 · budget prompt · first choice
“Primary SCA: OWASP Dependency-Check (free, comprehensive scanning)” Kimi K2 · budget prompt · first choice
“I'd suggest OWASP Dependency-Check as your primary tool” Claude Haiku 4.5 · paraphrase 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.
“Mend.io: Powerful but historically complex to configure and priced for enterprise” Kimi K2 · direct prompt · hard negative
“Use with Caution (For High-Volume Repositories) ... historically, it has struggled with accuracy and performance in very large codebases.” Qwen 3.7 Flash · negative prompt · soft negative
“Most mainstream tools (Snyk, Black Duck, Dependabot, Whitesource/Mend, etc.) fall into this category to some degree.” DeepSeek V4 Flash · negative prompt · soft negative
“For most mid-market B2B companies, Mend.io or Snyk would be the primary recommendations” MiniMax M2.5 · direct prompt · first choice
“Mend.io stands out as the leading choice for many mid-market organizations.” Claude Haiku 4.5 · direct prompt · first choice
“Mend.io (best for automated remediation and proactive SCA)” Claude Haiku 4.5 · comparative 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.