Zero of fourteen models named OWASP Dependency-Check first on the direct prompt; zero named GitHub Dependabot. OWASP Dependency-Check was named by fourteen of the fourteen models and GitHub Dependabot by twelve and OWASP Dependency-Check carries 37 labels and GitHub Dependabot 25, 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 GitHub Dependabot were named in the same answer thirty-three times, of the 106 answers naming OWASP Dependency-Check and the 61 naming GitHub Dependabot. In those answers GitHub Dependabot took the first choice five times and OWASP Dependency-Check five.
| 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.
“GitHub Dependabot as your entire SCA program: It can be useful for repositories on GitHub, but check the documented ecosystem and file-format coverage” GPT-6 Luna · negative prompt · soft negative
“May be insufficient as a standalone program for complex SBOM, license, or multi-repository governance” Perplexity Sonar · direct prompt · soft negative
“Dependabot is convenient if you're all-in on GitHub, but it's more of an updater than a deep scanner.” Grok 4.20 · paraphrase prompt · soft negative
“Using GitHub and want zero setup effort | GitHub Dependabot | Free, native, automatically creates fix PRs.” Gemini 3.5 Flash · budget prompt · first choice
“Best value for most budget-conscious companies: GitHub Dependabot—if your code is already on GitHub.” GPT-6 Luna · budget prompt · first choice
“GitHub Dependabot or Snyk Open Source are the best starting points due to their free tiers” Mistral Small · budget 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.