Three of fourteen models named SonarQube first on the direct prompt; zero named Veracode Static Analysis. Both were named by all fourteen models and SonarQube carries 62 labels and Veracode Static Analysis 39, so the shares are not directly comparable.
Named in four 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 static application security testing page.
Across every category in the October 2026 Edition, SonarQube and Veracode Static Analysis were named in the same answer 100 times, of the 189 answers naming SonarQube and the 138 naming Veracode Static Analysis. In those answers Veracode Static Analysis took the first choice three times and SonarQube twelve.
| Model | DirectSO | ParaphraseSO | ComparativeSO | Budget-constrainedSO | Scale-constrainedSO | NegativeSO |
|---|---|---|---|---|---|---|
| Claude Haiku 4.5 | SO | SO | SO | |||
| GPT-5.4 mini | SO | SO | SO | |||
| Gemini 3.5 Flash | SO | SO | SO | |||
| Perplexity Sonar | SO | SO | ||||
| Grok 4.1 Fast | SO | SO | SO | SO | SO | SO |
| Mistral Small | SO | SO | SO | |||
| DeepSeek V4 Flash | SO | SO | SO | SO | SO | |
| Llama 4 Maverick | SO | |||||
| Qwen 3.7 Flash | SO | SO | SO | SO | SO | |
| Kimi K2 | SO | SO | SO | SO | SO | |
| GLM 4.7 FlashX | SO | SO | SO | |||
| MiniMax M2.5 | SO | SO | SO | SO | ||
| GPT-6 Luna | SO | SO | SO | |||
| Muse Glimmer 30B | SO | SO | SO | SO | SO |
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.
“Noisiest out-of-box (40-60%+ FPs on Java/TS; OWASP F1-score ~27% in some evals)... avoid for security-only if you can't invest in config” Grok 4.1 Fast · negative prompt · hard negative
“Tools originally designed for *general code quality* (like SpotBugs, SonarQube's default rules) are often very weak at security-specific detection” DeepSeek V4 Flash · negative prompt · soft negative
“A code-quality scanner treated as comprehensive security coverage... verify the actual security rules for your languages, frameworks, and edition.” GPT-6 Luna · negative prompt · soft negative
“The best SAST tool for a company with a limited budget is Semgrep's free tier, SonarQube Community, Snyk Code's Team plan, or DeepSource.” Llama 4 Maverick · budget prompt · first choice
“The Best All-Around Choice: SonarQube (by SonarSource) This is the most balanced recommendation for most mid-sized companies.” Qwen 3.7 Flash · paraphrase prompt · first choice
“For many mid-sized B2B companies, SonarQube or Snyk offer good balance between cost, ease of use, and effectiveness.” 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.
“What I'd Avoid for Mid-Market: Checkmarx and Veracode are powerful but typically start at $60K–$100K+/year” Kimi K2 · paraphrase prompt · hard negative
“Full scans can delay fast-moving dev cycles, there's no on-premise option with code upload raising security concerns, and pricing can be steep” Claude Haiku 4.5 · negative prompt · soft negative
“not necessarily the one with the most heavy-duty enterprise compliance rules (like legacy tools Veracode or Fortify)” Gemini 3.5 Flash · direct prompt · soft negative
“the recommended static code security scanner for a mid-sized B2B company could be either Checkmarx or Veracode” Llama 4 Maverick · paraphrase prompt · first choice
“Excels in broad language/framework support (including legacy/binary), whole-app analysis, and enterprise integrations” Grok 4.1 Fast · comparative prompt · alternative
“Highly regulated environments, on-premises requirements, or teams needing very deep taint analysis.” GLM 4.7 FlashX · direct 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.