# Snyk Code vs Checkmarx One: which do AI models recommend for SAST, October 2026

IT AI Recommendation Index, October 2026 Edition, Static application security testing. Four of fourteen models named Snyk Code first on the direct prompt; zero named Checkmarx One. Page: https://it-ai-index.com/developer/static-application-security-testing/snyk-code-vs-checkmarx-one/

| | First-choice share | Rank | Negative rate | Labels | Models naming it |
|---|---|---|---|---|---|
| Snyk Code | 14% | #3 of 10 | 2% | 41 | 14 of 14 |
| Checkmarx One | 2% | #8 of 10 | 45% | 44 | 14 of 14 |

## The direct prompt, model by model

- Grok 4.1 Fast: snyk code first (first choices: Snyk Code) (alternatives: Semgrep, SonarQube)
- DeepSeek V4 Flash: snyk code first (first choices: Snyk Code) (alternatives: CodeAnt.ai, Semgrep, SonarQube)
- Llama 4 Maverick: snyk code first (first choices: Snyk Code)
- Kimi K2: snyk code first (first choices: Semgrep, Snyk Code) (alternatives: SonarQube)
- GPT-5.4 mini: neither first, one named (first choices: Semgrep) (alternatives: Checkmarx One, Snyk Code, Veracode Static Analysis)
- Gemini 3.5 Flash: neither first, one named (first choices: Aikido Security) (alternatives: GitHub Advanced Security, GitLab SAST, Semgrep, Snyk Code)
- Perplexity Sonar: neither first, one named (first choices: Semgrep) (alternatives: Checkmarx One, Snyk Code)
- Qwen 3.7 Flash: neither first, one named (first choices: SonarQube) (alternatives: Semgrep, Snyk Code)
- GLM 4.7 FlashX: neither first, one named (first choices: SonarQube) (alternatives: Checkmarx One, Codacy, DeepSource, GitHub Advanced Security, OpenText Fortify, Semgrep, Snyk Code, Veracode Static Analysis)
- Claude Haiku 4.5: neither named
- Mistral Small: neither named (first choices: Snyk) (alternatives: Aikido Security, Semgrep)
- MiniMax M2.5: neither named (first choices: Snyk) (alternatives: Semgrep, Veracode Static Analysis)
- GPT-6 Luna: neither named (first choices: Semgrep) (alternatives: GitHub Advanced Security, Snyk)
- Muse Glimmer 30B: neither named (first choices: SonarQube) (alternatives: Semgrep)

## What the models said about Snyk Code

- "Choose Snyk Code only if you already use Snyk Open Source/Container SCA...The limitation is fewer supported languages than SonarQube/Semgrep and no custom rule authoring." (Muse Glimmer 30B, direct prompt, soft negative)
- "I'd recommend Snyk Code as a top choice based on recent analyst reports (Forrester Leader), reviews, and pricing." (Grok 4.1 Fast, direct prompt, first choice)
- "Choose Snyk Code if your primary goal is developer adoption and you want a frictionless, speedy security tool" (Gemini 3.5 Flash, comparative prompt, first choice)
- "using a developer-first tool (like Snyk or GitHub Advanced Security) for fast, early feedback during coding" (Qwen 3.7 Flash, comparative prompt, first choice)

## What the models said about Checkmarx One

- "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)
- "be especially cautious with legacy configurations of Checkmarx, Fortify/OpenText, and SonarQube for security use cases unless they are heavily tuned" (Muse Glimmer 30B, negative prompt, soft negative)
- "Legacy enterprise | Checkmarx, Veracode, Fortify | Deep compliance... unless you have specific compliance requirements that mandate legacy tools" (Kimi K2, scale prompt, soft negative)
- "Checkmarx One (Gartner/Forrester Leader): Enterprise-grade with deep dataflow/taint analysis... Checkmarx for banks" (Grok 4.1 Fast, comparative prompt, first choice)
- "an enterprise-grade scanner (like Checkmarx or Fortify) for nightly full-scan reports and compliance auditing." (Qwen 3.7 Flash, comparative prompt, first choice)
- "Gartner Magic Quadrant Leader for 7 consecutive years... Best For: Large enterprises, portfolio-level governance" (Kimi K2, comparative prompt, first choice)

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. Comparisons are drawn for the top eight products in each category. Published under CC BY 4.0; the output is the models' output, and nothing here is a recommendation by the index.