Snyk Code vs GitHub Advanced Security
Four of fourteen models named Snyk Code first on the direct prompt; zero named GitHub Advanced Security. Snyk Code was named by fourteen of the fourteen models and GitHub Advanced Security by eleven and Snyk Code carries 41 labels and GitHub Advanced Security 16, so the shares are not directly comparable.
Named in one category this edition.
Named in five categories 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.
By framing
Snyk CodeFirst choices, of fourteen modelsGitHub Advanced Security
Across every category in the October 2026 Edition, Snyk Code and GitHub Advanced Security were named in the same answer twenty-six times, of the 118 answers naming Snyk Code and the 125 naming GitHub Advanced Security. In those answers GitHub Advanced Security took the first choice zero times and Snyk Code six.
Every model, every framing
| 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 | | | |
Snyk Code GitHub Advanced Security first choice named as an alternative argued againstblank: not namedEach cell is one answer, Snyk Code on the left and GitHub Advanced Security on the right.The direct prompt
Snyk Code first, GitHub Advanced Security not the choice
4 of 14 modelsGitHub Advanced Security was named in the answer but not as the choice, or not at all.Neither was the first choice, one was named
6 of 14 modelsThe answer put something else first and named one of the two as an alternative.Neither was named
4 of 14 modelsThe answer made no first choice from these two in this category.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.
By buyer segment
Snyk Code11%#3 of 13GitHub Advanced Security2%#6 of 13Snyk Code14%#3 of 10GitHub Advanced Security2%#6 of 10Snyk Code4%#4 of 10GitHub Advanced Security2%#8 of 10What the models said about Snyk Code
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Four of five in this category shown.
“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 GitHub Advanced Security
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Three of three in this category shown.
“GHAS is sold as an add-on license that can be quite expensive for a mid-sized B2B budget.” Gemini 3.5 Flash · paraphrase prompt · soft negative
“Top Recommendation: GitHub Advanced Security (GHAS)” Kimi K2 · paraphrase prompt · first choice
“GitHub Advanced Security / CodeQL if your company is deeply GitHub-native and wants SAST in the same platform.” Muse Glimmer 30B · comparative 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.