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Static application security testing · October 2026 Edition

Semgrep vs Snyk

Four of fourteen models named Semgrep first on the direct prompt; two named Snyk. Semgrep was named by fourteen of the fourteen models and Snyk by seven and Semgrep carries 63 labels and Snyk 11, so the shares are not directly comparable.

Semgrep

endorsed leader

Named in three categories this edition.

Snyk

accepted challenger

Named in eleven categories this edition.

First-choice share36%8%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate5%9%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#1#4A position in a field of 10; printed, not drawn.
Labels6311A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, Semgrep reading right to left. Rank and label count are printed, not drawn.Snyk Code was named alongside these two in nine of the fourteen direct answers. Semgrep vs SonarQube · Semgrep vs Snyk Code · Semgrep vs CodeQL

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

How many of the fourteen models made each the first choice, per way of asking, and how many argued against it.
SemgrepFirst choices, of fourteen modelsSnyk
Direct42
Paraphrase42
Comparative40
Budget-constrained90
Scale-constrained10
Negative403 against Semgrep · 1 against Snyk
Bars are first choices, 0 to 14 each sideModels that argued againstA model can name both, so the two sides of a row do not sum to fourteen.

Across every category in the October 2026 Edition, Semgrep and Snyk were named in the same answer forty-two times, of the 208 answers naming Semgrep and the 177 naming Snyk. In those answers Snyk took the first choice ten times and Semgrep eight.

Every model, every framing

The eighty-four answers behind the chart above, one cell each: where Semgrep and Snyk stood in it.
ModelDirectParaphraseComparativeBudget-constrainedScale-constrainedNegative
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
Semgrep Snyk first choice named as an alternative argued againstblank: not namedEach cell is one answer, Semgrep on the left and Snyk on the right.

The direct prompt

The plain question, one answer per model, grouped by where Semgrep and Snyk stood in it.

Semgrep first, Snyk an alternative

4 of 14 modelsSnyk was named in the answer but not as the choice, or not at all.
GPT-5.4 miniSemgrep alternatives: Checkmarx One, Snyk Code, Veracode Static Analysis
Perplexity SonarSemgrep alternatives: Checkmarx One, Snyk Code
Kimi K2Semgrep, Snyk Code alternatives: SonarQube
GPT-6 LunaSemgrep alternatives: GitHub Advanced Security, Snyk

Snyk first, Semgrep an alternative

2 of 14 modelsSemgrep was named in the answer but not as the choice, or not at all.
Mistral SmallSnyk alternatives: Aikido Security, Semgrep
MiniMax M2.5Snyk alternatives: Semgrep, Veracode Static Analysis

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.
Gemini 3.5 FlashAikido Security alternatives: GitHub Advanced Security, GitLab SAST, Semgrep, Snyk Code
Grok 4.1 FastSnyk Code alternatives: Semgrep, SonarQube
DeepSeek V4 FlashSnyk Code alternatives: CodeAnt.ai, Semgrep, SonarQube
Qwen 3.7 FlashSonarQube alternatives: Semgrep, Snyk Code
GLM 4.7 FlashXSonarQube alternatives: Checkmarx One, Codacy, DeepSource, GitHub Advanced Security, OpenText Fortify, Semgrep, Snyk Code, Veracode Static Analysis
Muse Glimmer 30BSonarQube alternatives: Semgrep

Neither was named

2 of 14 modelsThe answer made no first choice from these two in this category.
Claude Haiku 4.5no first choice
Llama 4 MaverickSnyk Code

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

The same question asked on behalf of a different buyer. Each standing is computed within its segment and they are never added together. The figures above are the mid-market standing, which is the one the category orders by.
Small business
Semgrep leads by forty-four points.
Semgrep53%#1 of 13
Snyk9%#4 of 13
The full small business standing →
Mid-marketThe figures above
Semgrep leads by twenty-eight points.
Semgrep36%#1 of 10
Snyk8%#4 of 10
The full mid-market standing →
Enterprise
Semgrep leads by four points.
Semgrep4%#5 of 10
Snyk0%#10 of 10
The full enterprise standing →

What the models said about Semgrep

Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of seven in this category shown.

“Semgrep OSS and Bandit are fast and low false-positive for obvious patterns, but miss vulnerabilities that span multiple functions... insufficient as sole nightly security scanners” Muse Glimmer 30B · negative prompt · soft negative
“Semgrep Community Edition as your only deep security scanner: It can be useful for fast checks and custom rules, but its analysis is limited to a file/function context” GPT-6 Luna · negative prompt · soft negative
“Checkmarx, Veracode, and Semgrep have all struggled with this because their rule-based engines flag anything that could be a vulnerability” Claude Haiku 4.5 · negative prompt · soft negative
“Semgrep as the primary scanner across all languages... For most budget-constrained companies, Semgrep OSS + SonarQube Community Edition... is the most commonly recommended starting point” Muse Glimmer 30B · budget prompt · first choice
“Tools like Semgrep are generally preferred for modern CI/CD because they are lightweight, customizable, and run significantly faster.” GLM 4.7 FlashX · negative prompt · first choice
“look for developer-friendly alternatives like Semgrep, where rules are written in YAML and read like standard code” Gemini 3.5 Flash · negative prompt · first choice

What the models said about Snyk

Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Two of two in this category shown.

“"We are forced to use Snyk–it's basically infuriating support and false positives... it's also insanely expensive"” Claude Haiku 4.5 · negative prompt · soft negative
“Snyk appears to be the most frequently recommended option for mid-market B2B companies running modern stacks” MiniMax M2.5 · direct prompt · first choice
Also compared

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.