Application security posture management · October 2026 Edition
ArmorCode vs Wiz
One of fourteen models named ArmorCode first on the direct prompt; one named Wiz. ArmorCode was named by fourteen of the fourteen models and Wiz by nine and ArmorCode carries 33 labels and Wiz 18, so the shares are not directly comparable.
Named in one category this edition.
Named in sixteen categories this edition.
First-choice share4%2%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate24%11%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#6#7A position in a field of 12; printed, not drawn.
Labels3318A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, ArmorCode reading right to left. Rank and label count are printed, not drawn.Aikido Security was named alongside these two in eight of the fourteen direct answers. Aikido Security vs ArmorCode · Aikido Security vs Wiz · Snyk vs ArmorCode
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 application security posture management page.
By framing
How many of the fourteen models made each the first choice, per way of asking, and how many argued against it.
ArmorCodeFirst choices, of fourteen modelsWiz
Direct111 against ArmorCode · 1 against Wiz
Paraphrase101 against ArmorCode
Comparative41
Budget-constrained002 against ArmorCode
Scale-constrained00
Negative004 against ArmorCode · 1 against Wiz
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.
Every model, every framing
The eighty-four answers behind the chart above, one cell each: where ArmorCode and Wiz stood in it.
| 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 | | |
ArmorCode Wiz first choice named as an alternative argued againstblank: not namedEach cell is one answer, ArmorCode on the left and Wiz on the right.The direct prompt
The plain question, one answer per model, grouped by where ArmorCode and Wiz stood in it.
ArmorCode first, Wiz not the choice
1 of 14 modelsWiz was named in the answer but not as the choice, or not at all.GPT-6 LunaArmorCode alternatives: CrowdStrike Falcon ASPM, Snyk AppRisk, Wiz ASPM
Wiz first, ArmorCode an alternative
1 of 14 modelsArmorCode was named in the answer but not as the choice, or not at all.Perplexity SonarWiz alternatives: ArmorCode, Checkmarx One, Snyk
Neither was the first choice, one was named
4 of 14 modelsThe answer put something else first and named one of the two as an alternative.GPT-5.4 miniCycode ASPM alternatives: ArmorCode, Legit Security, Snyk AppRisk
Gemini 3.5 FlashAikido Security alternatives: ArmorCode, Cycode ASPM, DefectDojo, Jit.io
Llama 4 MaverickAikido Security alternatives: ArmorCode, Snyk AppRisk
Qwen 3.7 FlashAikido Security alternatives: ArmorCode, Jit, Snyk AppRisk
Neither was named
8 of 14 modelsThe answer made no first choice from these two in this category.Claude Haiku 4.5Aikido Security alternatives: Cycode ASPM, Snyk
Grok 4.1 FastAikido Security, Strobes ASPM alternatives: Jit, StackHawk
Mistral SmallPhoenix Security alternatives: Aikido Security, Snyk AppRisk
DeepSeek V4 FlashAikido Security alternatives: Cycode ASPM, Jit.io, Legit Security, Snyk, Snyk AppRisk
Kimi K2Aikido Security, Snyk alternatives: Apiiro, Cycode ASPM, Jit, Semgrep
GLM 4.7 FlashXCycode ASPM, Snyk alternatives: Invicti ASPM, Strobes, Xygeni
MiniMax M2.5no first choice
Muse Glimmer 30Bno first choice
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
Level: the same share of first choices.
ArmorCode0%#12 of 12Wiz0%#– of 12Mid-marketThe figures above
Enterprise
What the models said about ArmorCode
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of eight in this category shown.
“Enterprise-grade ASPM platforms (such as ArmorCode, Cycode, and Apiiro) are incredibly powerful, but their pricing models are built for large enterprises and often start at tens of thousands of dollars” Gemini 3.5 Flash · budget prompt · soft negative
“Some aggregator-focused platforms like ArmorCode, Tromzo, and similar tools that primarily focus on ingesting and reporting rather than adding intelligence.” DeepSeek V4 Flash · negative prompt · soft negative
“ArmorCode is positioned as a vendor-neutral AppSec command centre that integrates with 100-plus security tools, deduplicates findings and is an aggregator only.” Muse Glimmer 30B · negative prompt · soft negative
“Choose Wiz or ArmorCode if you are a cloud-native organization looking for a "single pane of glass"” Qwen 3.7 Flash · comparative prompt · first choice
“Many existing scanners; don’t want to replace them: start with ArmorCode and Veracode Risk Manager.” GPT-6 Luna · comparative prompt · first choice
“Choose ArmorCode if you have 30+ security tools ... it's the ultimate unification and automation engine.” DeepSeek V4 Flash · comparative prompt · first choice
What the models said about Wiz
No label in this category carried a quote.
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.