SecureFlag vs SafeStack Academy
Nine of fourteen models named SecureFlag first on the direct prompt; zero named SafeStack Academy. SecureFlag was named by fourteen of the fourteen models and SafeStack Academy by eleven and SecureFlag carries 48 labels and SafeStack Academy 20, so the shares are not directly comparable.
Named in one category 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 secure code training page.
By framing
SecureFlagFirst choices, of fourteen modelsSafeStack Academy
Across every category in the October 2026 Edition, SecureFlag and SafeStack Academy were named in the same answer thirty-nine times, of the 156 answers naming SecureFlag and the 51 naming SafeStack Academy. In those answers SafeStack Academy took the first choice seven times and SecureFlag fourteen.
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 | |
SecureFlag SafeStack Academy first choice named as an alternative argued againstblank: not namedEach cell is one answer, SecureFlag on the left and SafeStack Academy on the right.The direct prompt
SecureFlag first, SafeStack Academy an alternative
9 of 14 modelsSafeStack Academy was named in the answer but not as the choice, or not at all.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.Neither was named
1 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
SecureFlag26%#1 of 6SafeStack Academy13%#3 of 6SecureFlag26%#1 of 7SafeStack Academy12%#3 of 7SecureFlag22%#2 of 8SafeStack Academy4%#4 of 8What the models said about SecureFlag
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Four of five in this category shown.
“Low review volume, limited long-term track record, minor integration issues” DeepSeek V4 Flash · negative prompt · soft negative
“SecureFlag offers the strongest combination of practical depth, modern threat coverage (including AI risks), and workflow integration” Qwen 3.7 Flash · direct prompt · first choice
“SecureFlag and Secure Code Warrior are the leaders when it comes to AI‑code readiness and AI‑software governance” GLM 4.7 FlashX · comparative prompt · first choice
“Choose SecureFlag if you want hands-on labs, workflow integration, threat modeling, and compliance evidence.” GPT-5.4 mini · comparative prompt · first choice
What the models said about SafeStack Academy
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Three of four in this category shown.
“I'd typically recommend starting with Top 10 Dev Training or SafeStack Academy for cost-effective compliance coverage” Kimi K2 · paraphrase prompt · first choice
“Start with SafeStack or Secure Code Warrior as your primary platform—it's affordable, scalable, and delivers quick wins.” Qwen 3.7 Flash · paraphrase prompt · first choice
“For the absolute best value: Start with RansomLeak (free if under 25 employees) or SafeStack ($30/user/year)” Kimi K2 · budget prompt · first choice
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.