KnowBe4 vs SoSafe
Nine of fourteen models named KnowBe4 first on the direct prompt; zero named SoSafe. Both were named by all fourteen models and KnowBe4 carries 65 labels and SoSafe 29, so the shares are not directly comparable.
Named in three categories 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 security awareness training page.
By framing
KnowBe4First choices, of fourteen modelsSoSafe
Across every category in the October 2026 Edition, KnowBe4 and SoSafe were named in the same answer sixty-six times, of the 215 answers naming KnowBe4 and the 72 naming SoSafe. In those answers SoSafe took the first choice two times and KnowBe4 thirty-one.
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 | | | | |
KnowBe4 SoSafe first choice named as an alternative argued againstblank: not namedEach cell is one answer, KnowBe4 on the left and SoSafe on the right.The direct prompt
KnowBe4 first, SoSafe an alternative
9 of 14 modelsSoSafe was named in the answer but not as the choice, or not at all.Neither was the first choice, one was named
3 of 14 modelsThe answer put something else first and named one of the two as an alternative.Neither was named
2 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
KnowBe474%#1 of 10SoSafe2%#4 of 10What the models said about KnowBe4
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of seven in this category shown.
“1.9-star Trustpilot rating (85 % 1-star reviews) – users call the content “garbage”” GLM 4.7 FlashX · negative prompt · hard negative
“What to Avoid - KnowBe4 – Industry leader but priced for enterprise” Kimi K2 · budget prompt · hard negative
“reviewers flag content fatigue after years on the platform and friction in phishing-simulation reporting and assessment setup” Muse Glimmer 30B · negative prompt · soft negative
“KnowBe4: The "Comprehensive Library" Leader ... Choose KnowBe4 if you need to pass audits easily and want a "turn-key" solution with the most content available.” Qwen 3.7 Flash · comparative prompt · first choice
“KnowBe4 is widely used across SMB, mid-market, and enterprise organizations and is a strong option for organizations of all sizes.” Claude Haiku 4.5 · direct prompt · first choice
“KnowBe4 and Hoxhunt stand out as the most comprehensive, AI‑driven platforms with large user bases and strong ratings.” GLM 4.7 FlashX · comparative prompt · first choice
What the models said about SoSafe
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Three of four in this category shown.
“Hoxhunt or SoSafe: Highly automated, adaptive platforms that tailor training based on individual user risk and behavior.” Gemini 3.5 Flash · scale prompt · first choice
“SoSafe is generally considered the best option due to its robust "free forever" tier” Qwen 3.7 Flash · budget prompt · first choice
“Hoxhunt and SoSafe are excellent for organizations prioritizing engagement and behavior change” Mistral Small · direct 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.