Synack vs Bugcrowd
Zero of fourteen models named Synack first on the direct prompt; zero named Bugcrowd. Synack was named by fourteen of the fourteen models and Bugcrowd by ten and Synack carries 29 labels and Bugcrowd 12, so the shares are not directly comparable.
Named in two 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 penetration testing as a service page.
By framing
SynackFirst choices, of fourteen modelsBugcrowd
Across every category in the October 2026 Edition, Synack and Bugcrowd were named in the same answer seventeen times, of the 105 answers naming Synack and the 36 naming Bugcrowd. In those answers Bugcrowd took the first choice zero times and Synack three.
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 |
Synack Bugcrowd first choice named as an alternative argued againstblank: not namedEach cell is one answer, Synack on the left and Bugcrowd on the right.The direct prompt
Neither was the first choice, one was named
2 of 14 modelsThe answer put something else first and named one of the two as an alternative.Neither was named
12 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
Synack4%#3 of 10Bugcrowd2%#7 of 10What the models said about Synack
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of six in this category shown.
“Choose Synack if you want a crowdsourced model and are willing to validate scope and pricing more carefully” Perplexity Sonar · paraphrase prompt · soft negative
“often more suited to larger enterprises or those with more complex needs” Mistral Small · paraphrase prompt · soft negative
“More enterprise-focused, higher cost/complexity.” Grok 4.1 Fast · paraphrase prompt · soft negative
“The best penetration testing service for a company with a limited budget is Synack, which offers penetration testing as a service starting at $119/month.” Llama 4 Maverick · budget prompt · first choice
“Offers continuous AI-driven penetration testing starting at $119/month, making it one of the most affordable options” Mistral Small · budget prompt · first choice
“Synack tops the list because it combines an elite human red team with agentic AI inside a single platform” Claude Haiku 4.5 · comparative prompt · first choice
What the models said about Bugcrowd
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Five of six in this category shown.
“often more suited to larger enterprises or those with more complex needs” Mistral Small · paraphrase prompt · soft negative
“Broader crowdsourcing, but less PTaaS-specific structure.” Grok 4.1 Fast · paraphrase prompt · soft negative
“Platforms like HackerOne, Bugcrowd, or Open Bug Bounty allow you to set a budget and pay only for valid vulnerabilities found” MiniMax M2.5 · budget prompt · first choice
“Companies wanting crowdsourced testing | Launch in <72 hours, subscription model” MiniMax M2.5 · paraphrase prompt · alternative
“their Enterprise PTaaS offering is well-suited for mid-sized agile enterprises” Qwen 3.7 Flash · paraphrase 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.