NetSPI vs Bishop Fox
One of fourteen models named NetSPI first on the direct prompt; one named Bishop Fox. NetSPI was named by twelve of the fourteen models and Bishop Fox by eleven and NetSPI carries 22 labels and Bishop Fox 13, so the shares are not directly comparable.
Named in two categories this edition.
Named in two categories 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
NetSPIFirst choices, of fourteen modelsBishop Fox
Across every category in the November 2026 Edition, NetSPI and Bishop Fox were named in the same answer thirty-three times, of the 69 answers naming NetSPI and the 50 naming Bishop Fox. In those answers Bishop Fox took the first choice two times and NetSPI eight.
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 4.20 | | | ||||
| 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 | | |
NetSPI Bishop Fox first choice named as an alternative argued againstblank: not namedEach cell is one answer, NetSPI on the left and Bishop Fox on the right.The direct prompt
NetSPI first, Bishop Fox not the choice
1 of 14 modelsBishop Fox was named in the answer but not as the choice, or not at all.Bishop Fox first, NetSPI not the choice
1 of 14 modelsNetSPI was named in the answer but not as the choice, or not at all.Neither was the first choice, one was named
5 of 14 modelsThe answer put something else first and named one of the two as an alternative.Neither was named
7 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
NetSPI0%#– of 8Bishop Fox0%#– of 8NetSPI30%#1 of 12Bishop Fox12%#4 of 12What the models said about NetSPI
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Five of six in this category shown.
“Better for complex, high-risk environments, but likely more than a typical mid-sized company needs initially” Perplexity Sonar · paraphrase prompt · soft negative
“traditional firms like Rapid7 or NetSPI might feel less "as-a-service" for ongoing needs” Grok 4.20 · paraphrase prompt · soft negative
“I'd generally recommend NetSPI if you want the safest "default" choice for a mature PTaaS program” GPT-5.4 mini · paraphrase prompt · first choice
“Choose Astra or NetSPI if you need a rigorous, manual audit that satisfies strict auditors” Qwen 3.7 Flash · comparative prompt · first choice
“NetSPI is a strong default choice for mid-market-to-enterprise buyers” GPT-5.4 mini · direct prompt · first choice
What the models said about Bishop Fox
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Four of five in this category shown.
“Better for complex, high-risk environments, but likely more than a typical mid-sized company needs initially” Perplexity Sonar · paraphrase prompt · soft negative
“widely regarded as one of the most technically capable boutique firms” Qwen 3.7 Flash · direct prompt · first choice
“High-risk, custom engagements | Specialist offensive-security consultancy focused on deep manual testing” Perplexity Sonar · comparative prompt · alternative
“Recognized for technical depth, manual testing, and a strong reputation in the security community.” Mistral Small · comparative 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.