Faddom vs Zero Networks Segment
Zero of fourteen models named Faddom first on the direct prompt; zero named Zero Networks Segment. Faddom was named by nine of the fourteen models and Zero Networks Segment by thirteen and Faddom carries 11 labels and Zero Networks Segment 31, 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 microsegmentation page.
By framing
FaddomFirst choices, of fourteen modelsZero Networks Segment
Across every category in the October 2026 Edition, Faddom and Zero Networks Segment were named in the same answer eight times, of the 39 answers naming Faddom and the 95 naming Zero Networks Segment. In those answers Zero Networks Segment took the first choice one time and Faddom 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 |
Faddom Zero Networks Segment first choice named as an alternative argued againstblank: not namedEach cell is one answer, Faddom on the left and Zero Networks Segment on the right.The direct prompt
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
11 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
Zero Networks Segment16%#1 of 10Faddom6%#3 of 10Faddom5%#4 of 9Zero Networks Segment2%#5 of 9Zero Networks Segment2%#6 of 9Faddom—not namedWhat the models said about Faddom
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Four of five in this category shown.
“Mapping only, not full enforcement” DeepSeek V4 Flash · direct prompt · soft negative
“The best microsegmentation solution for a company with a limited budget is Faddom, which is a budget-friendly dependency mapping tool.” Llama 4 Maverick · budget prompt · first choice
“For a company with limited budget, I'd recommend starting with Faddom” MiniMax M2.5 · budget prompt · first choice
“start with Enclave (free) or Faddom (low-cost)” Mistral Small · budget prompt · first choice
What the models said about Zero Networks Segment
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Five of six in this category shown.
“Zero Networks' MFA-centric model may not suit every environment... with Kubernetes segmentation still maturing.” Claude Haiku 4.5 · negative prompt · soft negative
“Emerging; less mature integrations” Grok 4.1 Fast · comparative prompt · soft negative
“Prioritize modern, identity/label-based tools (e.g., Calico for K8s, Zero Networks for simplicity)” Grok 4.1 Fast · negative prompt · first choice
“I recommend Zero Networks.” Qwen 3.7 Flash · paraphrase prompt · first choice
“Zero Networks (Runner-Up) - Best if: Your company is cloud-heavy or you want zero-trust segmentation” GLM 4.7 FlashX · 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.