Two of fourteen models named Illumio Segmentation first on the direct prompt; three named Akamai Guardicore Segmentation. Both were named by all fourteen models and Illumio Segmentation carries 56 labels and Akamai Guardicore Segmentation 43, so the shares are not directly comparable.
Named in one category 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 microsegmentation page.
Across every category in the November 2026 Edition, Illumio Segmentation and Akamai Guardicore Segmentation were named in the same answer 148 times, of the 184 answers naming Illumio Segmentation and the 158 naming Akamai Guardicore Segmentation. In those answers Akamai Guardicore Segmentation took the first choice eight times and Illumio Segmentation fifty-seven.
| 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 |
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.
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of eight in this category shown.
“Avoid Enterprise Giants (like Illumio or Tufin) unless you have the scale” Qwen 3.7 Flash · budget prompt · hard negative
“Cons reported are: requires tuning in high-throughput environments; PCE can experience slowness at very large scale... Agent overhead and deployment time is a common friction.” Muse Glimmer 30B · negative prompt · soft negative
“even the well-known players like Illumio face criticism primarily around a steep learning curve, not necessarily abandonment-level problems” DeepSeek V4 Flash · negative prompt · soft negative
“Best dedicated enterprise platform: Illumio is a strong default when the priority is workload-centric segmentation across heterogeneous hybrid environments.” Perplexity Sonar · comparative prompt · first choice
“PeerSpot ranks Illumio Segmentation as the top rated solution in 2026 with the largest mind share, 9.0 rating and 21.9% mind share.” Muse Glimmer 30B · comparative prompt · first choice
“A pioneer in microsegmentation... Illumio and Guardicore are leaders, with Illumio offering more mature policy engines” Mistral Small · comparative prompt · first choice
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of seven in this category shown.
“Instead of paying high six-figure annual licenses for enterprise microsegmentation suites like Illumio or Akamai Guardicore” Gemini 3.5 Flash · budget prompt · soft negative
“often start at tens of thousands of dollars annually ... can strain limited budgets” Grok 4.20 · budget prompt · soft negative
“If You Can Stretch the Budget ... Minimum deal size: ~$40,000” Kimi K2 · budget prompt · soft negative
“I recommend Akamai Guardicore Segmentation (now part of Akamai) as the top choice for east-west network segmentation (microsegmentation).” Grok 4.20 · paraphrase prompt · first choice
“the safest "best overall" microsegmentation choice is usually Illumio or Akamai Guardicore Segmentation” GPT-5.4 mini · direct prompt · first choice
“ColorTokens for rapid deployment and Akamai Guardicore (or Illumio) for deeper visibility and policy management” GLM 4.7 FlashX · direct 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.