# Akamai Guardicore Segmentation vs Zscaler Private Access: which do AI models recommend for microsegmentation, October 2026

IT AI Recommendation Index, October 2026 Edition, Microsegmentation. One of fourteen models named Akamai Guardicore Segmentation first on the direct prompt; one named Zscaler Private Access. Page: https://it-ai-index.com/network/microsegmentation/akamai-guardicore-segmentation-vs-zscaler-private-access/

| | First-choice share | Rank | Negative rate | Labels | Models naming it |
|---|---|---|---|---|---|
| Akamai Guardicore Segmentation | 12% | #3 of 9 | 20% | 51 | 14 of 14 |
| Zscaler Private Access | 2% | #6 of 9 | 0% | 14 | 8 of 14 |

## The direct prompt, model by model

- Qwen 3.7 Flash: akamai guardicore segmentation first (first choices: Akamai Guardicore Segmentation, Illumio Segmentation) (alternatives: ColorTokens Xshield)
- Perplexity Sonar: zscaler private access first (first choices: ColorTokens Xshield, Zscaler Private Access) (alternatives: Akamai Guardicore Segmentation, Cisco Secure Workload, Illumio Segmentation)
- Claude Haiku 4.5: neither first, one named (first choices: ColorTokens Xshield) (alternatives: Akamai Guardicore Segmentation, Cisco Secure Workload, Illumio Segmentation, Zero Networks Segment)
- GPT-5.4 mini: neither first, one named (first choices: Illumio Segmentation) (alternatives: Akamai Guardicore Segmentation, Zero Networks Segment)
- Grok 4.1 Fast: neither first, one named (first choices: ColorTokens Xshield) (alternatives: Akamai Guardicore Segmentation, Illumio Segmentation, Zscaler Private Access)
- Mistral Small: neither first, one named (first choices: ColorTokens Xshield) (alternatives: Akamai Guardicore Segmentation, Elisity, Illumio Segmentation)
- DeepSeek V4 Flash: neither first, one named (first choices: ColorTokens Xshield) (alternatives: Akamai Guardicore Segmentation, Illumio Segmentation)
- Kimi K2: neither first, one named (first choices: ColorTokens Xshield) (alternatives: Akamai Guardicore Segmentation, SideChannel Enclave)
- GLM 4.7 FlashX: neither first, one named (first choices: ColorTokens Xshield) (alternatives: Akamai Guardicore Segmentation, Illumio Segmentation)
- GPT-6 Luna: neither first, one named (first choices: Illumio Segmentation) (alternatives: Akamai Guardicore Segmentation, Cisco Secure Workload)
- Muse Glimmer 30B: neither first, one named (first choices: ColorTokens Xshield) (alternatives: Akamai Guardicore Segmentation, Cisco Secure Workload, formerly Tetration, Illumio Segmentation)
- Gemini 3.5 Flash: neither named (first choices: ColorTokens Xshield) (alternatives: 6sense, Faddom, HubSpot, SideChannel, Zero Networks Segment)
- Llama 4 Maverick: neither named (first choices: ColorTokens Xshield)
- MiniMax M2.5: neither named (first choices: ColorTokens Xshield) (alternatives: Illumio Segmentation)

## What the models said about Akamai Guardicore Segmentation

- "Avoid first if budget is tight: Akamai Guardicore, because pricing can be a constraint." (GPT-5.4 mini, budget prompt, hard negative)
- "some users report agent overhead, integration bugs, complex maps/visuals, and accuracy limits in risk detection" (Grok 4.1 Fast, negative prompt, soft negative)
- "Initial mapping complexity and operational overhead... can be overwhelming to organize manually" (Gemini 3.5 Flash, negative prompt, soft negative)
- "Akamai Guardicore Segmentation is a top choice due to its strong east-west visibility, ease of deployment, and support for hybrid environments" (Mistral Small, paraphrase prompt, first choice)
- "Illumio and Akamai Guardicore Segmentation are generally considered the top contenders for this segment" (Qwen 3.7 Flash, direct prompt, first choice)
- "For most mid-sized B2B companies, I'd recommend Akamai Guardicore Segmentation as your primary choice." (GLM 4.7 FlashX, paraphrase prompt, first choice)

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. Comparisons are drawn for the top eight products in each category. Published under CC BY 4.0; the output is the models' output, and nothing here is a recommendation by the index.