Three of fourteen models named Microsoft Hyper-V first on the direct prompt; one named VMware vSphere. Both were named by all fourteen models and Microsoft Hyper-V carries 52 labels and VMware vSphere 64, so the shares are not directly comparable.
Named in one category 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 server virtualization platforms page.
Across every category in the November 2026 Edition, Microsoft Hyper-V and VMware vSphere were named in the same answer 119 times, of the 137 answers naming Microsoft Hyper-V and the 191 naming VMware vSphere. In those answers VMware vSphere took the first choice thirty-two times and Microsoft Hyper-V sixteen.
| Model | DirectMH | ParaphraseMH | ComparativeMH | Budget-constrainedMH | Scale-constrainedMH | NegativeMH |
|---|---|---|---|---|---|---|
| Claude Haiku 4.5 | MH | MH | MH | MH | ||
| GPT-5.4 mini | MH | MH | MH | MH | ||
| Gemini 3.5 Flash | MH | MH | ||||
| Perplexity Sonar | MH | |||||
| Grok 4.20 | MH | MH | MH | MH | ||
| Mistral Small | MH | MH | MH | MH | MH | MH |
| DeepSeek V4 Flash | MH | MH | MH | MH | ||
| Llama 4 Maverick | MH | |||||
| Qwen 3.7 Flash | MH | MH | MH | MH | ||
| Kimi K2 | MH | MH | MH | |||
| GLM 4.7 FlashX | MH | MH | MH | MH | MH | |
| MiniMax M2.5 | MH | MH | MH | MH | ||
| GPT-6 Luna | MH | |||||
| Muse Glimmer 30B | MH | MH | MH |
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 seven in this category shown.
“Avoid: Hyper-V on Windows Server 2012 or Windows Server 2012 R2.” GLM 4.7 FlashX · negative prompt · hard negative
“Microsoft Hyper-V 2016 | May 2025 (deprecated) | Moderate” MiniMax M2.5 · negative prompt · hard negative
“System Center adds cost, weaker Linux guest support, and less innovation recently are concerns” Claude Haiku 4.5 · negative prompt · soft negative
“For most mid-market B2B companies, Hyper-V often represents the best value proposition due to lower costs” Claude Haiku 4.5 · direct prompt · first choice
“→ Microsoft Hyper-V if you're already a Microsoft shop and want zero extra licensing overhead” DeepSeek V4 Flash · direct prompt · first choice
“Proxmox VE or Microsoft Hyper-V often emerge as the top practical choices in 2024–2025” Grok 4.20 · direct prompt · first choice
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of eight in this category shown.
“VMware vSphere is a platform that some AI models recommend avoiding unless necessary, due to the cost increases post-Broadcom acquisition” Llama 4 Maverick · negative prompt · hard negative
“End of general support (Oct 2025 for 7.x).<br>- No new security patches, bug fixes, or standard support after EOL.” Grok 4.20 · negative prompt · hard negative
“What to Avoid on a Budget - VMware vSphere/ESXi ... No longer viable for budget-conscious SMBs.” DeepSeek V4 Flash · budget prompt · hard negative
“Stay with VMware. VCF or VVF on the terms above. ... While vSphere's performance and vSAN integration remain unmatched, mid-market enterprises are experiencing up to 3x price hikes upon renewal.” Muse Glimmer 30B · scale prompt · first choice
“Widely regarded as the leader in enterprise virtualization, offering robust scalability, centralized management, and strong performance for large-scale environments.” Mistral Small · comparative prompt · first choice
“For over a decade, VMware was the undisputed king of virtualization. It sets the industry standard for features, management, and reliability.” Qwen 3.7 Flash · comparative 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.