Eleven of fourteen models named Google Kubernetes Engine first on the direct prompt; zero named DigitalOcean Kubernetes. Both were named by all fourteen models and Google Kubernetes Engine carries 77 labels and DigitalOcean Kubernetes 42, 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 managed kubernetes platforms page.
Across every category in the November 2026 Edition, Google Kubernetes Engine and DigitalOcean Kubernetes were named in the same answer 107 times, of the 227 answers naming Google Kubernetes Engine and the 117 naming DigitalOcean Kubernetes. In those answers DigitalOcean Kubernetes took the first choice forty-five times and Google Kubernetes Engine thirty-four.
| 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.
“What to Avoid (The "Expensive" Options) ... AWS EKS, Google GKE, and Azure AKS ... budget killers” Qwen 3.7 Flash · budget prompt · hard negative
“You need privileged containers, node-level access, or fine-grained control over node infrastructure. Autopilot deliberately restricts some of these” GPT-6 Luna · negative prompt · soft negative
“GKE is deeply integrated with Google Cloud's specific networking and observability tools. Moving workloads off GKE can be difficult.” GLM 4.7 FlashX · negative prompt · soft negative
“the recommended hosted Kubernetes service for a mid-sized B2B company is Google Kubernetes Engine (GKE), as it is the clear leader with 43% of first choices” Llama 4 Maverick · paraphrase prompt · first choice
“If you want the most automation out of the box and strong ML/AI integrations, GKE is the most recommended choice in current AI model consensus.” Muse Glimmer 30B · direct prompt · first choice
“Often ranked as the best overall for reliability, monitoring, and ease (especially Autopilot mode, which is more "hands-off").” Grok 4.20 · negative 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.
“it lacks the extensive ecosystem of tools and support channels of AWS/GCP... not suitable for mission-critical enterprise applications” GLM 4.7 FlashX · negative prompt · soft negative
“Be cautious if you: Need advanced networking features... Be most wary of smaller clouds with narrow version support” Kimi K2 · negative prompt · soft negative
“DOKS documents those limits and warns against modifying its managed components.” GPT-6 Luna · negative prompt · soft negative
“the most cited practical picks are DigitalOcean Kubernetes for a managed, simple start, and Linode LKE for a free control plane with price stability” Muse Glimmer 30B · budget prompt · first choice
“The best managed Kubernetes platform for a company with a limited budget is DigitalOcean Kubernetes (DOKS) or Linode Kubernetes Engine (LKE).” Llama 4 Maverick · budget prompt · first choice
“For strictest budget, DigitalOcean Kubernetes offers the best value with zero control plane costs and affordable node pricing.” MiniMax M2.5 · budget 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.