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Managed Kubernetes platforms · November 2026 Edition

Google Kubernetes Engine vs Amazon EKS

Eleven of fourteen models named Google Kubernetes Engine first on the direct prompt; zero named Amazon EKS. Both were named by all fourteen models and Google Kubernetes Engine carries 77 labels and Amazon EKS 72, so the shares are not directly comparable.

Named in one category this edition.

Amazon EKS

criticized challenger

Named in one category this edition.

First-choice share52%4%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate14%28%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#1#4A position in a field of 12; printed, not drawn.
Labels7772A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, Google Kubernetes Engine reading right to left. Rank and label count are printed, not drawn.Azure Kubernetes Service was named alongside these two in nine of the fourteen direct answers. Google Kubernetes Engine vs DigitalOcean Kubernetes · Google Kubernetes Engine vs Azure Kubernetes Service · Google Kubernetes Engine vs Linode Kubernetes Engine

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.

By framing

How many of the fourteen models made each the first choice, per way of asking, and how many argued against it.
Google Kubernetes EngineFirst choices, of fourteen modelsAmazon EKS
Direct110
Paraphrase1121 against Amazon EKS
Comparative50
Budget-constrained103 against Google Kubernetes Engine · 8 against Amazon EKS
Scale-constrained10
Negative208 against Google Kubernetes Engine · 11 against Amazon EKS
Bars are first choices, 0 to 14 each sideModels that argued againstA model can name both, so the two sides of a row do not sum to fourteen.

Across every category in the November 2026 Edition, Google Kubernetes Engine and Amazon EKS were named in the same answer 217 times, of the 227 answers naming Google Kubernetes Engine and the 223 naming Amazon EKS. In those answers Amazon EKS took the first choice five times and Google Kubernetes Engine eighty-two.

Every model, every framing

The eighty-four answers behind the chart above, one cell each: where Google Kubernetes Engine and Amazon EKS stood in it.
ModelDirectParaphraseComparativeBudget-constrainedScale-constrainedNegative
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
Google Kubernetes Engine Amazon EKS first choice named as an alternative argued againstblank: not namedEach cell is one answer, Google Kubernetes Engine on the left and Amazon EKS on the right.

The direct prompt

The plain question, one answer per model, grouped by where Google Kubernetes Engine and Amazon EKS stood in it.

Google Kubernetes Engine first, Amazon EKS an alternative

11 of 14 modelsAmazon EKS was named in the answer but not as the choice, or not at all.
GPT-5.4 miniGoogle Kubernetes Engine alternatives: Amazon EKS
Gemini 3.5 FlashGoogle Kubernetes Engine alternatives: Amazon EKS, Azure Kubernetes Service, Porter, Qovery
Perplexity SonarGoogle Kubernetes Engine alternatives: Amazon EKS, Azure Kubernetes Service, DigitalOcean Kubernetes
Grok 4.20Google Kubernetes Engine alternatives: Amazon EKS, Azure Kubernetes Service, Red Hat OpenShift
Mistral SmallGoogle Kubernetes Engine alternatives: Amazon EKS, Azure Kubernetes Service, Northflank, Red Hat OpenShift
DeepSeek V4 FlashGoogle Kubernetes Engine alternatives: Amazon EKS, Azure Kubernetes Service, DigitalOcean Kubernetes
Llama 4 MaverickGoogle Kubernetes Engine alternatives: Amazon EKS, Atmosly, DigitalOcean Kubernetes
Qwen 3.7 FlashGoogle Kubernetes Engine alternatives: Amazon EKS, Azure Kubernetes Service, Rancher, Red Hat OpenShift
Kimi K2Google Kubernetes Engine alternatives: Amazon EKS, Azure Kubernetes Service
GPT-6 LunaGoogle Kubernetes Engine alternatives: AKS Automatic, Amazon EKS
Muse Glimmer 30BGoogle Kubernetes Engine alternatives: Amazon EKS, Azure Kubernetes Service, Mirantis Kubernetes Engine, Rancher, Red Hat OpenShift, VMware Tanzu

Neither was the first choice, one was named

1 of 14 modelsThe answer put something else first and named one of the two as an alternative.
GLM 4.7 FlashXAzure Kubernetes Service alternatives: Amazon EKS, Google Kubernetes Engine, Rancher

Neither was named

2 of 14 modelsThe answer made no first choice from these two in this category.
Claude Haiku 4.5no first choice
MiniMax M2.5no first choice

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

The same question asked on behalf of a different buyer. Each standing is computed within its segment and they are never added together. The figures above are the mid-market standing, which is the one the category orders by.
Small business
Google Kubernetes Engine leads by thirty-one points.
Google Kubernetes Engine31%#2 of 14
Amazon EKS0%#13 of 14
The full small business standing →
Mid-marketThe figures above
Google Kubernetes Engine leads by forty-eight points.
Google Kubernetes Engine52%#1 of 12
Amazon EKS4%#4 of 12
The full mid-market standing →
Enterprise
Google Kubernetes Engine leads by fifty-one points.
Google Kubernetes Engine57%#1 of 8
Amazon EKS6%#4 of 8
The full enterprise standing →

What the models said about Google Kubernetes Engine

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

What the models said about Amazon EKS

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 ... introduce several "budget killers"” Qwen 3.7 Flash · budget prompt · hard negative
“Frequently cited as one of the most frustrating... Many teams report it as a "nightmare" for anything beyond basic setups.” Grok 4.20 · negative prompt · hard negative
“Avoid AWS EKS for tight budgets unless you have heavy AWS usage (control plane fees + EC2 costs add up quickly).” Grok 4.20 · budget prompt · hard negative
“For most mid-sized B2B companies, EKS, GKE, or AKS are the top picks due to their maturity and ecosystem.” Mistral Small · paraphrase prompt · first choice
“EKS is usually the safest default for a mid-sized B2B company” GPT-5.4 mini · paraphrase prompt · first choice
“Preferable if the company already relies heavily on AWS services... typically requires more platform-engineering effort.” Perplexity Sonar · paraphrase prompt · alternative
Also compared

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.