Every category where a model named Kubeflow for a mid-market B2B company. Share is first choices across the direct, paraphrase, budget and scale prompts; rank is within every product named in that category.

Category	Function	Share	Rank	Negative rate	Labels	Quadrant
ML platforms	Data platform	0%	77 of 99	38%	13	criticized challenger
Workflow orchestration	Data platform	0%	34 of 86	0%	2	under 10 labels · led by Prefect at 24%

Movement

This is the first edition on this tier, so no move can be computed for Kubeflow yet. From the next edition this section shows, per buyer segment, whether its share moved by more than the measured noise floor.

By model

How each model treated Kubeflow across every prompt where it was named for a mid-market B2B company. Twelve models, six prompts per category.

Model	Alternative	Mention	Negative	Labels
Claude Haiku 4.5	0	1	0	1
GPT-5.4 mini	0	0	0	0
Gemini 3.5 Flash	0	0	2	2
Perplexity Sonar	0	0	0	0
Grok 4.1 Fast	0	2	0	2
Mistral Small	0	1	0	1
DeepSeek V4 Flash	0	0	1	1
Llama 4 Maverick	0	0	1	1
Qwen 3.7 Flash	0	1	1	2
Kimi K2	0	2	0	2
GLM 4.7 FlashX	2	0	0	2
MiniMax M2.5	1	0	0	1

By framing

Which of the six questions produced the naming. By model says how often; this says asked what. The first-choice count on the right carries the marks of the models that produced it.

FramingLabels by classFirst choices

Direct1 labelNone

Paraphrase12 labelsNone

Comparative7 labelsNone

Budget-constrained0 labelsNone

Scale-constrained4 labelsNone

Negative14 labels1not counted in share

First choiceAlternativeMentionNegative38 labels in all, every segment counted; 0 of the 1 first choices count toward share, since the comparative and negative framings do not. The bar is one segment per label class, to scale within the framing.

What the models said for it

Verbatim evidence the judge attached to positive labels.

“Free, fully customizable, but higher operational overhead and steeper learning curve.” GLM 4.7 FlashX · ML platforms · paraphrase prompt · alternative

“Open-source but requires significant management overhead” MiniMax M2.5 · ML platforms · paraphrase prompt · alternative

“Kubernetes-native, custom pipelines and deployment” GLM 4.7 FlashX · ML platforms · comparative prompt · alternative

And against it

Verbatim evidence attached to negative labels. A warning on a product with few labels is a warning; on a product with many, it is one voice among them.

“Do not try to fully self-host highly complex open-source stacks (like raw Kubeflow) unless you have a massive, specialized platform team.” Gemini 3.5 Flash · ML platforms · scale prompt · hard negative

“maintaining a self-hosted Kubeflow cluster can turn into a massive maintenance burden” Qwen 3.7 Flash · ML platforms · negative prompt · soft negative

“Unlike raw Kubeflow (which requires dedicated Kubernetes platform engineers)” Gemini 3.5 Flash · ML platforms · paraphrase prompt · soft negative

“flexible and free, but requires ML engineering depth to operate” DeepSeek V4 Flash · ML platforms · paraphrase prompt · soft negative

Named alongside

The products named in the same answers as Kubeflow, over the 38 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and Kubeflow was named but was not.

ProductSame answerTook the first choice insteadHead to head

Amazon SageMaker34 of 385Not in the top three

Google Vertex AI28 of 386Not in the top three

Azure Machine Learning28 of 383Not in the top three

MLflow23 of 381Not in the top three

Databricks20 of 385Not in the top three

DataRobot15 of 381Not in the top three

Dataiku8 of 380Not in the top three

H2O.ai8 of 380Not in the top three

RapidMiner6 of 380Not in the top three

DagsHub5 of 380Not in the top three

A head-to-head page exists where both products are in a category's top three. The other rows are the same fact without a page behind them, so they link to the product instead.

What carried it into the answer

The sites and pages cited by the answers that named Kubeflow. A fact about retrieval, not a lever on the model.

Citations exist only for the models that return a source list, four of the twelve in this edition, so these counts come from 30 of the 38 answers that named Kubeflow and are not a share of its labels.

Domains cited

g2.com15

techtarget.com11

truefoundry.com10

dagshub.com9

ciopages.com8

devopsschool.com8

linkedin.com8

medium.com8

trustradius.com8

tinyctl.dev7

Ninety-two of the ninety-two domain citations in answers naming Kubeflow came from somebody else's page.

Pages cited

dagshub.com/blog/top-deep-learning-platforms8

techtarget.com/ai/tip/Compare-6-top-MLOps-platforms7

tinyctl.dev/roundups/machine-learning-platforms7

articsledge.com/post/machine-learning-platforms-comparison-azure-ai-vs-aws-sagemaker-vs-go6

dataiku.com/blog/enterprise-machine-learning-platforms-how-to-choose6

g2.com/categories/mlops-platforms6

mlopscrew.com/blog/top-10-mlops-platforms6

us.fitgap.com/search/mlops-platforms/small-business6

Pages are listed as the models cited them.

Names read as Kubeflow

What the judge wrote, as written, with how often. The vendor table decides that these count as Kubeflow; a claim can dispute any of them.

Kubeflow (self‑hosted) 1

Is this your product?

Claim this page

Claiming is free and changes nothing in the data. A claimed page shows a verified contact who is told when each edition publishes and when Kubeflow's standing changes by more than the noise floor; the right to propose corrections to the vendor table, meaning names the judge wrote that should or should not read as Kubeflow, applied by version and listed in the change log; and a one-line description supplied by the vendor and marked as such.

It does not get any change to labels, shares or verdicts, any preview, or any say over which quotes appear. A verification link goes to your work email; an address at kubeflow.org is approved on the spot, any other address is reviewed by hand.

Your name and company appear on the claimed page, or the company alone if you ask below. A title and a LinkedIn address appear there too if you give them, and are left off if you do not. Your email address is never published.