Every category where a model named BigML 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%	24 of 99	0%	4	under 10 labels · led by Azure Machine Learning at 17%

Movement

This is the first edition on this tier, so no move can be computed for BigML 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 BigML across every prompt where it was named for a mid-market B2B company. Twelve models, six prompts per category.

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

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

Direct3 labels1

Paraphrase0 labelsNone

Comparative1 labelNone

Budget-constrained7 labelsNone

Scale-constrained0 labelsNone

Negative4 labelsNone

First choiceAlternativeMentionNegative15 labels in all, every segment counted; 1 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.

“Offers an entry-level plan for AutoML and simple deployment, which can be cost-effective for small businesses” Mistral Small · ML platforms · budget prompt · alternative

“Other options include Google Vertex AI (AI Platform) and BigML, which offer affordable pricing models” Llama 4 Maverick · ML platforms · budget prompt · alternative

“A good option if you want simple AutoML and hosted predictions” Perplexity Sonar · ML platforms · budget 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.

No model argued against it.

Named alongside

The products named in the same answers as BigML, over the 15 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and BigML was named but was not.

ProductSame answerTook the first choice insteadHead to head

Azure Machine Learning10 of 151Not in the top three

KNIME9 of 155Not in the top three

Google Vertex AI9 of 152Not in the top three

Amazon SageMaker7 of 150Not in the top three

Google Colab4 of 152Not in the top three

MLflow4 of 152Not in the top three

KNIME Analytics Platform3 of 152Not in the top three

Kaggle3 of 151Not in the top three

RapidMiner3 of 151Not in the top three

DataRobot3 of 150Not 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 BigML. 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 15 of the 15 answers that named BigML and are not a share of its labels.

Domains cited

g2.com12

startupstash.com12

godofprompt.ai8

softwr.com7

learn.g2.com6

articsledge.com5

deepusecase.com4

devopsschool.com4

reddit.com4

appreviewlab.com3

Sixty-five of the sixty-five domain citations in answers naming BigML came from somebody else's page.

Pages cited

startupstash.com/best-low-code-machine-learning-platforms12

godofprompt.ai/blog/machine-learning-platforms-for-small-businesses8

softwr.com/best/machine-learning-for-small-businesses7

g2.com/categories/machine-learning/small-business6

g2.com/discussions/what-is-the-most-cost-efficient-machine-learning-platform6

g2.com/categories/data-science-and-machine-learning-platforms/small-business5

g2.com/categories/mlops-platforms/small-business5

learn.g2.com/best-data-science-ml-platforms4

Pages are listed as the models cited them.

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 BigML'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 BigML, 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 bigml.com 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.