Index › Vendors › GCP Recommender · September 2026 Edition

GCP · 1 category · Named, not ranked

GCP Recommender

7Judge labels

2First choices

0Negative labels

4 of 12Models named it

1Category

September 2026 Edition. Every number here is derived from the raw labels under vendor table vv2026-09.2, every buyer segment counted.

Standing

3 labels, too few to rank

A product needs 10 labels in a category before a share or quadrant is stated. GCP Recommender was named 3 times in FinOps, where Vantage led with 54%. The labels and the evidence are below, counted exactly.

By buyer segmentRead the same way at every buyer size.

Small business6 of 78

under the label threshold

Mid-market24 of 79

under the label threshold

Enterprisenot named

No model named it for this buyer.

In finops · each standing computed within its segment · bars are 0 to 100 · the accent bar is the product's own best reading

Standing by category

Every category where a model named GCP Recommender 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
Cloud cost management	Cloud and infrastructure	0%	24 of 79	0%	3	under 10 labels · led by Vantage at 54%

Movement

This is the first edition on this tier, so no move can be computed for GCP Recommender 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 GCP Recommender 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	0	0	0
Grok 4.1 Fast	0	0	0
Mistral Small	0	0	0
DeepSeek V4 Flash	0	1	1
Llama 4 Maverick	0	0	0
Qwen 3.7 Flash	0	0	0
Kimi K2	1	0	1
GLM 4.7 FlashX	0	0	0
MiniMax M2.5	1	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

Direct0 labelsNone

Paraphrase0 labelsNone

Comparative0 labelsNone

Budget-constrained5 labels2

Scale-constrained0 labelsNone

Negative2 labelsNone

First choiceAlternativeMentionNegative7 labels in all, every segment counted; 2 of the 2 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.

“AWS Cost Explorer, Azure Advisor, GCP Recommender ... Free” Kimi K2 · FinOps · budget prompt · alternative

“GCP Recommender - Free with Google Cloud” MiniMax M2.5 · FinOps · 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 GCP Recommender, over the 7 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and GCP Recommender was named but was not.

ProductSame answerTook the first choice insteadHead to head

Vantage7 of 73Not in the top three

AWS Cost Explorer7 of 72Not in the top three

Infracost6 of 70Not in the top three

Azure Advisor5 of 70Not in the top three

OpenCost4 of 70Not in the top three

CAST AI3 of 70Not in the top three

CloudZero3 of 70Not in the top three

Kubecost3 of 70Not in the top three

SpendArk3 of 70Not in the top three

VMware Tanzu CloudHealth3 of 70Not 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 GCP Recommender. 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 7 of the 7 answers that named GCP Recommender and are not a share of its labels.

Domains cited

cloudaware.com7

cloudzero.com7

spendark.com7

comparedge.com3

costpatrol.io3

g2.com3

gartner.com3

leanopstech.com3

learn.g2.com3

nops.io3

No domain is on file for GCP Recommender, so its own site is not marked.

Pages cited

cloudaware.com/blog/cloud-cost-management-tools7

cloudzero.com/blog/cloud-cost-management-tools7

spendark.com/blog/cloud-cost-tools-small-business7

gartner.com/reviews/market/cloud-financial-management-tools3

learn.g2.com/best-cloud-cost-management-software3

spendark.com/blog/cloud-cost-management-alternatives3

amnic.com/blogs/cloud-cost-management-tools2

apis.io/plans/vantage-sh/vantage-sh-plans-pricing2

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 GCP Recommender'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 GCP Recommender, 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 the vendor's own domain 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.