Every category where a model named GCP Cloud Load Balancing 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	Since September 2026
Load balancers	Network and edge	0%	17 of 94	25%	12	criticized challenger

Movement

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

By model

How each model treated GCP Cloud Load Balancing across every prompt where it was named for a mid-market B2B company. Fourteen models, six prompts per category.

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Model	First choice	Alternative	Mention	Negative	Labels
Claude Haiku 4.5	0	0	0	0	0
GPT-5.4 mini	0	0	0	0	0
Gemini 3.5 Flash	0	1	0	0	1
Perplexity Sonar	0	0	0	0	0
Grok 4.1 Fast	0	1	0	1	2
Mistral Small	0	0	1	1	2
DeepSeek V4 Flash	0	2	0	0	2
Llama 4 Maverick	0	0	0	0	0
Qwen 3.7 Flash	0	1	0	0	1
Kimi K2	0	0	1	0	1
GLM 4.7 FlashX	1	0	0	0	1
MiniMax M2.5	0	1	0	1	2
GPT-6 Luna	0	0	0	0	0
Muse Glimmer 30B	0	0	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 labelsNone

Paraphrase0 labelsNone

Comparative3 labelsNone

Budget-constrained2 labelsNone

Scale-constrained5 labels1

Negative10 labels1not counted in share

First choiceAlternativeMentionNegative23 labels in all, every segment counted; 1 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.

“Cloud‑native LBs (AWS ALB/NLB, GCP Cloud LB, Azure Standard LB) are designed to do exactly this.” GLM 4.7 FlashX · Load balancers · negative prompt · first choice

“use cloud-managed services (like AWS ALB, Azure Load Balancer, or GCP Cloud Load Balancing)” Gemini 3.5 Flash · Load balancers · negative prompt · alternative

“managed load balancer (AWS ALB/NLB, Azure Standard LB, GCP Load Balancing)” DeepSeek V4 Flash · Load balancers · negative prompt · alternative

“Cloud-provider native (AWS ALB, Azure Front Door, GCP Cloud LB)” Qwen 3.7 Flash · Load balancers · negative 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.

“Cloud-native load balancers (AWS ELB, Azure LB, GCP LB) ... may lack deep packet inspection, advanced routing rules, or cross-cloud consistency” MiniMax M2.5 · Load balancers · negative prompt · soft negative

“Auth complexity, limited customization/IAM integration, health check glitches, complex pricing.” Grok 4.1 Fast · Load balancers · negative prompt · soft negative

“excellent within their ecosystems but can lead to vendor lock-in” Mistral Small · Load balancers · negative prompt · soft negative

Named alongside

The products named in the same answers as GCP Cloud Load Balancing, over the 23 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and GCP Cloud Load Balancing was named but was not.

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ProductSame answerTook the first choice insteadHead to head

HAProxy20 of 237Not among the top eight

NGINX19 of 234Not among the top eight

AWS Elastic Load Balancing15 of 231Not among the top eight

Azure Load Balancer15 of 230Not among the top eight

Citrix ADC12 of 230Not among the top eight

F5 BIG-IP11 of 233Not among the top eight

AWS ALB6 of 230Not among the top eight

Azure Basic Load Balancer5 of 230Not among the top eight

Cloudflare Load Balancing5 of 230Not among the top eight

F54 of 232Not among the top eight

A head-to-head page exists where both products are among a category's top eight. 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 Cloud Load Balancing. A fact about retrieval, not a lever on the model.

Citations exist only for the models that return a source list, five of the fourteen in this edition, so these counts come from 20 of the 23 answers that named GCP Cloud Load Balancing and are not a share of its labels.

Domains cited

loadbalancer.org15

guideflow.com12

g2.com9

f5.com8

kemptechnologies.com8

learn.g2.com8

learn.microsoft.com8

linkedin.com7

myhospitalnow.com7

aws.github.io6

No domain is on file for GCP Cloud Load Balancing, so its own site is not marked.

Pages cited

loadbalancer.org/blog/whats-the-best-cloud-load-balancer11

guideflow.com/blog/load-balancer-software8

learn.g2.com/best-load-balancing-software8

guideflow.com/et-ee/blog/load-balancer-software7

myhospitalnow.com/blog/top-10-load-balancers-features-pros-cons-comparison7

aws.github.io/aws-networking-best-practices/application-networking/load-balancing5

learn.microsoft.com/en-us/azure/load-balancer/secure-load-balancer5

onenoughtone.com/learning-path/system-design-hld/learning/load-balancer-comparison/55

Pages are listed as the models cited them.

Search and answers

Where GCP Cloud Load Balancing stands in Google search beside where it stands in the models' answers.

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In search

Google, US estimates

Searches for its name, Google: 20 a month (“gcp cloud load balancing”)
AI search demand for its name, est.: 4 a month
Its own site: No site of its own on file, so no site figures

In answers

This edition

Share of first choices

rank 17 of 94 in load balancers

Segment leader

29%

HAProxy

First choices: 1 across its categories
Named in: 23 answers
Its own site cited: No site on file to match

Search figures are US estimates from DataForSEO, read October 5, 2026; AI search demand is its modeled, directional estimate, not a count of queries to any assistant. The answers are this edition's. Two measurements side by side: neither is read as the cause of the other.

Names read as GCP Cloud Load Balancing

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

GCP LB 5GCP Load Balancing 2GCP Cloud LB 1GCP Load Balancer 1

Follow GCP Cloud Load Balancing

An email the morning each edition publishes: where this product moved, where it held, and by how much against the noise floor. One address, confirmed by a click; a stop link in every email.

Already following? Everything you follow, with a stop for each.

The company

GCP is the company behind GCP Cloud Load Balancing.

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On record

Company records

Also from GCP: GCP Artifact Registry, GCP Cloud Armor, GCP Cloud Build, GCP Cloud Endpoints, GCP Cloud LB, GCP DLP, GCP Dataflow, GCP Dataplex and 9 more

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 Cloud Load Balancing'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 Cloud Load Balancing, applied by version and listed in the change log; and a one-line description supplied by the vendor and marked as such.

What a new claim receivesHide what a new claim receives

A new claim receives the current edition's vendor brief for GCP Cloud Load Balancing by email, built from the raw record of the edition. It shows:

where GCP Cloud Load Balancing is named, by buyer and by framing, and which cells hold its first choices;
the claims the models make when they name it, ranked, with the strongest and the weakest quoted;
its vocabulary against the segment leader's, and the pages the models cited;
who was chosen in the answers that did not name GCP Cloud Load Balancing, and every reason the record gives;
a battlecard for each top rival: the head-to-head split, why they win, and the reservation quoted against them;
one page of published figures cleared to show a buyer.