| Category | Function | Share | Rank | Negative rate | Labels | Quadrant | Since September 2026 |
|---|---|---|---|---|---|---|---|
| Load balancers | Network and edge | 2% | 8 of 94 | 14% | 29 | accepted challenger |
| Model | First choice | Alternative | Mention | Negative | Labels |
|---|---|---|---|---|---|
| Claude Haiku 4.5 | 1 | 0 | 3 | 0 | 4 |
| GPT-5.4 mini | 0 | 1 | 0 | 0 | 1 |
| Gemini 3.5 Flash | 0 | 1 | 0 | 0 | 1 |
| Perplexity Sonar | 0 | 0 | 0 | 0 | 0 |
| Grok 4.1 Fast | 0 | 2 | 0 | 0 | 2 |
| Mistral Small | 0 | 1 | 1 | 1 | 3 |
| DeepSeek V4 Flash | 0 | 2 | 0 | 1 | 3 |
| Llama 4 Maverick | 0 | 0 | 2 | 0 | 2 |
| Qwen 3.7 Flash | 0 | 1 | 0 | 0 | 1 |
| Kimi K2 | 0 | 0 | 1 | 0 | 1 |
| GLM 4.7 FlashX | 0 | 0 | 1 | 0 | 1 |
| MiniMax M2.5 | 0 | 2 | 2 | 1 | 5 |
| GPT-6 Luna | 0 | 2 | 0 | 0 | 2 |
| Muse Glimmer 30B | 0 | 1 | 1 | 1 | 3 |
Verbatim evidence the judge attached to positive labels.
“Cloud-native load balancers (AWS ALB, Azure LB) are often the best fit” Claude Haiku 4.5 · Load balancers · direct prompt · first choice
“Azure Load Balancer for network-layer distribution, especially in Azure-native environments.” GPT-5.4 mini · Load balancers · direct prompt · alternative
“AWS Elastic Load Balancing, Azure Load Balancer, or Google Cloud Load Balancing” MiniMax M2.5 · Load balancers · budget prompt · alternative
“use cloud-managed services (like AWS ALB, Azure Load Balancer, or GCP Cloud Load Balancing)” Gemini 3.5 Flash · Load balancers · negative prompt · alternative
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
“Traefik is rated higher for value, with reviewers expressing greater satisfaction with its pricing compared to Azure Load Balancer.” Muse Glimmer 30B · Load balancers · budget prompt · soft negative
“excellent within their ecosystems but can lead to vendor lock-in” Mistral Small · Load balancers · negative prompt · soft negative
“Similar trade-offs to AWS” DeepSeek V4 Flash · Load balancers · budget prompt · soft negative
Citations exist only for the models that return a source list, five of the fourteen in this edition, so these counts come from 63 of the 83 answers that named Azure Load Balancer and are not a share of its labels.
No domain is on file for Azure Load Balancer, so its own site is not marked.
Pages are listed as the models cited them.
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.
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.
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 Azure Load Balancer'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 Azure Load Balancer, applied by version and listed in the change log; and a one-line description supplied by the vendor and marked as such.
A new claim receives the current edition's vendor brief for Azure Load Balancer by email, built from the raw record of the edition. It shows: