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Load balancers · November 2026 Edition

AWS Elastic Load Balancing vs AWS Application Load Balancer

Zero of fourteen models named AWS Elastic Load Balancing first on the direct prompt; two named AWS Application Load Balancer. AWS Elastic Load Balancing was named by fourteen of the fourteen models and AWS Application Load Balancer by ten and AWS Elastic Load Balancing carries 34 labels and AWS Application Load Balancer 14, so the shares are not directly comparable.

AWS Elastic Load Balancing

accepted challenger

Named in one category this edition.

Named in one category this edition.

First-choice share4%4%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate9%14%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#5#7A position in a field of 16; printed, not drawn.
Labels3414A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, AWS Elastic Load Balancing reading right to left. Rank and label count are printed, not drawn.NGINX was named alongside these two in eleven of the fourteen direct answers. HAProxy vs AWS Elastic Load Balancing · HAProxy vs AWS Application Load Balancer · NGINX vs AWS Elastic Load Balancing

Share is the count of first choices across the direct, paraphrase, budget and scale prompts over all fourteen models, for a mid-market B2B company; rank is within the category; every quote names the model and the prompt it came from. Both figures come from the load balancers page.

By framing

How many of the fourteen models made each the first choice, per way of asking, and how many argued against it.
AWS Elastic Load BalancingFirst choices, of fourteen modelsAWS Application Load Balancer
Direct021 against AWS Elastic Load Balancing
Paraphrase00
Comparative10
Budget-constrained101 against AWS Elastic Load Balancing
Scale-constrained10
Negative001 against AWS Elastic Load Balancing · 2 against AWS Application Load Balancer
Bars are first choices, 0 to 14 each sideModels that argued againstA model can name both, so the two sides of a row do not sum to fourteen.

Every model, every framing

The eighty-four answers behind the chart above, one cell each: where AWS Elastic Load Balancing and AWS Application Load Balancer stood in it.
ModelDirectAEAAParaphraseAEAAComparativeAEAABudget-constrainedAEAAScale-constrainedAEAANegativeAEAA
Claude Haiku 4.5AAAEAE
GPT-5.4 miniAA
Gemini 3.5 FlashAAAEAE
Perplexity SonarAEAEAEAA
Grok 4.20AEAEAEAE
Mistral SmallAEAE
DeepSeek V4 FlashAEAEAEAEAE
Llama 4 MaverickAE
Qwen 3.7 FlashAEAAAE
Kimi K2AE
GLM 4.7 FlashXAEAA
MiniMax M2.5AAAAAEAE
GPT-6 LunaAA
Muse Glimmer 30BAEAEAA
AE AWS Elastic Load BalancingAA AWS Application Load BalancerAE first choiceAE named as an alternativeAE argued againstblank: not namedEach cell is one answer, AWS Elastic Load Balancing on the left and AWS Application Load Balancer on the right.

The direct prompt

The plain question, one answer per model, grouped by where AWS Elastic Load Balancing and AWS Application Load Balancer stood in it.

AWS Application Load Balancer first, AWS Elastic Load Balancing not the choice

2 of 14 modelsAWS Elastic Load Balancing was named in the answer but not as the choice, or not at all.
Claude Haiku 4.5AWS Application Load Balancer, Azure Load Balancer, Network Load Balancer alternatives: Google Cloud Load Balancing, NGINX
GPT-5.4 miniAWS Application Load Balancer alternatives: AWS Network Load Balancer, Cloudflare Load Balancing, Google Cloud Application Load Balancer

Neither was the first choice, one was named

4 of 14 modelsThe answer put something else first and named one of the two as an alternative.
Gemini 3.5 FlashCloudflare Load Balancing alternatives: AWS Application Load Balancer, Azure Application Gateway, GCP Cloud Load Balancing, HAProxy, NGINX, Progress Kemp LoadMaster
Perplexity SonarProgress Kemp LoadMaster alternatives: AWS Elastic Load Balancing, Cloudflare Load Balancing, HAProxy, NGINX
MiniMax M2.5no first choice alternatives: AWS Application Load Balancer, Azure Load Balancer, Citrix ADC, F5 BIG-IP, Google Cloud Load Balancing, HAProxy, NGINX
Muse Glimmer 30BHAProxy alternatives: AWS Elastic Load Balancing, Azure Load Balancer, NGINX, Progress Kemp LoadMaster

Neither was named

8 of 14 modelsThe answer made no first choice from these two in this category.
Grok 4.20HAProxy alternatives: AWS Elastic Load Balancing (ELB) – ALB/NLB, Cloudflare Load Balancing, Loadbalancer.org Enterprise ADC, NGINX, Progress Kemp LoadMaster
Mistral SmallNGINX alternatives: Citrix ADC, F5 BIG-IP, HAProxy, Kemp LoadMaster, Loadbalancer.org Enterprise ADC
DeepSeek V4 FlashHAProxy, Progress Kemp LoadMaster alternatives: NGINX
Llama 4 MaverickNGINX alternatives: Citrix ADC, F5 BIG-IP, HAProxy, Kemp LoadMaster
Qwen 3.7 FlashNGINX alternatives: Application Load Balancer, HAProxy
Kimi K2Kemp LoadMaster alternatives: HAProxy
GLM 4.7 FlashXProgress Kemp LoadMaster alternatives: Cloudflare Load Balancing, HAProxy, NGINX
GPT-6 LunaApplication Load Balancer alternatives: Application Gateway, External Application Load Balancer, Front Door, Network Load Balancer

Bold names in an answer are the products the judge labeled a first choice; a model naming several gives each of them that label. The full answer text for every row is in the record.

By buyer segment

The same question asked on behalf of a different buyer. Each standing is computed within its segment and they are never added together. The figures above are the mid-market standing, which is the one the category orders by.
Small business
AWS Elastic Load Balancing leads by seven points.
AWS Elastic Load Balancing14%#2 of 14
AWS Application Load Balancer7%#5 of 14
The full small business standing →
Mid-marketThe figures above
Level: the same share of first choices.
AWS Elastic Load Balancing4%#5 of 16
AWS Application Load Balancer4%#7 of 16
The full mid-market standing →
Enterprise
AWS Elastic Load Balancing leads by three points.
AWS Elastic Load Balancing5%#5 of 16
AWS Application Load Balancer2%#12 of 16
The full enterprise standing →

What the models said about AWS Elastic Load Balancing

Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of seven in this category shown.

“Internet-facing AWS ALB/NLB or similar cloud LBs when they should be internal: A very common misconfiguration exposes backend services publicly.” Grok 4.20 · negative prompt · soft negative
“may be overkill unless you're already using those cloud platforms” DeepSeek V4 Flash · budget prompt · soft negative
“Companies fully committed to AWS (but creates vendor lock-in)” DeepSeek V4 Flash · direct prompt · soft negative
“Fully in AWS/Azure/GCP: Stick to native cloud load balancers (AWS ALB/NLB, Azure ALB, GCP Cloud LB). It minimizes overhead” Gemini 3.5 Flash · scale prompt · first choice
“1 | AWS Elastic Load Balancing (ALB/NLB/GWLB) | Cloud-native (AWS) | AWS-centric apps, microservices, containers” Grok 4.20 · comparative prompt · first choice
“often recommended as the top choice for small businesses because it offers a free tier” Mistral Small · budget prompt · first choice

What the models said about AWS Application Load Balancer

Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Five of six in this category shown.

“AWS ALB is unsuitable for workloads requiring L4 forwarding, ultra-low-latency pass-through, or non-HTTP protocols; use NLB or the appropriate L4 service instead.” Perplexity Sonar · negative prompt · soft negative
“ALB is not the right choice when the workload is non-HTTP (use NLB)” Muse Glimmer 30B · negative prompt · soft negative
“I'd recommend starting with AWS ALB or Azure Load Balancer (depending on your cloud provider)” Claude Haiku 4.5 · direct prompt · first choice
“AWS-centric company: AWS Application Load Balancer for web apps” GPT-5.4 mini · direct prompt · first choice
“Cloud-first, mostly HTTP(S) APIs, limited ops staff | AWS ALB, Azure Application Gateway, Google Cloud Load Balancing” MiniMax M2.5 · direct prompt · alternative
Also compared

Comparisons are drawn for the top eight products in each category, each against each. The output is the models' output; nothing here is a recommendation by the index.