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Index › Network and edge › Load balancers › Progress Kemp LoadMaster vs AWS Elastic Load Balancing
Load balancers · October 2026 Edition

Progress Kemp LoadMaster vs AWS Elastic Load Balancing

Five of fourteen models named Progress Kemp LoadMaster first on the direct prompt; two named AWS Elastic Load Balancing. Progress Kemp LoadMaster was named by ten of the fourteen models and AWS Elastic Load Balancing by thirteen and Progress Kemp LoadMaster carries 20 labels and AWS Elastic Load Balancing 33, so the shares are not directly comparable.

Progress Kemp LoadMaster

accepted challenger

Named in one category this edition.

AWS Elastic Load Balancing

accepted challenger

Named in one category this edition.

First-choice share27%6%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate0%12%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#2#4A position in a field of 13; printed, not drawn.
Labels2033A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, Progress Kemp LoadMaster reading right to left. Rank and label count are printed, not drawn.HAProxy was named alongside these two in ten of the fourteen direct answers. HAProxy vs Progress Kemp LoadMaster · HAProxy vs AWS Elastic Load Balancing · Progress Kemp LoadMaster vs NGINX

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.
Progress Kemp LoadMasterFirst choices, of fourteen modelsAWS Elastic Load Balancing
Direct52
Paraphrase90
Comparative03
Budget-constrained012 against AWS Elastic Load Balancing
Scale-constrained00
Negative022 against AWS Elastic Load Balancing
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 Progress Kemp LoadMaster and AWS Elastic Load Balancing stood in it.
ModelDirectPKAEParaphrasePKAEComparativePKAEBudget-constrainedPKAEScale-constrainedPKAENegativePKAE
Claude Haiku 4.5AEAEAE
GPT-5.4 mini
Gemini 3.5 FlashPKAEPKAEAE
Perplexity SonarAE
Grok 4.1 FastPKPKAEAEAEAE
Mistral SmallPKAEAE
DeepSeek V4 FlashPKPKAEPKAE
Llama 4 MaverickPK
Qwen 3.7 FlashAEPK
Kimi K2PKPKAEAE
GLM 4.7 FlashXPKPKAE
MiniMax M2.5PKAEPKAEAE
GPT-6 LunaAE
Muse Glimmer 30BPKAEPK
PK Progress Kemp LoadMasterAE AWS Elastic Load BalancingPK first choicePK named as an alternativePK argued againstblank: not namedEach cell is one answer, Progress Kemp LoadMaster on the left and AWS Elastic Load Balancing on the right.

The direct prompt

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

Progress Kemp LoadMaster first, AWS Elastic Load Balancing an alternative

5 of 14 modelsAWS Elastic Load Balancing was named in the answer but not as the choice, or not at all.
DeepSeek V4 FlashProgress Kemp LoadMaster alternatives: AWS Application Load Balancer, Cloudflare Load Balancing, HAProxy, NGINX
Kimi K2HAProxy, Progress Kemp LoadMaster alternatives: F5 NGINX
GLM 4.7 FlashXNGINX, Progress Kemp LoadMaster alternatives: F5 BIG-IP, HAProxy
MiniMax M2.5Progress Kemp LoadMaster alternatives: AWS Elastic Load Balancing, Azure Load Balancer, Cloudflare Load Balancing, GCP Cloud Load Balancing, NGINX
Muse Glimmer 30BProgress Kemp LoadMaster alternatives: AWS Elastic Load Balancing, Azure Load Balancer, Cloudflare Load Balancing, HAProxy, NGINX

AWS Elastic Load Balancing first, Progress Kemp LoadMaster not the choice

2 of 14 modelsProgress Kemp LoadMaster was named in the answer but not as the choice, or not at all.
Claude Haiku 4.5AWS Elastic Load Balancing, Azure Load Balancer, NGINX alternatives: Citrix ADC, F5, HAProxy
Qwen 3.7 FlashAWS Elastic Load Balancing, Azure Application Gateway, NGINX alternatives: Cloudflare Load Balancing, HAProxy

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 Elastic Load Balancing, Azure Application Gateway, HAProxy, NGINX, Progress Kemp LoadMaster
Perplexity SonarHAProxy alternatives: AWS Elastic Load Balancing, Azure Application Gateway
Grok 4.1 FastHAProxy, NGINX alternatives: AWS ALB, Azure Load Balancer, Cloudflare Load Balancing, GCP Cloud Load Balancing, Progress Kemp LoadMaster
Mistral SmallCloudflare Load Balancing alternatives: HAProxy, Progress Kemp LoadMaster, VMware Avi Load Balancer

Neither was named

3 of 14 modelsThe answer made no first choice from these two in this category.
GPT-5.4 miniApplication Load Balancer alternatives: Azure Load Balancer, Google Cloud's Application Load Balancer, Network Load Balancer
Llama 4 Maverickno first choice
GPT-6 LunaAWS Application Load Balancer alternatives: Azure Application Gateway, Azure Load Balancer, Cloudflare Load Balancing, Google Cloud Application Load Balancer, Google Cloud 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 one point.
AWS Elastic Load Balancing10%#4 of 13
Progress Kemp LoadMaster9%#– of 13
The full small business standing →
Mid-marketThe figures above
The order flips: Progress Kemp LoadMaster leads at mid-market.
Progress Kemp LoadMaster27%#2 of 13
AWS Elastic Load Balancing6%#4 of 13
The full mid-market standing →
Enterprise
Progress Kemp LoadMaster leads by four points.
Progress Kemp LoadMaster4%#– of 10
AWS Elastic Load Balancing0%#9 of 10
The full enterprise standing →

What the models said about Progress Kemp LoadMaster

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

“Best All-Rounder (Hybrid/Virtual/On-Premises): Progress Kemp LoadMaster ... is widely considered the gold standard for the mid-market.” Gemini 3.5 Flash · paraphrase prompt · first choice
“I'd recommend Progress Kemp LoadMaster as the best application delivery controller for a mid-sized B2B company” GLM 4.7 FlashX · paraphrase prompt · first choice
“Progress Kemp LoadMaster (now part of Progress) is the one I would suggest as the default starting point.” MiniMax M2.5 · paraphrase prompt · first choice

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 eight in this category shown.

“Avoid cloud-native load balancers (like AWS ALB/ELB) if your budget is tight” Kimi K2 · budget prompt · hard negative
“Cloud-native load balancers (AWS ELB, Azure LB, GCP LB) excel in their ecosystems but may lack deep packet inspection” MiniMax M2.5 · negative prompt · soft negative
“Relies on CloudWatch; tuning timeouts/limits needed.” Grok 4.1 Fast · negative prompt · soft negative
“Cloud-native load balancers (AWS ALB, Azure LB) are often the best fit - they scale automatically, integrate with your infrastructure, and have predictable costs” Claude Haiku 4.5 · direct prompt · first choice
“For very small budgets: Start with cloud-native load balancers (AWS ALB, etc.) as they eliminate upfront costs” MiniMax M2.5 · budget prompt · first choice
“Prefer managed cloud-native: AWS ALB/NLB, GCP Premium/Global, Azure Standard—high reliability scores” Grok 4.1 Fast · negative prompt · first choice
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.