Two of fourteen models named AWS Elastic Load Balancing first on the direct prompt; zero named Traefik. AWS Elastic Load Balancing was named by thirteen of the fourteen models and Traefik by ten and AWS Elastic Load Balancing carries 33 labels and Traefik 21, so the shares are not directly comparable.
Named in one category this edition.
Named in two categories this edition.
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.
Across every category in the October 2026 Edition, AWS Elastic Load Balancing and Traefik were named in the same answer twenty-four times, of the 93 answers naming AWS Elastic Load Balancing and the 55 naming Traefik. In those answers Traefik took the first choice two times and AWS Elastic Load Balancing eight.
| Model | DirectAE | ParaphraseAE | ComparativeAE | Budget-constrainedAE | Scale-constrainedAE | NegativeAE |
|---|---|---|---|---|---|---|
| Claude Haiku 4.5 | AE | AE | AE | |||
| GPT-5.4 mini | ||||||
| Gemini 3.5 Flash | AE | AE | AE | |||
| Perplexity Sonar | AE | |||||
| Grok 4.1 Fast | AE | AE | AE | AE | ||
| Mistral Small | AE | AE | ||||
| DeepSeek V4 Flash | AE | AE | ||||
| Llama 4 Maverick | ||||||
| Qwen 3.7 Flash | AE | |||||
| Kimi K2 | AE | AE | ||||
| GLM 4.7 FlashX | AE | |||||
| MiniMax M2.5 | AE | AE | AE | |||
| GPT-6 Luna | AE | |||||
| Muse Glimmer 30B | AE |
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.
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
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Three of four in this category shown.
“For most small businesses today, Traefik offers the best balance of cost (free), ease of management (auto-discovery), and functionality” Qwen 3.7 Flash · budget prompt · first choice
“Cloud-native champion - designed for containers ... Kubernetes/container-heavy | Traefik or NGINX Ingress” Kimi K2 · comparative prompt · first choice
“If you run Docker/Kubernetes: Go with Traefik. It integrates seamlessly and reduces operational overhead.” Kimi K2 · budget prompt · alternative
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.