Two of fourteen models named Site24x7 first on the direct prompt; zero named Prometheus. Site24x7 was named by twelve of the fourteen models and Prometheus by thirteen and Site24x7 carries 27 labels and Prometheus 31, so the shares are not directly comparable.
Named in eleven categories this edition.
Named in nine 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 infrastructure monitoring page.
| Model | Direct | Paraphrase | Comparative | Budget-constrained | Scale-constrained | Negative |
|---|---|---|---|---|---|---|
| Claude Haiku 4.5 | ||||||
| GPT-5.4 mini | ||||||
| Gemini 3.5 Flash | ||||||
| Perplexity Sonar | ||||||
| Grok 4.20 | ||||||
| Mistral Small | ||||||
| DeepSeek V4 Flash | ||||||
| Llama 4 Maverick | ||||||
| Qwen 3.7 Flash | ||||||
| Kimi K2 | ||||||
| GLM 4.7 FlashX | ||||||
| MiniMax M2.5 | ||||||
| GPT-6 Luna | ||||||
| Muse Glimmer 30B |
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.
No label in this category carried a quote.
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Three of three in this category shown.
“Open-source like Zabbix/Prometheus + Grafana work if you have in-house talent for maintenance, but they add operational burden.” Grok 4.20 · paraphrase prompt · soft negative
“Don't expose Prometheus, Alertmanager, exporters, or their metrics and debugging endpoints directly to the public internet.” GPT-6 Luna · negative prompt · soft negative
“Kubernetes & Cloud-Native (Budget Aware) | Prometheus + Grafana | Industry standard, native Kubernetes support, highly customizable.” Gemini 3.5 Flash · comparative prompt · first choice
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.