Zero of fourteen models named Grafana Cloud first on the direct prompt; zero named SigNoz. Grafana Cloud was named by thirteen of the fourteen models and SigNoz by eleven and Grafana Cloud carries 36 labels and SigNoz 23, so the shares are not directly comparable.
Named in five categories this edition.
Named in eight 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 application performance monitoring page.
Across every category in the November 2026 Edition, Grafana Cloud and SigNoz were named in the same answer sixty-eight times, of the 216 answers naming Grafana Cloud and the 211 naming SigNoz. In those answers SigNoz took the first choice seven times and Grafana Cloud thirteen.
| 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.
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Two of two in this category shown.
“self-hosted solutions like Grafana (requiring significant maintenance effort)” Qwen 3.7 Flash · paraphrase prompt · soft negative
“Start with Grafana Cloud's free tier or New Relic's free tier to get started at $0 cost.” DeepSeek V4 Flash · budget prompt · first choice
No label in this category carried a quote.
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.