Zero of fourteen models named Better Stack first on the direct prompt; zero named Grafana Cloud Logs. Better Stack was named by ten of the fourteen models and Grafana Cloud Logs by eight and Better Stack carries 19 labels and Grafana Cloud Logs 16, so the shares are not directly comparable.
Named in eight categories this edition.
Named in one category 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 log management 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. Four of five in this category shown.
“Grafana Cloud Logs, if you want one simple per-GB price. Its bill can depend on processed, written, retained” GPT-6 Luna · negative prompt · soft negative
“For most budget-conscious small companies, I'd start with Grafana Cloud Logs.” GPT-6 Luna · budget prompt · first choice
“For startups or small tech teams: Start with Axiom or Grafana Cloud.” Gemini 3.5 Flash · budget prompt · first choice
“Grafana Loki + Grafana Cloud (Best Overall Value)” DeepSeek V4 Flash · paraphrase 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.