One of fourteen models named Mixpanel first on the direct prompt; zero named Plausible Analytics. Both were named by all fourteen models and Mixpanel carries 39 labels and Plausible Analytics 46, so the shares are not directly comparable.
San Francisco, United States, founded 2009. Named in ten categories this edition.
Tartu, Estonia, founded 2018. Named in three 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 web analytics 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 four in this category shown.
“Privacy-oriented tools like Plausible and Matomo are often chosen because they emphasize data minimization, fewer cookies, and more control.” GPT-5.4 mini · negative prompt · first choice
“Plausible or Pirsch: Lightweight, open-source, cookieless, and EU-hosted for GDPR compliance.” Grok 4.20 · negative prompt · first choice
“alternatives like Plausible Analytics, Fathom, and Matomo have driven significant adoption” Claude Haiku 4.5 · negative 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.