Nine of fourteen models named Dreamdata first on the direct prompt; zero named Google Meridian. Dreamdata was named by fourteen of the fourteen models and Google Meridian by thirteen and Dreamdata carries 38 labels and Google Meridian 34, so the shares are not directly comparable.
Named in six categories this edition.
By Google, Mountain View, California, United States, founded 1998. 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 attribution and marketing mix modeling page.
Across every category in the October 2026 Edition, Dreamdata and Google Meridian were named in the same answer thirty-six times, of the 125 answers naming Dreamdata and the 89 naming Google Meridian. In those answers Google Meridian took the first choice two times and Dreamdata fifteen.
| 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. Six of six in this category shown.
“"losing head-to-head comparisons" against competitors, with users actively seeking alternatives” DeepSeek V4 Flash · negative prompt · soft negative
“What to Avoid on a Tight Budget - Dreamdata starts at ~$750/month” Kimi K2 · budget prompt · soft negative
“but these are better fits when your budget is no longer very limited” Perplexity Sonar · budget prompt · soft negative
“Dreamdata or Factors.ai for attribution, and Google Meridian or Northbeam for MMM, would be the most balanced and effective choices.” Mistral Small · paraphrase prompt · first choice
“Attribution: Dreamdata if your buying cycles are long, account-based, and you want B2B-specific multi-touch attribution tied to revenue” GPT-5.4 mini · paraphrase prompt · first choice
“the strongest overall choice is usually Dreamdata if your priority is B2B revenue attribution and customer-journey analysis” Perplexity Sonar · direct prompt · first choice
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of eight in this category shown.
“Free, open-source libraries like Google Meridian or Meta Robyn require dedicated data scientists... a SaaS platform with a managed service component is almost always the right choice” Gemini 3.5 Flash · scale prompt · soft negative
“Mid-market companies rarely have full-time data scientists to manage open-source MMM code (like Google Meridian or Meta Robyn)” Gemini 3.5 Flash · direct prompt · soft negative
“Google Meridian if you lack data or modeling support. Meridian is open source, not a turnkey measurement service.” GPT-6 Luna · negative prompt · soft negative
“open-source MMM tools like Meta's Robyn or Google's Meridian are increasingly attractive due to their transparency and cost-effectiveness” Mistral Small · negative prompt · first choice
“Open-source Bayesian MMM, native Google Ads integration... Successor to LightweightMMM; free, transparent code” GLM 4.7 FlashX · comparative prompt · first choice
“Google's Meridian is a Bayesian MMM framework released openly for anyone to use—no licensing fees.” Grok 4.20 · budget 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.