# Meta Robyn: how AI models rank it, October 2026

GTM AI Recommendation Index, October 2026 Edition. Named in 23 judge labels across 1 categories by 9 of 14 models. Page: https://gtm-ai-index.com/vendors/meta-robyn/

## Standing by category

| Category | Share | Rank | Negative rate | Labels |
|---|---|---|---|---|
| Attribution and marketing mix modeling | 0% | 23 | 17% | 23 |

## What the models said for it

- "open-source MMM tools like Meta's Robyn or Google's Meridian are increasingly attractive due to their transparency and cost-effectiveness" (Mistral Small, Attribution & MMM)
- "Meta Robyn as a close alternative: Facebook's free open-source MMM (R/Python). Similar power, large community" (Grok 4.1 Fast, Attribution & MMM)
- "Meta describes it as an experimental project; it is a framework to operate, not a turnkey managed service" (GPT-6 Luna, Attribution & MMM)
- "Look instead for platforms built on open-source frameworks (like Meta’s Robyn or Google’s LightweightMMM)" (Gemini 3.5 Flash, Attribution & MMM)

## And against it

- "requires meaningful technical capability to run with R experience, and is built primarily around digital and direct response data" (Claude Haiku 4.5, Attribution & MMM)
- "Meta Robyn if you need a managed, push-button answer. It's an open-source MMM package, so your team needs the skill and time" (GPT-6 Luna, Attribution & MMM)
- "rarely have full-time data scientists to manage open-source MMM code (like Google Meridian or Meta Robyn)" (Gemini 3.5 Flash, Attribution & MMM)
- "require dedicated data scientists to clean data, build pipelines, validate, and maintain the models" (Gemini 3.5 Flash, Attribution & MMM)

## Movement since September 2026

Floor: 11 points of share, measured on the calibration repeat. A larger change is movement; a smaller one is noise.

- Attribution and marketing mix modeling: 1% to 0%, −1. Inside the floor by 10 points · rank 16 → 23 of 123.

## The company

Meta Platforms; https://www.meta.com/; Menlo Park, United States; founded 2004; about 58,604 employees (2020); public, META on Nasdaq. From Wikidata, fetched 2026-09-14.

## Record

- Method: https://gtm-ai-index.com/methodology/
- Raw judge labels and full responses: https://gtm-ai-index.com/data/
- License: CC BY 4.0. Cite as GTM AI Recommendation Index, October 2026 Edition, gtm-ai-index.com.