# Metabase vs Cube: which do AI models recommend for embedded analytics, October 2026

IT AI Recommendation Index, October 2026 Edition, Embedded analytics. Two of fourteen models named Metabase first on the direct prompt; zero named Cube. Page: https://it-ai-index.com/it-data/embedded-analytics/metabase-vs-cube/

| | First-choice share | Rank | Negative rate | Labels | Models naming it |
|---|---|---|---|---|---|
| Metabase | 22% | #1 of 19 | 12% | 40 | 14 of 14 |
| Cube | 2% | #6 of 19 | 0% | 20 | 10 of 14 |

## The direct prompt, model by model

- GLM 4.7 FlashX: metabase first (first choices: Metabase) (alternatives: Looker, ThoughtSpot Embedded)
- GPT-6 Luna: metabase first (first choices: Metabase) (alternatives: Looker Embed, Sisense, ThoughtSpot Embedded)
- Claude Haiku 4.5: neither first, one named (first choices: Sisense) (alternatives: Holistics, Looker Embedded, Metabase, Power BI Embedded)
- Gemini 3.5 Flash: neither first, one named (first choices: Omni) (alternatives: Embeddable, Luzmo, Metabase, Qrvey)
- Perplexity Sonar: neither first, one named (first choices: ThoughtSpot Embedded) (alternatives: Cube, Looker, Zoho Analytics)
- Kimi K2: neither first, one named (first choices: Explo) (alternatives: Looker, Metabase, Power BI Embedded, Preset)
- MiniMax M2.5: neither first, one named (first choices: Microsoft Power BI Embedded) (alternatives: Cube, Explo, Grow, Looker, Metabase, Sisense, Tableau Embedded Analytics, ThoughtSpot Embedded)
- GPT-5.4 mini: neither named (first choices: Sisense) (alternatives: Looker, Power BI Embedded, ThoughtSpot Embedded)
- Grok 4.1 Fast: neither named (first choices: Reveal BI) (alternatives: Bold BI, Domo Everywhere, Power BI Embedded, Tableau, Zoho Analytics)
- Mistral Small: neither named (first choices: Explo, Sisense) (alternatives: Microsoft Power BI Embedded, Tableau Embedded Analytics)
- DeepSeek V4 Flash: neither named (first choices: Luzmo) (alternatives: GoodData, Sisense)
- Llama 4 Maverick: neither named (first choices: Reveal BI) (alternatives: Cube.dev, Omni.co, Thinklytics Insights, Zoho)
- Qwen 3.7 Flash: neither named (first choices: Sisense) (alternatives: Looker, Microsoft Power BI Embedded, ThoughtSpot Embedded)
- Muse Glimmer 30B: neither named (first choices: Sisense) (alternatives: Reveal BI, Toucan)

## What the models said about Metabase

- "self-hosted Metabase for embedding (security, performance)" (DeepSeek V4 Flash, negative prompt, hard negative)
- "often cited as the fastest path to a first embedded dashboard but hits limits on serious multi-tenant isolation" (Kimi K2, comparative prompt, soft negative)
- "Deep embedding features gated to paid tiers; multi-tenant isolation weaker than dedicated embedded platforms" (DeepSeek V4 Flash, comparative prompt, soft negative)
- "Metabase (especially with static embeds) and Querio are the top recommendations for companies with limited budgets" (Mistral Small, budget prompt, first choice)
- "the best embedded analytics platform is likely the open-source self-hosted version of Metabase, which is completely free" (Grok 4.1 Fast, budget prompt, first choice)
- "Start with Metabase if you want to test the waters cost-effectively and have engineering resources" (Kimi K2, paraphrase prompt, first choice)

## What the models said about Cube

- "Cube: An industry-standard "headless" semantic layer with an open-source core. It is excellent for high-concurrency, complex multi-tenancy, and has a native AI-agent API." (Gemini 3.5 Flash, scale prompt, first choice)
- "Choose Cube or Omni if you are building a modern SaaS application that needs scalable, highly secure multi-tenancy" (Gemini 3.5 Flash, comparative prompt, first choice)
- "Choose Cube if you need strong multi-tenant isolation and row-level security for SaaS embedding." (Perplexity Sonar, comparative prompt, first choice)

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. Comparisons are drawn for the top eight products in each category. Published under CC BY 4.0; the output is the models' output, and nothing here is a recommendation by the index.