Top 10 Global AI “Models” by Monthly Usage (What We Can Actually Measure in 2026)
When people say “top AI models by usage,” they usually mean user-facing AI products (ChatGPT, Gemini, Meta AI, Copilot, etc.).
That’s because true foundation-model usage (tokens served per model, unique users per underlying model family) is mostly private. What we can track is a mix of:
company-reported MAU/WAU
app MAU rankings (mobile)
web traffic share / visits (as a proxy when MAU isn’t disclosed)
So this list is the best public, defensible estimate of “who’s biggest” by monthly usage as of late-2025 / early-2026, with notes on what the metric actually means.
The top 10 (with the most defensible public metrics)
| Rank | AI product (proxy for “model”) | Best public monthly usage signal | Notes |
|---|---|---|---|
| 1 | ChatGPT (OpenAI) Chat | Very large weekly active user count reported publicly (often used as a proxy for MAU scale). | Exact MAU isn’t always disclosed; WAU is frequently cited instead. |
| 2 | Meta AI (Meta / Llama) Embedded | Large monthly active user figures reported across Meta apps (WhatsApp/Instagram/Facebook/Messenger). | Usage is aggregated across multiple surfaces, not a single standalone app. |
| 3 | Gemini app (Google) Chat | Standalone app monthly users reported by Google (varies by reporting period). | “Gemini” usage can also include integrations across Google products. |
| 4 | Microsoft Copilot Suite | Monthly active user numbers and “Copilot family” adoption figures reported by Microsoft. | Definitions can vary (consumer vs M365 vs Windows vs GitHub). |
| 5 | DeepSeek Chat | Public MAU estimates from app analytics/market research (can vary widely). | Adoption is geography-dependent; estimates differ by methodology. |
| 6 | Perplexity AI Search | Active user estimates + web traffic proxies (visits/unique visitors) used when MAU isn’t official. | Numbers vary by whether sources measure “visits” vs “active users.” |
| 7 | Grok (X / xAI) Chat | Monthly users/traffic estimates tied to X distribution and app usage. | Access and pricing changes can swing usage quickly. |
| 8 | Claude (Anthropic) Chat | User/traffic estimates from public reports and analytics sources. | MAU is less consistently “official” than some big-platform assistants. |
| 9 | Character.AI Entertainment | MAU estimates + extremely high monthly visits as an engagement proxy. | Usage is often time-on-app heavy (roleplay/companions). |
| 10 | Midjourney Image Gen | Community size and active-user estimates (Discord-based usage is often cited). | Not a chat assistant; MAU is rarely reported directly. |
Why this list isn’t “pure foundation models”
A foundation model (GPT-4.x, Gemini 3.x, Claude 3.x/4.x, Llama, etc.) is often served through many distribution surfaces:
a standalone app
API partners
embedded assistants (OS, browser, enterprise suites)
third-party products and wrappers
So “monthly usage” is typically reported at the product layer (ChatGPT, Gemini app, Meta AI, Copilot), not at the raw model layer.
How to use this list in a practical business way (abZ Global angle)
If you’re building web apps or e-commerce, the “top 10” matters less than where users already are:
ChatGPT + Gemini + Meta AI dominate consumer mindshare → best for content discovery, prompts, and “AI search” style journeys.
Copilot dominates embedded enterprise workflows → best for B2B tooling, docs, spreadsheets, internal knowledge.
Perplexity is “AI search-first” → strong for citation-driven exploration and research UX patterns.
Character.AI + Midjourney show how big “non-work” use is → entertainment and creative tooling remain massive.
Important caveats (so you don’t repeat bad numbers)
MAU vs visitors vs app MAU vs WAU: these are not interchangeable.
“Across products” (Meta AI, Copilot family) can inflate numbers vs a single app.
Geography/policy (DeepSeek, Grok) can shift usage sharply.
Many “stats sites” mix sources; prefer company filings / earnings / reputable reporting when available (Meta, Microsoft, Google).