Table of Contents
Explore the top 100 Generative AI products defining 2025—how they’re ranked, who’s winning, what surprised us, and where the industry is heading next.
Key Takeaways
- The GenAI 100 ranks 50 web and 50 mobile products by usage and revenue, spotlighting market traction, not just hype.
- 17 newcomers—including DeepSeek, Hyo, and Bolt—redefined the leaderboard, signaling rapid change and rising new categories.
- Companion AI apps dominate consumer attention, while AI video tools are reaching critical product-market readiness.
- "Vibe coding" platforms like Lovable and Bolt show demand for frictionless creation—even among experienced devs.
- DeepSeek’s rise from launch to #2 in just 10 days demonstrates massive global appetite for novel, open-access reasoning models.
- There's only a 40% overlap between the most used and most profitable apps—niche tools often earn more per user.
- Emerging tools like Deep Research, Korea, and Operator offer glimpses into the next generation of multimodal, agentic interfaces.
- Long-term winners aren’t just technically strong—they deliver sticky experiences, real value, and rapid iteration.
How the GenAI 100 Works—and Why It Matters
- The report tracks real consumer behavior across platforms. Web rankings use SimilarWeb monthly visits; mobile rankings use Sensor Tower MAUs and revenue.
- Products must be generative-AI-first to qualify. This isn't about big brands adding AI features—it’s about AI-native experiences.
- For the first time, the 2025 list includes top mobile products by revenue, revealing a split between popularity and profitability.
- The Brink List tracks “almost-made-it” products, showcasing fast risers like Lovable, Korea, and Otter.
- Remarkably, 16 companies have appeared on all four editions of the list—evidence of early dominance and brand staying power.
The GenAI 100 isn’t speculative—it captures what millions of people are actually using, paying for, and coming back to.
The Consumer AI Landscape: From ChatGPT to DeepSeek
- ChatGPT still leads—but growth was stagnant from Feb 2023 to Feb 2024. The surge came only after new features like voice mode, Canvas, and advanced reasoning launched.
- DeepSeek emerged like a rocket: within 10 days of launch, it became the #2 web product; within 5 days on mobile, it ranked #14—despite no prior market presence.
- Key factors behind DeepSeek’s success:
- Free access to top-tier reasoning models
- Real-time chain-of-thought rendering
- High usability in markets restricted from ChatGPT (e.g., China)
- Day-30 retention: DeepSeek = 7%, ChatGPT = 9%—a surprisingly close margin, indicating user stickiness from the outset.
This isn’t the end of ChatGPT dominance—but DeepSeek’s viral adoption proves the “winner-takes-all” assumption was premature.
AI Video Is No Longer a Toy—It’s a Platform Shift
- Three AI video newcomers made the list: Hyo, Clling (China-based), and Sora (OpenAI).
- Chinese models stunned reviewers with realistic, promptable video quality—despite limited capital and public visibility.
- AI video is maturing rapidly:
- Prompts now include camera angles, cinematography terms, and animation styles
- Tools can stitch image models, upscalers, and video motion into single pipelines
- Google’s upcoming V2 model is expected to push boundaries further—possibly enabling multi-minute generation.
Video is shifting from novelty to infrastructure. Creative control, multimodality, and specificity are now table stakes.
Rise of Companion AI: Intimacy as a Killer Use Case
- Companion bots—especially those with NSFW or fanfiction themes—ranked shockingly high. Three made the top 10.
- These aren’t just chatbots. They’re identity-shaping, emotionally resonant, and persistent across use sessions.
- Multimodal voice features (as seen in Character AI and Grok) add immersion, but most companions are still text-first.
- There’s massive latent demand for AI friends, romantic partners, and fanfic role-play—particularly among Gen Z audiences.
- Notably, many top-ranking sites and apps in this category see more creation traffic (custom characters, interactions) than consumption traffic.
AI companionship isn’t fringe—it’s foundational. Emotional AI is now a legitimate product category with sustained engagement and growth.
Vibe Coding and the Dawn of DIY Software
- Bolt and Lovable made the top mobile list by letting anyone build working apps from text prompts—no coding needed.
- Ironically, many users are technical, using these tools for fast prototyping and exporting editable code.
- This signals two major trends:
- “Disposable software”: apps that exist for a weekend or a joke
- “Personal software”: highly specific tools that serve niche but real needs
- These products haven’t yet produced viral hits, but their presence on the list signals untapped creator potential.
Coding is no longer a barrier—it’s a stylistic choice. AI is unlocking product development for millions who never thought they’d build.
Revenue ≠ Reach: What the Monetization Data Reveals
- Only 40% of top-used mobile AI products overlap with top-grossing ones. Smaller audiences often monetize better.
- Categories like photo editing, beauty filters, and productivity AI dominate revenue—even if they’re less buzzy.
- Apps like Otter, Speak, and Captions pull in $100M+ ARR from only 1–2M users. These are not mass apps—they’re power tools.
- Plant ID apps (yes, really) make the list for revenue, showing depth in non-flashy verticals.
- Pricing strategy matters:
- Paid gating boosts per-user revenue
- Indie developers use low-cost ad targeting to grow profitably without VC funding
The AI consumer market rewards depth over breadth. Micro-monetization, not virality, may be the path to sustainability.
Multimodal Futures: What Comes After Text
- AI products are still heavily text-driven. But coming shifts will be driven by:
- Visual reasoning (click, swipe, draw)
- Device interaction (browser agents, file access, mobile-first flows)
- Context-aware interfaces (screen scraping, real-time sensors)
- Early examples:
- Gemini Flash model: sees your screen, yells when you’re distracted
- Operator: completes tasks like bill payment, job posting, or graphic design via browser
- Deep Research: obsessive, internet-scale document analysis
- Developers will shape these primitives into verticalized apps—from meme forensics to business analytics to self-discipline coaches.
The next frontier isn’t another GPT clone. It’s interface evolution—AI that sees, acts, and coexists with your tools and habits.
Product-Led Success: What the Winners Have in Common
- Technological sophistication doesn’t guarantee success. Many world-class researchers fail in consumer markets.
- Product experience, not AI horsepower, defines long-term adoption.
- Winning teams:
- Focus on specific user problems
- Optimize for delight, not complexity
- Use the best model for the job—even if it’s older
- Avoid unnecessary AI bloat when not stable or helpful
- As one observer put it, “Let the data be your guide”—consumer AI is not a theory class, it’s a popularity contest powered by usage curves.
The companies with staying power are shipping fast, learning from the crowd, and solving real-life frustrations—AI is just the engine.
Generative AI in 2025 isn’t about unicorn fantasies or model specs—it’s about products that stick. From video generation and voice companions to disposable apps and multimodal workflows, the landscape is wildly diverse. But the thread uniting every winner is simple: solve something people care about, and do it faster, easier, and more creatively than before.
The future of AI won’t be decided by research labs. It’ll be written by users—and the builders who actually listen to them.
