Where Does Consumer AI Stand at the End of 2025?

Analysis of the consumer AI competitive landscape showing ChatGPT's massive lead with 800-900M weekly users versus Gemini at 35-40% of that scale. Only 9% of consumers pay for multiple LLM products, suggesting winner-take-most dynamics. Gemini is growing desktop users 155% YoY while ChatGPT grows only 23%, indicating rapid market shifts.

• •Less than 10% of ChatGPT users visit competing LLM providers, showing strong lock-in
• •ChatGPT dominates with 800-900M weekly active users; Gemini has 35% web scale, 40% mobile
• •Claude, Grok, Perplexity trail at 8-10% of ChatGPT's usage
• •Gemini accelerating growth at 155% YoY despite scale, while ChatGPT slows to 23%
• •Only 9% of consumers pay for more than one major LLM product

Deep dive into 2025's most viral model launches, particularly in image and video generation. OpenAI's Ghibli moment and Sora, Google's Veo and Nano Banana dominated consumer attention. Major advances in realism, reasoning within images/video, and multi-input capabilities transformed creative workflows beyond just aesthetic improvements.

• •OpenAI's ChatGPT-4o Ghibli moment and Sora 2 went viral; Google's Veo 3 and Nano Banana Pro achieved comparable or greater virality
• •Image models now handle complex reasoning: market maps, infographics, multi-image inputs with text
• •Video models achieved realistic physics, proper background movement, audio integration
• •Nano Banana Pro's search integration enables accurate product photography and historical references
• •OpenAI kept features in ChatGPT; Google launched standalone products for custom interfaces

Critical analysis of how small product decisions dramatically impact user behavior. ChatGPT's trending templates and character consistency features drive engagement, while Gemini's blank screen approach creates friction. The discussion reveals that product sensibility and execution matter more than model capabilities for mainstream adoption.

• •ChatGPT's TikTok-style trending templates reduce friction vs Gemini's blank screen
• •Character persistence across images enables storyboarding and repeat generation
• •Application layer startups (Cria, Hydra, Higgs) popularized template formats before ChatGPT adopted them
• •ChatGPT took years to launch dedicated image interface despite having models
• •Product execution separates successful launches from failed ones regardless of model quality

Discussion of underrated product launches including OpenAI's Pulse productivity features and personal connectors, plus Perplexity's Comet browser. These represent new primitives for proactive AI assistance and agentic workflows, though execution challenges limit current adoption. Comet's workflow automation achieved higher sustained traffic than ChatGPT's Atlas browser.

• •Pulse aims for proactive productivity nudges given ChatGPT's 25x weekly usage frequency
• •Personal connectors (calendar, email, documents) enable cross-tool summarization but reliability issues persist
• •Perplexity Comet browser excels at agentic workflows and repeatable tasks on preset schedules
• •Comet launch spike and sustained traffic exceeded ChatGPT's Atlas despite smaller distribution
• •These features target prosumer segment but need better execution for mainstream adoption

Analysis of why OpenAI's social features (group chats, Sora 2 as social app) haven't succeeded. The core insight: AI products solve 'help me' problems while social products address 'see me/connect me' needs - fundamentally different emotional drivers. Sora 2 works as a creator tool but fails as a consumption platform, similar to CapCut rather than TikTok.

• •ChatGPT's core value is 'help me be better' vs social's 'see me/connect with others' - incompatible motivations
• •Group chat works for 2-3 people planning tasks but doesn't scale as social product
• •Sora 2 succeeded as creator tool (50%+ of AI video on feeds) but failed as social consumption app
• •AI-generated content lacks status game dynamics since it's not 'real' representation of creator
• •Humor-based status game around prompting could be viable direction but requires iteration

Evaluation of how challenger companies positioned themselves in 2025. Claude owns technical users with opinionated features (MCP, skills, artifacts) but struggles with mainstream accessibility. Meta's SAM 3 series excels at segmentation. Grok shows steepest improvement curve in image/video with aggressive template-driven approach and entertainment focus.

• •Claude replaced ChatGPT for technical users but features too complex for mainstream (3x more teens use Character AI than Claude)
• •Claude launched file creation, skills, artifacts first but buried in settings; needs simpler UX
• •Meta's strongest models are SAM 3 (segment anything for video/image/audio) for developers, not consumers
• •Grok went from no image/video models to competitive in 6 months with fastest iteration speed
• •Grok's template-driven approach and X distribution targets entertainment use cases vs productivity

Forward-looking predictions emphasizing ChatGPT's enterprise push (8-9x YoY growth) driving consumer adoption, the critical importance of their apps SDK for workflow automation, and the convergence toward 'anything in, anything out' multimodal models. Templates and stylistic differentiation will matter more than raw capabilities as models commoditize.

• •ChatGPT enterprise usage up 8-9x YoY; workplace adoption will drive consumer usage as people use one LLM
• •Apps SDK/directory will be huge for both consumer and enterprise, enabling cross-tool workflows
• •Multimodal convergence: combining text, image, video models into unified 'anything to anything' systems
• •Templates and styles (like Ghibli, TikTok trends) drive adoption more than model capability improvements
• •Cost reductions will enable video-first products within lab models; repurposing teams should integrate templates

Strong case for startup opportunities: big labs consistently fail at opinionated consumer products (Pulse, Atlas, Sora social, Google's 20+ experiments). Only text-in/text-out is dominated by ChatGPT. Startups win through multi-model strategies, power user focus, and creative input/output combinations. Consumer AI now shows 100%+ revenue retention through usage-based pricing.

• •Big labs launched dozens of consumer products in 2025; almost all failed except core chat interfaces
• •Labs lack incentive structure for opinionated products (promo committees favor safe, incremental features)
• •Startups can be multi-model while labs are first-party only; critical for power users who drive monetization
• •Text-in/text-out dominated by ChatGPT, but creative angles with different modalities remain open
• •Consumer AI achieving 100%+ revenue retention through usage-based pricing beyond subscriptions - unprecedented

Discussion of compute bottlenecks forcing labs to choose between training, inference, and entertainment vs coding use cases. XAI uniquely unconstrained. Product recommendations include Pomelli for multimodal agents, Krea for multi-model creative work, ElevenLabs Reader for audio consumption, Gamma for presentations, and Granola for note-taking.

• •All labs except XAI are compute-constrained, forcing tradeoffs between training and inference
• •Viral entertainment features (Nano Banana) can slow down core LLM development
• •Pomelli (Google Labs) demonstrates future of agents + image generation for ad campaigns
• •Krea enables using best model per modality with saved elements/characters for consistency
• •Models now enable scalable consumer apps; 2026 expected to be breakthrough year for consumer builders