Meta just dropped Llama 4, and it's not one model — it's two: Scout and Maverick. A dual-pronged strategy that says a lot about where open-source AI is headed.
Scout: The Efficient Workhorse
Scout is built for deployment. Smaller footprint, lower latency, optimized for on-device and edge inference. Think: the model you embed in your product without worrying about GPU costs.
Maverick: The Performance Beast
Maverick goes head-to-head with GPT-4-level models. Same open-source philosophy, but with beefed-up architecture. Meta claims it matches or beats GPT-4 Turbo on several reasoning benchmarks.
Why Two Models?
Smart move. OpenAI and Anthropic each sell one giant model. Meta sells two calibrated to different use cases. Developers get: Scout for production (cheap, fast) + Maverick for exploration (powerful, research-grade).
The Open-Source Layer
Both models are Apache 2.0. Full weights, no restrictions. This is Meta doubling down on their bet: commoditize the AI layer, profit from the platform layer (Instagram, WhatsApp, Quest).
What It Means For Developers
You now have an alternative that's truly open — not "open weights with a usage policy," but Apache 2.0 open. Build on it, fine-tune it, commercialize it. No API billing, no rate limits, no vendor lock-in.
The gap between open-source and proprietary is closing faster than most enterprise buyers realize.
Full analysis on my blog. New AI industry breakdowns daily.
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