Llama 4 Scout

Meta released the Llama 4 family in April 2025, and by mid-2026 these models have settled into clear roles. Llama 4 Scout is the long-context specialist with a 10 million token window and the cheapest per-token cost, while Llama 4 Maverick is the frontier-quality generalist that beats GPT-4o on several benchmarks. Both share the same 17B active parameters via Mixture-of-Experts architecture, but they’re built for very different jobs. Here’s exactly when to use each one, with real pricing, benchmark data, and deployment strategies. ...

Llama 4 Scout is Meta’s open-weight model with a 10 million token context window — the largest of any open-weight model released in 2026. At roughly 4 tokens per line of code, that covers approximately 2.5 million lines of code in a single prompt. In practice this means you can load an entire mid-size production repository — including tests, docs, and config — without chunking, vector databases, or retrieval pipelines. ...