AI Radar: Meta Llama 4 — Multimodal, Open, With Fine Print

No open ecosystem is more widely deployed than Llama. With its fourth generation, Meta moves to mixture-of-experts and makes the models multimodal from the ground up — a clear leap, but not without fine print.

The Herd at a Glance

• Llama 4 Scout: 17B active parameters across 16 experts, fits on a single H100, and ships with an exceptionally large context window.
• Llama 4 Maverick: also 17B active parameters but 128 experts — the all-rounder that keeps pace with much larger proprietary models.
• Llama 4 Behemoth: at 288B active parameters, Meta's strongest model yet, still in training and intended as a teacher for the smaller variants.
• Natively multimodal: text and image are processed jointly, not bolted on afterward.

The Caveat

Llama is available in the open, but not in the classic open-source sense: it carries a community license with restrictions — for very large providers and in its acceptable-use policy. For European companies, there is the added point that Meta has at times attached regional conditions to the multimodal features. So anyone deploying Llama 4 in production should vet the license as carefully as the model.

Our Take

The fact that Scout fits on a single H100 makes serious open AI accessible to SMEs — that is the good news. The license is the price: affordable, but required reading. We judge models by task — and with Llama, the fine print is part of the task.