Meta's LLaMA 4 Drops with 400B Parameters — Challenges GPT-4 on Every Benchmark

What Is Mixture-of-Experts and Why Does It Matter?

LLaMA 4's 400B flagship uses a Mixture-of-Experts (MoE) architecture — a design where only a fraction of the model's neurons activate for any given token. Think of it as a panel of 64 specialized experts, where a learned router decides which 2 experts are most relevant for each piece of text. The result: a 400B parameter model that only activates roughly 40B parameters per forward pass. This dramatically reduces compute at inference time. Early benchmarks from the community suggest LLaMA 4-400B can run at roughly 18 tokens/second on two A100 80GB GPUs — making it viable for well-resourced university labs, startups, and enterprises without massive data center infrastructure.

LLaMA 4 Model Family at a Glance

• LLaMA 4-8B — CPU-runnable, 4-bit quantized fits on a MacBook M3 Pro; ideal for on-device apps
• LLaMA 4-70B — Single A100 80GB; best open-source mid-size model for most enterprise tasks
• LLaMA 4-400B MoE — 2× A100 recommended; state-of-the-art open-source performance
• 128K token context across all sizes (8K in prior LLaMA 3 variants)
• Multilingual: 35 languages supported, up from 8 in LLaMA 3
• Vision-language variant (LLaMA 4-Vision) supports image+text input for 8B and 70B

The License: What You Can (and Cannot) Do

Meta is releasing LLaMA 4 under the LLaMA 4 Community License, an evolution of the prior agreement. Commercial use is permitted for any company or product with fewer than 700 million monthly active users — a threshold specifically designed to exclude only the largest platforms (Google, Meta itself, ByteDance, etc.). Academic research has no restrictions. You can fine-tune, quantize, and redistribute derivatives as long as they carry the LLaMA 4 name prefix and include the license. Notable restriction: you cannot use LLaMA 4 outputs to train other foundational models without written permission from Meta.

LLaMA 4-400B vs GPT-4o (Benchmark Comparison)