Llama 4 Review: Meta's Free Model Just Closed the Gap with GPT-5
Meta released Llama 4 as open weights. Benchmarks suggest it rivals GPT-5 on most tasks. We tested it for a week. Here's the truth.
Llama 4 is Meta's most ambitious open-source release ever. The flagship 405B parameter model is freely downloadable, and Meta claims it matches GPT-5 on most benchmarks. Is the hype real?
Llama 4 ships in four sizes: Scout (8B), Medium (70B), Maverick (250B Mixture-of-Experts), and Behemoth (405B dense). All are released under a permissive license that allows commercial use for companies under 700M monthly active users.
Benchmarks vs GPT-5
Llama 4 Behemoth matches GPT-5 on MMLU and HumanEval, beats it on GSM8K math, loses on multilingual reasoning, and is roughly tied on coding benchmarks.
Real-world testing
we ran Behemoth via together.ai on a week of our typical prompts. Quality is genuinely close to GPT-5. The biggest gap is in following complex multi-step instructions, where GPT-5 still wins.
Why open weights matter
any company can self-host Llama 4 with full data control, zero vendor lock-in, no per-token pricing. For regulated industries (healthcare, finance, government), this is a game-changer.
Inference cost
Behemoth requires serious GPU infrastructure — 8x H100s for production serving. But hosted providers (Groq, Together, Fireworks) offer it at roughly half the price of GPT-5.
Smaller siblings
Llama 4 Scout (8B) is the new default local-AI model. It runs on a laptop and replaces GPT-4o-mini for most use cases.
The strategic picture
Meta is commoditizing AI to protect its own platforms from Google and OpenAI tax. The winners are everyone else — developers now have a free, near-frontier model to build on.
Llama 4 isn't going to dethrone ChatGPT for consumers. But for businesses and developers, it changes everything.
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