Meta just dropped Llama-4, but it does NOT look good…
# Meta’s Llama 4 Release: Impressive Claims, Mixed Reality
Meta recently released their new Llama 4 family of AI models, but the reception has been mixed despite some impressive technical specifications. This release has sparked both excitement and controversy in the AI community.
## The Llama 4 Family: Massive but Specialized
Meta introduced three new mixture-of-experts (MoE) models:
– **Llama 4 Scout**: 109 billion parameters with 17 billion active parameters and 16 experts
– **Llama 4 Maverick**: 400 billion parameters with 17 billion active parameters and 128 experts
– **Llama 4 Behemoth**: 2 trillion parameters with 288 billion active parameters and 16 experts (still in training)
Unlike traditional dense models where all parameters activate for each token, MoE models only activate a fraction of their parameters at any time, allowing for more knowledge storage with reduced computational demands.
## Headline Features
– **Massive context window**: Llama 4 Scout supports a 10 million token context window, 78 times larger than most open models
– **Multimodal capabilities**: Built from the ground up with text and image understanding (but can’t generate images)
– **High benchmark scores**: Claims an impressive 1417 ELO on LM Arena
## The Controversies
Despite the impressive specifications, several issues have emerged:
1. **Poor instruction following**: Independent testers found Llama 4 models frequently failing to follow even basic instructions, such as counting letters in a word
2. **Benchmark discrepancies**: Significant gaps between Meta’s claimed benchmark results and independent testing
3. **Misleading marketing**: Some community members felt the marketing around “active parameters” was intentionally misleading
4. **Context quality issues**: On Fiction Live Bench (which tests comprehension rather than search ability), performance declined dramatically after just 400 tokens
5. **Different benchmark models**: Meta acknowledged using a “version optimized for conversations” for LM Arena benchmarks, not the actual released models
## Current Strengths
Despite the criticisms, Llama 4 does excel in vision understanding capabilities, performing well on vision
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