Llama 4 Maverick
Llama 4 Maverick by Meta is a 400B MoE model with 128 experts, 17B active parameters, native early-fusion multimodality, and a 1M token context window.
Model Overview
Capabilities, design details, and architectural traits
Llama 4 Maverick - 128-Expert MoE General-Purpose Multimodal Model
Llama 4 Maverick is Meta's open-weight general-purpose model in the Llama 4 series. It uses a mixture-of-experts (MoE) architecture with 128 routed experts plus one shared expert. Each token is routed to the shared expert and exactly one of the 128 routed experts per MoE layer.
Architecture
Maverick uses alternating dense and MoE layers - not a pure MoE stack - combined with early fusion for native multimodality, integrating text and image inputs at the token level. It is released in both BF16 and FP8 quantized weights.
Context Strategy
Maverick supports a 1 million token context window, positioned for applications requiring extensive document or multi-image reasoning.
Training Data
Pretrained on approximately 22 trillion tokens of multimodal data, including publicly available content, licensed data, and Meta platform data (Instagram, Facebook, Meta AI interactions).
Benchmark Performance
Independent evaluations · Artificial Analysis
Accuracy & Capability Details
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| Model Details | |||
|---|---|---|---|
| General Info | |||
| Provider | Meta | Anthropic | Anthropic |
| Release Date | April 5, 2025 | September 22, 2026 | September 28, 2026 |
| Knowledge Cutoff | Aug 2024 | - | Jun 2026 |
| Context & Limits | |||
| Context Window | 1.0M Best Context Window | 1M | 1M |
| Pricing (per 1M tokens) | |||
| Input Pricing | $0.25 Best Input Pricing | $4 | $2 |
| Output Pricing | $0.87 Best Output Pricing | $20 | $10 |
| Modalities | |||
| Inputs | textimage | textimagefile | textimagefile |
| Outputs | text | text | text |
| Benchmarks (0-100) | |||
| Intelligence Index | 10.0 | 57.6 Best Intelligence Index | 56.0 |
| Coding Index | 16.3 | - | - |
| Agentic Index | 0.6 | - | - |
Humanity's Last Exam
Extremely difficult logical reasoning and knowledge.
Long Context Reasoning
Logical reasoning over long context windows.
SciCode Benchmark
Scientific coding and mathematical modeling.
Independent evaluation data provided by Artificial Analysis. To view the latest benchmarks and full details, visit their official site.
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