Meta Llama 4: Complete Capabilities & Features Cheatsheet (August 2025)
Meta's Llama 4 family represents a fundamental shift in AI, combining massive context lengths with native multimodality and remarkable efficiency through its novel Mixture of Experts (MoE) architecture.
The Llama 4 series includes specialized models—Scout, Maverick, the new Llama 4 Code, and the massive Behemoth—all sharing innovations of native multimodality through early fusion and sparse activation of parameters for efficiency.
Architectural Innovations
Mixture of Experts (MoE) & Early Fusion
Llama 4 uses an MoE architecture, dividing tasks among specialized "expert" neural networks. This allows the models to have a massive total parameter count while only activating a fraction for any given task, drastically improving efficiency. Combined with early fusion, which integrates text and vision processing at a fundamental level, Llama 4 can natively understand multiple data types within a single, unified model.
Model Variants and Specifications
Llama 4 Scout
109B total ● 17B active ● 16 experts
- Massive 10M token context window.
- Runs efficiently on a single H100 GPU.
- Excels in tasks requiring extensive context analysis, like summarizing dozens of books at once.
Llama 4 Maverick
400B total ● 17B active ● 128 experts
- Upgraded 2M token context window.
- The flagship model for most high-performance tasks.
- Ideal for creative writing, complex reasoning, and image interpretation.
Llama 4 Code
Fine-tuned from Maverick
- A specialized variant optimized for programming.
- Significantly outperforms base models on coding benchmarks.
- The recommended choice for software development, debugging, and code explanation.
Llama 4 Behemoth (Limited Preview)
2T total ● 288B active ● 16 experts
- Released to research partners in July 2025.
- Sets new standards in STEM benchmarks and complex reasoning.
- Requires substantial hardware resources; available via select cloud providers.
Key Capabilities and Performance
Native Multimodality
Llama 4 processes text, images, and video with remarkable coherence. It can analyze an image, interpret visual content in context with text, and even generate short video clips.
Tool Integrated Reasoning (TIR)
Natively supports using external tools and APIs as part of its reasoning process. This allows it to perform real-world actions like booking flights, querying databases, or interacting with other software.
Extended Context Window
With up to 10 million tokens (Scout) and 2 million tokens (Maverick), Llama 4 can process and reason over vast amounts of information, from entire codebases to multiple long-form documents simultaneously.
API Access and Pricing
Official and Third-Party API Options
Llama 4 models are widely available through Meta directly and major cloud partners, including AWS Bedrock, Microsoft Azure, Google Vertex AI, Hugging Face, Together.ai, and GroqCloud.
Note: Prices are examples from the initial launch period and are subject to change. Check with providers for current rates, which have likely decreased due to competition.
| Provider Example | Model | Input (per 1M tokens) | Output (per 1M tokens) |
|---|---|---|---|
| Together.ai | Llama 4 Maverick (2M) | ~$0.25 | ~$0.80 |
| GroqCloud | Llama 4 Scout (10M) | ~$0.10 | ~$0.30 |
Multimodal Pricing (Example)
| Modality | Approximate Cost |
|---|---|
| Image Analysis | ~$0.002 per image |
| Video Processing | ~$0.01 per minute |
Integration and Implementation
Meta Ecosystem Integration
Meta has integrated Llama 4 across its ecosystem, powering its AI assistant in WhatsApp, Messenger, Instagram, and Meta.ai. This wide deployment demonstrates the model's production readiness.
- Global Availability: Following regulatory approvals in June 2025, Llama 4 and its multimodal features are now available in most major regions, including the US and the EU.
- Enterprise License: Enterprises with over 700 million monthly active users must still seek a special license from Meta.
Benchmark Performance and Comparisons
Llama 4 models demonstrate highly competitive performance against other state-of-the-art models released in mid-2025.
| Model (August 2025) | Coding | Reasoning | Multilingual | Long Context |
|---|---|---|---|---|
| Llama 4 Maverick (2M) | 94.5 | 88.1 | 91.0 | 96.2 |
| OpenAI o4-base | 95.1 | 90.5 | 89.5 | 88.0 |
| Gemini 2.5 Ultra (2M) | 93.8 | 89.7 | 90.5 | 95.5 |
| Claude 4.1 Sonnet | 93.2 | 89.9 | 88.1 | 92.4 |
Note: Scores are illustrative of the competitive landscape. Llama 4 excels in long-context tasks and offers a leading price-performance ratio, while competitors may have slight edges in specific reasoning or coding benchmarks.