Meta: Llama 4 Maverick
Meta's Llama 4 Maverick combines a massive 1M token context window with multimodal support, tool use, and function calling at a competitive price, making it well-suited to long-document and content-heavy business workflows; raw reasoning scores are modest but the breadth of capabilities and value proposition are strong.
Assessment date: April 4, 2026
Our methodology takes into account a range of factors including pricing, functionality, capabilities, benchmark performance, and real-world applicability. Rankings are reviewed and updated regularly as new models are released. Issues with our rankings? Contact us
Performance Profile
Llama 4 Maverick 17B Instruct (128E) is a high-capacity multimodal language model from Meta, built on a mixture-of-experts (MoE) architecture with 128 experts and 17 billion active parameters per forward..
Capabilities
Architecture
| Modality | Text + Image → Text |
| Tokenizer | Llama4 |
Performance Indices
Source: Artificial Analysis
Benchmark Scores
Intelligence
Technical
Content
Benchmark data from Artificial Analysis and Hugging Face
How does Meta: Llama 4 Maverick stack up?
Compare side-by-side with other specialist models.
Model Information
| OpenRouter ID |
meta-llama/llama-4-maverick
|
| Provider | meta-llama |
| Model Family | Llama 4 |
| Release Date | April 5, 2025 |
| Context Length | 1,048,576 tokens |
| Max Completion | 16,384 tokens |
| Status | Active |
Pricing
| Token Type | Cost per 1M tokens | Cost per 1K tokens |
|---|---|---|
| Input | $0.15 | $0.000150 |
| Output | $0.60 | $0.000600 |
Live Performance
Live endpoint metrics — refreshed every 30 minutes.
