Meta: Llama 4 Maverick
By Meta Llama
Released: 2025-04-05
Meta Llama Llama 4 Maverick, developed by Meta, features 17B parameters, MoE architecture and 1,049k-token context window. 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 pass (400B total). It supports multilingual text and image input, and produces multilingual text and code output across 12 supported languages. optimised for vision-language tasks, Maverick is instruction-tuned for assistant-like behaviour, image reasoning, and general-purpose multimodal interaction. Maverick features early fusion for native multimodality and a 1 million token context window. It was trained on a curated mixture of public, licensed, and Meta-platform data, covering ~22 trillion tokens, with a knowledge cutoff in August 2024. Released on April 5, 2025 under the Llama 4 Community License, Maverick is suited for research and commercial applications requiring advanced multimodal understanding and high model throughput. Available at $0.15/1M tokens.
Visit Meta: Llama 4 MaverickAI-Powered
Leverages advanced AI technology to deliver cutting-edge capabilities and results.
Fast & Efficient
Optimized performance ensures quick results without compromising on quality.
Purpose-Built
Specifically designed for llms tasks and workflows.
Meta Llama Model Timeline
164k tokens context
1,049k tokens context
328k tokens context
131k tokens context
131k tokens context
131k tokens context
131k tokens context
131k tokens context
60k tokens context
131k tokens context
33k tokens context
16k tokens context
131k tokens context
10k tokens context
131k tokens context
8k tokens context
8k tokens context
8k tokens context
Specifications
AI Evaluation
Combines language understanding with search capabilities. Excels at finding and synthesizing information from various sources.
Pros
- Competitive pricing ($0.15/1M)
- Massive 1,049k token context
- Advanced logical reasoning
- Image and visual analysis
Cons
- API integration required
- May need prompt tuning
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