Model Profile: LLaMA 4 Maverick (Meta)
Explore Meta's LLaMA 4 Maverick, a next-gen natively multimodal MoE model excelling in coding, reasoning, and vision tasks with high efficiency on allmates.ai.
Last updated 8 months ago
Tagline: Meta's next-gen multimodal MoE model for top performance in coding, reasoning, and vision.
📊 At a Glance
Primary Strength: Native Multimodality (Text & Vision), Excellent Coding & Reasoning, High Efficiency (MoE), Large Context.
Performance Profile:
Intelligence: 🟢 Higher (Industry-leading for its class)
Speed: 🟢 Faster (17B active parameters)
Cost: 🟡 Medium (Efficient MoE architecture)
Key Differentiator: Natively multimodal (early fusion of text & vision), 17B active / 128 experts (400B total) MoE architecture, 1M token context. Beats GPT-4 on image-text benchmarks.
allmates.ai Recommendation: A leading-edge choice for Mates requiring advanced multimodal understanding (especially vision), top-tier coding and reasoning, with excellent performance-to-cost ratio.
📖 Overview
LLaMA 4 Maverick, announced by Meta AI in mid-2025, is a next-generation, natively multimodal foundation model. It features a Mixture-of-Experts (MoE) architecture with approximately 17 billion active parameters (out of ~400B total from 128 experts), designed for high efficiency and top-tier performance. Maverick excels in coding, reasoning, and particularly in vision tasks, reportedly outperforming models like GPT-4 on image-text benchmarks. It supports a 1 million token context window and is designed for high-quality chat and advanced image captioning/analysis.
🛠️ Key Specifications
Feature Detail | |
Provider | Meta AI |
Model Series/Family | LLaMA 4 |
Context Window | 1,000,000 tokens |
Max Output Tokens | 1,000,000 tokens |
Knowledge Cutoff | April 2025 |
Architecture | Mixture-of-Experts (MoE), Natively Multimodal (Text & Vision early fusion) |
Size | 400B total from 128 experts |
🔀 Modalities
Input Supported:
Text
Images
Output Generated:
Text
⭐ Core Capabilities Assessment
Reasoning & Problem Solving: ⭐⭐⭐⭐✰ (Very Strong)
Excellent reasoning capabilities, enhanced by MoE architecture and refined post-training.
Writing & Content Creation: ⭐⭐⭐⭐✰ (Very Strong)
Produces coherent, context-rich text, capable of creative tasks combining text and visuals.
Coding & Development: ⭐⭐⭐⭐✰ (Very Strong)
"Industry-leading capabilities on coding"; a top performer for code generation and understanding.
Mathematical & Scientific Tasks: ⭐⭐⭐⭐✰ (Very Strong)
Strong in math and science, can interpret graphs/equations from images.
Instruction Following: ⭐⭐⭐✰✰ (Good)
Well-tuned for chat and following complex instructions, including multimodal ones.
Factual Accuracy & Knowledge: ⭐⭐⭐⭐✰ (Very Strong)
Broad and up-to-date knowledge base, with strong grounding in visual information.
🚀 Performance & 💰 Cost
Speed / Latency: Faster
High performance-to-cost ratio due to 17B active parameters, making it fast for its capability level.
Pricing Tier (on allmates.ai): Medium
Designed for efficiency; likely competitive pricing on cloud platforms.
✨ Key Features & Strengths
Native Multimodality (Vision): Early fusion of text and vision for deep image understanding.
Leading Coding Performance: A top-tier model for software development tasks.
Efficient MoE Architecture: High capability with efficient inference (17B active).
Large Context Window: 1 million tokens for processing extensive information.
Advanced Image Understanding: Excels at precise image captioning, analysis, and visual Q&A.
Open Availability (Likely): Continues Meta's trend, with deployment on major cloud platforms.
🎯 Ideal Use Cases on allmates.ai
Multimodal Customer Support Mates: Understanding user issues from text and uploaded screenshots.
Advanced Coding Assistants: Mates providing sophisticated code generation, review, and debugging with visual context (e.g., UI mockups).
Visual Q&A and Analysis: Mates that can answer detailed questions about images, charts, or diagrams.
Content Creation with Visuals: Generating descriptive text for images or creating content that integrates visual understanding.
High-Performance Generalist Mates: When a blend of top-tier reasoning, coding, and vision is needed efficiently.
⚠️ Limitations & Considerations
Audio/Video Modalities: Primarily focused on text and vision at launch; other modalities not explicitly detailed.
Complexity of MoE Deployment: Self-hosting such a model, despite active parameter efficiency, can still be complex.
License Terms: Specific terms for commercial use of LLaMA 4 weights should be verified.
🏷️ Available Versions & Snapshots (on allmates.ai)
llama-4-maverick(or similar, alias pointing to the recommended version)