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)