Activefrontiermultimodal Open Source

Llama 4 Maverick

by Meta· Released April 2025· Cutoff December 2024

Llama 4 Maverick is Meta's most advanced multimodal model, designed for complex reasoning and vision-language tasks. It excels in coding, math, and instruction following, with a 10M token context window and native support for images and text. As the flagship of the Llama 4 family, it sets new standards for open-weight AI performance.

Official Site API Docs 🤗 Hugging Face

Input cost

Free (open source)

Output cost

Free (open source)

Context window

10M tokens

Max output

8192 tokens

Modalities

textimage

Parameters

400B (MoE, 17B active)

License

Llama 4 Community License

Capabilities

Multimodal (text + image)Function CallingCode GenerationReasoningJSON ModeStreamingLong Context UnderstandingInstruction Following

Best For

Complex multimodal reasoning, long-context analysis, and advanced coding tasks.

Strengths

State-of-the-art multimodal performance
Massive 10M token context window
Strong coding and math capabilities
Open-source with permissive license
Efficient MoE architecture for fast inference

Limitations

Requires significant computational resources
May exhibit biases present in training data
Not optimized for real-time audio or video processing
Limited availability of fine-tuning tools
Potential for hallucination in ambiguous contexts

Use Cases

Analyzing long documents with embedded images

Generating code from visual diagrams

Multimodal question answering over large datasets

Complex mathematical problem solving

Building AI assistants with vision capabilities

Content creation combining text and images

Research in multimodal AI

Improvements Over Previous Model

Introduced multimodal (text+image) support, unlike Llama 3 which was text-only
Context window expanded from 128K tokens (Llama 3) to 10M tokens
MoE architecture with 400B total parameters (17B active) vs dense 70B/405B in Llama 3
Significantly improved coding and math benchmarks
New Llama 4 Community License with broader permissions
Enhanced instruction following and reasoning capabilities

Back to all models

Improvements Over Previous Model

Introduced multimodal (text+image) support, unlike Llama 3 which was text-only

Context window expanded from 128K tokens (Llama 3) to 10M tokens

MoE architecture with 400B total parameters (17B active) vs dense 70B/405B in Llama 3

Significantly improved coding and math benchmarks

New Llama 4 Community License with broader permissions

Enhanced instruction following and reasoning capabilities