Meta's natively multimodal model (Llama 4) with an MoE architecture: 17B active and 400B total parameters (128 experts), 1M context, early fusion of text and image; open weights (Llama 4 Community License).
Context window
1M
tokens
Parameters
400B total / 17B active (MoE: 128 ekspertow)
parameters
Release date
5 April 2025
Access:DownloadAPIHostedDeployment:๐ป Localโ Cloud
Overview
Applications
Access & deployment
DownloadAPIHosted
LocalCloud
Weights: Open weights
Key parameters
๐ Context: 1M
๐งฉ Parameters: 400B total / 17B active (MoE: 128 ekspertow)
โ Toolsย ยทย โ Fine-tuning
๐ฅ Input: text, image
Platforms
Technical specification
Context window
1M
tokens
Parameters
400B total / 17B active (MoE: 128 ekspertow)
parameters
Knowledge cutoff
1 Aug 2024
Knowledge boundary
License
Llama 4 Community License
Hardware requirements
Large MoE model (400B weights) - requires a multi-accelerator server (e.g. a GPU node) or quantization for self-hosting; 17B active parameters lower inference cost. Supported: Transformers, vLLM.
Features:โ Tool useโ Fine-tuning
Modalities
โฌ Input
textimage
โฌ Output
textcode
Capabilities and applications
Native model capabilities
Reasoning
The model's ability to reason logically and solve complex problems.
Category: reasoning
Multi-step reasoning
Carrying out multi-step chains of reasoning across long, complex tasks.
Category: reasoning
Long context
Support for large context windows โ tens to hundreds of thousands (or millions) of input tokens. Enables analysis of entire codebases, long documents, and many parallel conversations without losing earlier information. GPT-5.1 supports 400,000 tokens.
Category: language
Coding
Generating, analysing and modifying code in many programming languages. Covers writing functions, debugging, refactoring, code review, and creating tests. Measured by benchmarks such as HumanEval and SWE-bench.
Category: coding
Function Calling
Category: planning
Structured output
Producing data in structured formats such as JSON.
Category: structured_generation
Image understanding
Analysing and interpreting the content of images.
Category: vision
Chart understanding
Reading and interpreting charts, tables and diagrams.
Category: vision
OCR
Recognising text within images and documents.
Category: vision
Multilingual
Competence in many natural languages (from a few to over a hundred): understanding, generation, translation, and code-switching within a single conversation. Frontier models support a wide range of languages with comparable quality.
Category: language
Planning
Forming and executing action plans for complex tasks.
Category: planning
Benchmark results
1 benchmark
LMArena (Chatbot Arena) - wersja eksperymentalna
Elo ยท An experimental chat version of Llama 4 Maverick scored an ELO of 1417 on LMArena (per Meta).
1417Elo
๐
5 Apr 2025
Source: Meta blog (2025-04-05). Score refers to the experimental version, not the released weights.
Pricing
Technical architecture
Core Architecture
Model Form
Training Techniques
Related Technologies
Deployment and security
โ Available on platforms
๐ Security / Enterprise
โ Verified enterprise information
Open weights (Llama 4 Community License) - self-hosting / on-premises possible with full data control. The license imposes restrictions (e.g. entities with >700M MAU require a separate grant). Supports function calling and tool integration.
Updated: 31 Jul 2026โ Security documentation
