Activefrontiermultimodal Open Source

Llama 4 Behemoth

by Meta· Released April 2025· Cutoff December 2024

Llama 4 Behemoth is Meta's most powerful and largest open-source multimodal model, designed to push the boundaries of AI research and development. It excels at complex reasoning, coding, and understanding both text and images, serving as a research-focused model for the community. As the flagship of the Llama 4 family, it offers unprecedented scale and capability for open-weight models.

Official Site 🤗 Hugging Face

Input cost

Free (open source)

Output cost

Free (open source)

Context window

1M tokens

Max output

8192 tokens

Modalities

textimage

Parameters

License

Llama 4 Community License

Capabilities

Multimodal Understanding (Text + Image)Complex ReasoningCode GenerationLong Context ProcessingFunction CallingMultilingual Support

Best For

Cutting-edge AI research, complex multimodal reasoning, and large-scale code generation tasks.

Strengths

Largest open-source model with 2 trillion parameters
State-of-the-art performance on reasoning and coding benchmarks
Supports extremely long context windows (1M tokens)
Strong multimodal capabilities with native image understanding

Limitations

Extremely high computational requirements for inference
Not optimized for real-time or low-latency applications
Requires significant expertise to deploy and fine-tune
Limited availability of pre-built tooling and ecosystem compared to smaller models

Use Cases

Advanced AI research and experimentation

Complex code generation and software development

Multimodal data analysis (e.g., medical imaging with text)

Long-document understanding and summarization

Scientific research and hypothesis generation

Large-scale synthetic data generation

Educational tools for advanced AI studies

Improvements Over Previous Model

First model in the Llama 4 family to reach 2 trillion parameters
Introduces native multimodal capabilities (text + image) compared to Llama 3's text-only
Context window expanded from 128K tokens (Llama 3) to 1M tokens
Significant improvements in reasoning and coding benchmarks over Llama 3
New MoE architecture for more efficient parameter usage

Back to all models

Use Cases

Advanced AI research and experimentation

Complex code generation and software development

Multimodal data analysis (e.g., medical imaging with text)

Long-document understanding and summarization

Scientific research and hypothesis generation

Large-scale synthetic data generation

Educational tools for advanced AI studies

Improvements Over Previous Model

First model in the Llama 4 family to reach 2 trillion parameters

Introduces native multimodal capabilities (text + image) compared to Llama 3's text-only

Context window expanded from 128K tokens (Llama 3) to 1M tokens

Significant improvements in reasoning and coding benchmarks over Llama 3

New MoE architecture for more efficient parameter usage