Experience Meta's Revolutionary Llama 4 AI Models Today

Try the world's most powerful open-weight multimodal AI models with unprecedented 10M context windows and mixture-of-experts architecture - all for free in your browser.

Try Llama 4 Demo Now

Test Llama 4's Capabilities In Your Browser

Experience the power of Llama 4 Scout and Maverick directly in your browser. Upload images, ask complex questions, or test the 10M token context window capabilities.

Overview of Llama 4 AI

Native Multimodality

Seamlessly process both text and images with early fusion architecture that enables deep understanding across modalities.

Unprecedented Context Length

Work with up to 10 million tokens in Llama 4 Scout - analyze entire books, codebases, or document collections in a single prompt.

Mixture-of-Experts Architecture

Experience better performance with fewer resources through Llama 4's innovative MoE design that activates only a fraction of parameters per token.

Superior Performance

Outperforms competitors like GPT-4o, Gemini 2.0, and Claude on numerous benchmarks while requiring significantly less computational power.

Open Weights Access

Download and run Llama 4 models locally or integrate them into your applications with complete access to model weights.

Multilingual Excellence

Built with support for 200+ languages, with 10x more multilingual training tokens than previous Llama models.

How To Use The Llama 4 AI Online Demo

1
Choose Your Model
Select either Llama 4 Scout (17B parameters with 16 experts) or Llama 4 Maverick (17B parameters with 128 experts)
2
Enter Your Prompt
Type your question, instruction, or creative request in the text field
3
Upload Images (Optional)
Click the image icon to upload up to 8 images for multimodal tasks
4
Adjust Parameters (Optional)
Fine-tune generation settings like temperature and max tokens
5
Submit and Explore
Click "Generate" and watch Llama 4 create a response based on your inputs

Sample Prompts

"Explain the difference between mixture-of-experts and dense transformer models"
"Analyze these financial charts and identify market trends" (with image upload)
"Write a creative story based on this photograph" (with image upload)
"Summarize these multiple research papers in a comparative analysis" (with document upload)

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Llama 4 AI Technical Specifications

Model Specifications Comparison

Model	Active Parameters	Experts	Total Parameters	Context Window	Single H100 GPU
Llama 4 Scout	17B	16	109B	10M	Yes
Llama 4 Maverick	17B	128	400B	128K	No
Llama 4 Behemoth	288B	16	2T	128K	No

Pre-Training Specifications

•Trained on over 30 trillion tokens (2x Llama 3)
•FP8 precision without sacrificing quality
•390 TFLOPs/GPU achieved during pre-training
•200 languages supported (10x more multilingual tokens than Llama 3)
•100+ languages with over 1B tokens each

Post-Training Approaches

•Lightweight SFT → Online RL → Lightweight DPO pipeline
•50% of easy data removed (judged by Llama models)
•Continuous online RL with adaptive data filtering
•Carefully curated curriculum for multimodal balance
•Pre-trained and post-trained with 256K context length

Benchmarks and Comparisons

Llama 4 Maverick vs. Leading Models

Llama 4 Scout vs. Other Smaller Models

Bias Reduction Achievements

Llama 4 AI Technical Innovations

MetaP Training Technique

Allows reliable setting of critical model hyper-parameters which transfer well across different values of batch size, model width, depth, and training tokens

iRoPE Architecture

Interleaved attention layers without positional embeddings and temperature scaling of attention to enhance length generalization

Codistillation from Behemoth

Novel distillation loss function that dynamically weights soft and hard targets through training

Continuous Online RL

Training alternates between model training and filtering to retain only medium-to-hard difficulty prompts

Asynchronous RL Training

Fully asynchronous online RL training framework with ~10x improvement in training efficiency over previous generations

Safeguards and Protections

System-Level Approaches

•Llama Guard: Input/output safety model based on ML Commons hazards taxonomy
•Prompt Guard: Classifier for detecting malicious prompts and inject inputs
•CyberSecEval: Evaluations to understand and reduce AI cybersecurity risk

Testing and Evaluation

•GOAT: Generative Offensive Agent Testing for multi-turn adversarial interactions
•Systematic testing across various scenarios and use cases
•Adversarial dynamic probing across various topics

Frequently Asked Questions

What is Llama 4?

Llama 4 is Meta's latest family of AI models featuring a mixture-of-experts architecture and native multimodal capabilities. The family includes Llama 4 Scout (17B active parameters with 16 experts), Llama 4 Maverick (17B active parameters with 128 experts), and the upcoming Llama 4 Behemoth (288B active parameters with 16 experts).

How is Llama 4 different from previous models?

Llama 4 represents a significant advancement with its mixture-of-experts architecture, native multimodality (processing both text and images), and unprecedented context length of up to 10 million tokens. It outperforms previous Llama models and many competitors while requiring less computational resources.

Is this demo the official Meta AI product?

No, this website provides a third-party implementation of the open-weight Llama 4 models released by Meta. It is not affiliated with or endorsed by Meta.

Can I download the Llama 4 models?

Yes, Llama 4 Scout and Llama 4 Maverick are available for download on llama.com and Hugging Face. This website provides a convenient way to test the models without downloading them.

What can I use Llama 4 for?

Llama 4 excels at a wide range of tasks including text generation, image understanding, complex reasoning, code generation, multilingual translation, document analysis, and creative content creation.

How much context can Llama 4 handle?

Llama 4 Scout offers an industry-leading context window of 10 million tokens, allowing it to process entire books, codebases, or collections of documents in a single prompt.

Is my data safe when using this demo?

We do not store your prompts or generated outputs beyond what's needed for the current session. For details on our data handling practices, please see our Privacy Policy.

Where can I learn more about Llama 4's technical details?

For in-depth information about the architecture, training methodology, and benchmarks, visit Meta's AI blog or read the technical papers published about Llama 4.