🚨 BREAKING: NEW Llama 4 Update (FREE!)

Key Concepts

Llama 4, Llama 4 Maverick, Llama 4 Scout, Grock, Open Router, Benchmarks, Context Window (10 million tokens), API, Code Generation, Reasoning, LM Arena, Side-by-side comparison, Visual Studio Code, Client, Rootcode, SEO Optimization.

Llama 4 Model Overview

The video discusses the newly released Llama 4 models, focusing on Llama 4 Maverick and Llama 4 Scout. A key highlight is Llama 4's extended context window of 10 million tokens. The models are available on llama.com, Hugging Face, and Grock.

Model Variants

Llama 4 Maverick: Shown in benchmarks to outperform Gemini 2.0 Flash, Deepseek 3.1, and GPT-4o.
Llama 4 Scout: A smaller, lightweight model suitable for local hosting, benchmarked against Gemma 3, Mistral 3.1, and Gemini 2.0 Flash.
Llama 4 Baremoth: Supposedly outperforming Claude 3.7 Sonnet, Gemini 2.0 Pro, and GPT 4.5. Early preview available.

Accessing Llama 4

llama.com: Request access via the download section.
Hugging Face: Available on Hugging Face.
Grock (grok.com): Access through the dev console and playground. Llama 4 Scout is available in the playground.
Open Router: Llama 4 Maverick and Scout are available as free APIs.

Benchmarking and Performance

Content Creation Test

The presenter tested Llama 4 Maverick and Scout with the prompt: "Create an SEO optimized article for this keyword = content outline for content creation. Do this included some information about me who I am etc."
Scout's output was subjectively deemed better than Maverick's for content creation. Scout generated a 719-word article quickly.

Reasoning Challenge

The models were tested with the prompt: "There's a tree on the other side of the river, how can I pick an apple?"
Maverick provided a concise response, pointing out the impossibility due to winter and the river.
Scout gave a more detailed and longer response.

Speed Comparison

Llama 4 inside Grock was significantly faster than using it through Open Router.

Code Generation Tests

Visual Studio Code Integration

Client and Rootcode extensions were used to integrate Llama 4 into Visual Studio Code.
Open Router was selected as the API provider for Llama 4 within these extensions.
A test to "create a self-playing snake game" was initiated using Llama 4 Scout.

3JS Runner Game Test

A prompt from the AI Profit Boardroom was used: "Make me a captivating endless runner game key instructions on the screen p5jfc no HTML i like pixelated dinosaurs and interesting backgrounds."
The test was conducted within Grock using Llama 4 Scout.
The generated code was tested but did not work as expected.

LM Arena Comparison

Meta's Llama 4 Maverick is ranked number two overall on LM Arena, surpassing Deepseek and tying for number one in hard prompts and coding.
A side-by-side comparison was conducted on LM Arena between Llama 4 Maverick and Chat GPT-4o using the same prompt as before.
Chat GPT-4o's response was subjectively rated as significantly better than Llama 4 Maverick's.

Key Quotes

"Llama 4 actually has a 10 million token limit it is absolutely insane."
"One of the things I've always been impressed by with Llama is its ability to just be so fast it's just redonkulous."
"That is unbelievably fast wow so actually if you want really speedy results I would recommend using llama 4 directly inside Brock it seems to be a lot faster."
"Honestly is that anywhere near the same level as call 3.7 Sonet no."

Technical Terms

Context Window: The amount of text the model can consider when generating a response. Llama 4 has a 10 million token context window.
API (Application Programming Interface): A set of rules and specifications that software programs can follow to communicate with each other.
Benchmarks: Standardized tests used to measure the performance of AI models.
SEO (Search Engine Optimization): The process of improving the visibility of a website or web page in search engine results.
LM Arena: A platform for comparing and ranking large language models.

Synthesis/Conclusion

The video provides a first look at the new Llama 4 models, highlighting their impressive context window and benchmark performance. While Llama 4 Maverick shows promise in benchmarks, initial tests in the video suggest that its performance may not consistently match that of models like Chat GPT-4o. Llama 4 Scout offers a lightweight alternative, and using Llama 4 directly within Grock appears to provide the fastest response times. The presenter encourages viewers to test the models themselves and provides links to access them. The presenter also promotes his AI community and SEO strategy session.