Mistral AI's Pixol 12B: A New Vision Model Review

Mistral AI's Pixol 12b excels at vision tasks, showcasing impressive performance and speed in image recognition and description.

### Mistral AI Launches Pixol 12B: A Game-Changing Multimodal Vision Model
* 🚀 Mistral AI has introduced **Pixol 12B**, an innovative open-source multimodal vision model that is set to be tested in this video.
* 💻 The model is hosted on Vulture, a cloud service provider that offers **easy GPU rentals**, and viewers can receive **$300 of free credit** using code **Burman300**.
* 📝 The initial announcement of Pixol was vague, but further details revealed it as a **12 billion parameter model** that excels in multimodal tasks, supporting **variable image sizes** and a **context window of 128,000 tokens**.
* 📊 In benchmark comparisons, Pixol 12B outperformed other models like Lava and Gemini across various tasks, showcasing its **strong performance in vision and instruction following**.
* 🐍 Testing began with coding tasks, where the model struggled with **logic and reasoning** but demonstrated **impressive speed and accuracy** in vision-related tasks, such as identifying a **llama** and recognizing **Bill Gates**.
* 🔍 The model successfully solved captchas and provided **accurate answers regarding iPhone storage**, though it misidentified an app's **download status**.
* 😂 When asked to explain a meme, Pixol accurately described the differences between startups and big companies, highlighting its **capability in understanding cultural references**.
* 🖼 Overall, Pixol 12B is a **powerful vision model**, and the video concludes with a recommendation to **explore its capabilities**, along with thanks to Vulture for their support.

Pixtral is REALLY Good - Open-Source Vision Model

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Mistral AI's Pixol 12b: A New Multimodal Vision Model

Mistral AI has launched Pixol 12b, an open-source multimodal vision model with 12 billion parameters.

The model excels in instruction following and offers strong performance on both multimodal and text-only tasks.

It supports variable image sizes, multiple images, and has a long context window of 128,000 tokens, making it a powerful tool for various vision and text tasks.

The model struggled with logic and reasoning tasks but excelled in visual recognition, quickly describing a llama and identifying Bill Gates.

It successfully solved a captcha challenge and provided accurate answers about an iPhone's storage, including total storage, used storage, and the app using the most storage.

However, it failed to correctly identify the app that was not downloaded on the phone, showing some limitations in understanding visual cues.

The meme humorously contrasts the work culture of startups and big companies using a construction analogy.

Startups are depicted as hands-on and actively digging, while big companies are shown observing and discussing without participating.

This illustration highlights the different approaches to work and oversight between the two.

The HTML code for a simple dropdown menu with a flavor selection was accurate and functional.

A more complex section of code from the Vulture homepage was also retrieved, but it didn't perfectly match the desired layout or include images.

The search for Waldo in a picture provided a general description of the character's location but didn't give a specific answer.

The right half of the image features several groups of people walking and standing.

Using a coordinate system, Waldo is located at approximately 65 horizontal and 45 down.

The low-resolution picture made it challenging, but Waldo was successfully found at that coordinate.