Boost your AI´s response quality by 200% to 400%*

World’s first operating system for AI with heterogeneous computing

Company

The Company

MultiCortex is a tech company that developed the world’s first operating system based on heterogeneous computing.

Heterogeneous computing involves the use of different types of processors (CPU, GPU, FPGA, among others) working together to enhance performance and efficiency, emerging as the future of artificial intelligence.

MultiCortex has bases in both the United States and Brazil, and was founded by professionals with over 30 years of experience in the industry.

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Heterogeneous Computing

Technology

Officially established at Harvard University, heterogeneous computing is a technology that employs different types of processors within a single system to optimize performance and energy efficiency.

Historical Overview:

1980–1990: Research begins on multi-architecture systems that integrate different processors.
1995: Publication of the article “Simultaneous Multithreading: Maximizing On-Chip Parallelism” by M. Tullsen, J. Eggers, and M. Levy. This work is considered a milestone in the field.
2003: The concept of heterogeneous computing is officially born at Harvard University.
Until 2020: The concept is extensively studied by Intel (USA).
2024: MultiCortex develops the world’s first AI-focused operating system based on heterogeneous computing.
2025: The concept grows exponentially with the expansion of the UXL Foundation, an organization created to promote heterogeneous computing worldwide.

Highlights

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Optimized performance

Each type of processor is used for what it does best.

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Energy efficiency

It avoids the excessive use of high-powered resources.

Cost reduction

By combining general-purpose hardware with specialized accelerators, it is possible to reduce operational costs.

MultiCortex AI Operating System (OS)

MultiCortex Operating System was developed using OpenSUSE, CUDA, oneAPI, OpenVINO, and ROCm, and stands out for its heterogeneous computing technology.

Heterogeneous computing applied to AI brings multiple benefits, especially the simultaneous use of different models and accelerators from various manufacturers — a milestone for the industry.

Interface:

As of June 2025, it is estimated that there are only four operating systems in the world specifically designed for artificial intelligence on servers.

Among them, the MultiCortex operating system is by far the most advanced.

In recognition of these and other achievements, Alessandro Faria, Co-founder of MultiCortex, was named Intel Top Innovator World Champion 2024–2025*.

Important: Survey conducted by the company between May 2025 and June 2025. Additionally, there are AI-focused desktop operating systems, such as Steve by Walturn, Copilot, OpenKylin, Warmwind, among others. However, these are not capable of handling server-level (enterprise-grade) processing loads. The MultiCortex OS is also suitable for desktop use. *Images are for illustrative purposes only. Source: https://newsroom.intel.com/pt/inteligencia-artificial/top-innovators-de-2024-e-destaca-inovacao-brasil

Benefits of the MultiCortex Operating System (SO) for AI

Zero technological lock-in for hardware;

Zero technological lock-in for open soure models;
Depth gains (more complete responses);
Data sovereignty;
Reduction of TCO (Total Cost of Ownership).

Contact MultiCortex for more information.

Illustrative images: Depth gains (more comprehensive responses). Comparative tests between systems using the same LLM model, machine, and prompt — one without MultiCortex and one with it. The metric used was the length of the response to the same question. The tests were conducted at the company’s facilities between February and March 2025.

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Buy now on AWS

Phi-4 - 14b - For GPU

Boosted by MultiCortex

Built on openSUSE Linux, this product provides private AI using the Phi-4 model with 14 billion parameters. MultiCortex allows you to boost your AI's response quality. This is a plug-and-play, low-cost product with no token fees.

About Phi-4:

Phi-4 is a state-of-the-art language model developed by Microsoft, standing out for its ability to perform complex reasoning, especially in areas like mathematics. With 14 billion parameters, Phi-4 represents a significant advancement for Microsoft, delivering high-quality results in a relatively compact size.

Performance and Applications:
Phi-4 outperforms comparable models in tasks related to mathematical reasoning, thanks to advancements in its training process and the use of high-quality curated data. Additionally, its efficiency allows it to be deployed in environments with limited computational resources, enabling local execution with reduced latency and lower operational cost.

Key Strengths of Phi-4:

High performance in mathematical reasoning: Outperforms larger models in math-related tasks due to its optimized training.
Computational efficiency: Can run on local devices with lower operational costs and low latency.
Optimized architecture: Decoder-only transformer model with 14 billion parameters and a 16,000 token context window.
Advanced training: Uses high-quality synthetic data and a rigorous fine-tuning process for better instruction following.
Enhanced safety and alignment: Incorporates modern techniques to ensure safer and more reliable responses.

Buy now Phi-4 - 14b Boosted by MultiCortex on AWS.

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Gemma 3 - 12b - For CPU

Boosted by MultiCortex

Built on openSUSE Linux, this product provides private AI using the Gemma 3 model with 1 billion parameters. MultiCortex allows you to boost your AI's response quality. This is a plug-and-play, low-cost product with no token fees.

About Gemma 3:

Gemma 3 is the latest generation of open language models developed by Google (April/2025). Designed to be efficient and versatile, Gemma 3 offers advanced capabilities that support a wide range of artificial intelligence applications.

Key Features of Gemma 3:

Multimodality: Gemma 3 can process text inputs, images, and short videos, enabling the creation of applications that analyze and interpret various types of media.

Multilingual Support: With support for over 140 languages, Gemma 3 facilitates global communication and adaptation of applications.

Extended Context Windows: The model supports context windows of up to 128,000 tokens, allowing for the processing of more complex information and better handling of tasks that require deep contextual understanding.

Computational Efficiency: Gemma 3 is designed to operate efficiently on devices with limited resources, and is considered the most powerful AI model capable of running on a single GPU.

Advanced Reasoning Capabilities: The model delivers advanced capabilities in mathematics, reasoning, and chat, including structured outputs and function calls— expanding the possibilities for interaction and automation.

Buy now Gemma 3 - 1b Boosted by MultiCortex on AWS.

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Gemma 3 - 12b - For CPU

Boosted by MultiCortex

Built on openSUSE Linux, this product provides private AI using the Gemma 3 model with 12 billion parameters. MultiCortex allows you to boost your AI's response quality. This is a plug-and-play, low-cost product with no token fees.

About Gemma 3:

Gemma 3 is the latest generation of open language models developed by Google (April/2025). Designed to be efficient and versatile, Gemma 3 offers advanced capabilities that support a wide range of artificial intelligence applications.

Key Features of Gemma 3:

Multimodality: Gemma 3 can process text inputs, images, and short videos, enabling the creation of applications that analyze and interpret various types of media.

Multilingual Support: With support for over 140 languages, Gemma 3 facilitates global communication and adaptation of applications.

Extended Context Windows: The model supports context windows of up to 128,000 tokens, allowing for the processing of more complex information and better handling of tasks that require deep contextual understanding.

Computational Efficiency: Gemma 3 is designed to operate efficiently on devices with limited resources, and is considered the most powerful AI model capable of running on a single GPU.

Advanced Reasoning Capabilities: The model delivers advanced capabilities in mathematics, reasoning, and chat, including structured outputs and function calls— expanding the possibilities for interaction and automation.

Buy now Gemma 3 - 12b Boosted by MultiCortex on AWS.

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LLaMa 3.2 - 1b - For CPU

Boosted by MultiCortex

Built on openSUSE Linux, this product provides private AI using the LLaMa 3.2 model with 1 billion parameters. MultiCortex allows you to boost your AI's response quality. This is a plug-and-play, low-cost product with no token fees.

About LLaMa 3.2:

LLaMa Three 3.2 is a large language model developed by Meta AI and released in December twenty twenty four. This model represents a significant advancement in terms of efficiency and performance in the field of artificial intelligence.

Performance and Efficiency:
Llama 3.2 delivers strong performance with significantly lower computational requirements compared to previous models. This enables developers and companies to deploy advanced AI solutions without the need for expensive and specialized infrastructure.

Multilingual Capabilities:
Designed to serve a global audience, LLaMa 3.2 supports multiple languages and outperforms many existing conversational models on standard industry benchmarks. This makes it ideal for applications that require understanding and generating text in various languages.

Highlights:

Computational efficiency. Designed to run on more accessible infrastructure, reducing operational costs.

Practical applications. Used by companies for automation, customer support, and other AI tasks.

Privacy and control. Companies can implement the model without compromising sensitive customer data.

Buy now LLaMa 3.2 - 1b Boosted by MultiCortex on AWS.

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LLaMa 3.2 - 3b - For CPU

Boosted by MultiCortex

Built on openSUSE Linux, this product provides private AI using the LLaMa 3.2 model with 3 billion parameters. MultiCortex allows you to boost your AI's response quality. This is a plug-and-play, low-cost product with no token fees.

About LLaMa 3.2:

LLaMa Three 3.2 is a large language model developed by Meta AI and released in December twenty twenty four. This model represents a significant advancement in terms of efficiency and performance in the field of artificial intelligence.

Performance and Efficiency:
Llama 3.2 delivers strong performance with significantly lower computational requirements compared to previous models. This enables developers and companies to deploy advanced AI solutions without the need for expensive and specialized infrastructure.

Multilingual Capabilities:
Designed to serve a global audience, LLaMa 3.2 supports multiple languages and outperforms many existing conversational models on standard industry benchmarks. This makes it ideal for applications that require understanding and generating text in various languages.

Highlights:

Computational efficiency. Designed to run on more accessible infrastructure, reducing operational costs.

Practical applications. Used by companies for automation, customer support, and other AI tasks.

Privacy and control. Companies can implement the model without compromising sensitive customer data.

Buy now LLaMa 3.2 - 3b Boosted by MultiCortex on AWS.

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Deepseek R-1 - 1.5b - For CPU

Boosted by MultiCortex

Built on openSUSE Linux, this product provides private AI using the Deepseek R-1 model with 1.5 billion parameters. MultiCortex allows you to boost your AI's response quality. This is a plug-and-play, low-cost product with no token fees.

About Deepseek R1:
DeepSeek R1 is an advanced open source language model initiative focused on delivering high performance, efficiency, and versatility. The lineup includes models of different sizes and architectures, with a strong emphasis on its modern Mixture of Experts approach, supporting a large input context length.

Why is this architecture eficiente:

The Mixture of Experts approach is powerful because it allows only a fraction of the model to be used at a time. This results in:

Reduced inference time. Even with billions of parameters, partial activation keeps execution fast.

Computational efficiency. Selective use of experts reduces memory consumption and processing power.

Improved specialization. Each expert can focus on specific task types, enhancing overall accuracy.

Ideal use cases for DeepSeek R1:

Interpreting large, structured reports or datasets

Literature reviews and meta-analyses

Advanced chatbots and conversational agents that handle long dialogues and rich contexts.

Code generation and understanding, thanks to its ability to process large blocks of text.

Buy now Deepseek R-1 - 1.5b Boosted by MultiCortex on AWS.

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Deepseek R-1 - 14b - For GPU

Boosted by MultiCortex

Built on openSUSE Linux, this product provides private AI using the Deepseek R-1 model with 14 billion parameters. MultiCortex allows you to boost your AI's response quality. This is a plug-and-play, low-cost product with no token fees.

About Deepseek R1:
DeepSeek R1 is an advanced open source language model initiative focused on delivering high performance, efficiency, and versatility. The lineup includes models of different sizes and architectures, with a strong emphasis on its modern Mixture of Experts approach, supporting a large input context length.

Why is this architecture eficiente:

The Mixture of Experts approach is powerful because it allows only a fraction of the model to be used at a time. This results in:

Reduced inference time. Even with billions of parameters, partial activation keeps execution fast.

Computational efficiency. Selective use of experts reduces memory consumption and processing power.

Improved specialization. Each expert can focus on specific task types, enhancing overall accuracy.

Ideal use cases for DeepSeek R1:

Interpreting large, structured reports or datasets

Literature reviews and meta-analyses

Advanced chatbots and conversational agents that handle long dialogues and rich contexts.

Code generation and understanding, thanks to its ability to process large blocks of text.

Buy now Deepseek R-1 - 14b Boosted by MultiCortex on AWS.

Click here

Qwen 2.5 - 0.5b - For CPU

Boosted by MultiCortex

Built on openSUSE Linux, this product provides private AI using the Qwen 2.5 model with 0.5 billion parameters. MultiCortex allows you to boost your AI's response quality. This is a plug-and-play, low-cost product with no token fees.

About Qwen:

Qwen is the large language model and large multimodal model series of the Qwen Team, Alibaba Group. Now the large language models have been upgraded to Qwen2.5. Both language models and multimodal models are pretrained on large-scale multilingual and multimodal data and post-trained on quality data for aligning to human preferences. Qwen is capable of natural language understanding, text generation, vision understanding, audio understanding, tool use, role play, playing as AI agent, etc.

Qwen 2.5 has the following features:

Pretrained on our latest large-scale dataset, encompassing up to 18T tokens.

Significant improvements in instruction following, generating long texts (over 8K tokens), understanding structured data (e.g, tables), and generating structured outputs especially JSON.

More resilient to the diversity of system prompts, enhancing role-play implementation and condition-setting for chatbots.

Context length support up to 128K tokens and can generate up to 8K tokens.

Multilingual support for over 29 languages, including Chinese, English, French, Spanish, Portuguese, German, Italian, Russian, Japanese, Korean, Vietnamese, Thai, Arabic, and more.

Buy now Qwen 2.5 - 0.5b Boosted by MultiCortex on AWS.

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Qwen 2.5 - 14b - For GPU

Boosted by MultiCortex

Built on openSUSE Linux, this product provides private AI using the Qwen 2.5 model with 14 billion parameters. MultiCortex allows you to boost your AI's response quality. This is a plug-and-play, low-cost product with no token fees.

About Qwen:

Qwen is the large language model and large multimodal model series of the Qwen Team, Alibaba Group. Now the large language models have been upgraded to Qwen2.5. Both language models and multimodal models are pretrained on large-scale multilingual and multimodal data and post-trained on quality data for aligning to human preferences. Qwen is capable of natural language understanding, text generation, vision understanding, audio understanding, tool use, role play, playing as AI agent, etc.

Qwen 2.5 has the following features:

Pretrained on our latest large-scale dataset, encompassing up to 18T tokens.

Significant improvements in instruction following, generating long texts (over 8K tokens), understanding structured data (e.g, tables), and generating structured outputs especially JSON.

More resilient to the diversity of system prompts, enhancing role-play implementation and condition-setting for chatbots.

Context length support up to 128K tokens and can generate up to 8K tokens.

Multilingual support for over 29 languages, including Chinese, English, French, Spanish, Portuguese, German, Italian, Russian, Japanese, Korean, Vietnamese, Thai, Arabic, and more.

Buy now Qwen 2.5 - 14b Boosted by MultiCortex on AWS.

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Mistral Small - 24b - For GPU

Boosted by MultiCortex

Built on openSUSE Linux, this product provides private AI using the Mistral Small model with 24 billion parameters. MultiCortex allows you to boost your AI's response quality. This is a plug-and-play, low-cost product with no token fees.

About Mistral 0.3:

Mistral 0.3 is an open source language model developed by the company Mistral AI. It is designed to deliver high performance, versatility, and practical use across a wide range of natural language tasks.

Main Features:

Extended context of up to thirty two thousand tokens allowing it to handle long and complex inputs.
Built using a decoder only architecture similar to GPT style models.
High performance on tasks such as text understanding problem solving question answering and code interpretation.
Trained with modern alignment techniques ensuring greater safety clarity and adherence to instructions.

Highlights of Mistral 0.3:

Competitive performance surpassing many open source models of similar size in standard benchmarks.

Ready for instruction and chat use suitable for conversation tasks virtual assistants technical support and interactive applications.

Ideal for local or enterprise environments requiring less demanding infrastructure.

Easy integration into custom AI pipelines APIs and commercial applications.

Buy now Mistral Small - 24b Boosted by MultiCortex on AWS.

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Founders

Bruno Ghizoni

Highlights:

Internationally awarded in AI with the title "Distinguished Innovator" delivered through the curatorship of George Washington University (USA) and BSA (Business Software Alliance - largest global conglomerate of software companies);

More than 20 years of experience in innovation and the financial market;

Led more than R$150 million in investments in innovation;

Creator of Majestic - 1st beverage line in the world developed with AI support;

Degree from ESG and MBA in innovation from FIA-USP;

Professor of innovation at FIA-USP.

Alessandro Faria

Highlights:

Co-founder of MultiCortex, OITI TECHNOLOGIES, and the global openSUSE Linux INNOVATOR initiative
Self-taught researcher and innovation enthusiast since 1983 (at age 11)
Dedicated Linux user since 1998, with a focus on biometrics and computer vision
Experienced in facial biometrics since 2003 and NDK Android development since 2008
One of the pioneers of CUDA in Brazil, working with artificial neural networks and neurotechnology since 2009
Inventor of the CERTIFACE technology and the Linux HPC EXO AI platform
Delivered over 250 lectures, published 14 printed articles, and authored over 120 articles on Viva o Linux, reaching over 9 million views
Roles and recognitions:
Mentor at CybersecurityGirls BR
Guest lecturer at FIA
Official member and ambassador of openSUSE Linux Latin America
OWASP São Paulo Chapter Leader
Technical columnist and openSUSE Linux AWS engineer
Global Intel Innovator and Intel AI Community Council Member
Notable Member at I2AI
Member of the Data & AI Committee at ABINC
Advisory board member at ABRIA
Innovation Ambassador at Credicitrus
Innovation Advisor at Peck Advogados
Founding member of Instituto Fóton+ for Quantum Technologies
Global Intel Innovator Champion for 2024 and 2025

Partners

Social Project

In 2024, around 2.6 billion people still do not have access to the internet, according to data from the International Telecommunication Union (ITU). Digital inequality is more critical in regions of Africa, Asia, and Latin America.

The AI FOR ALL social project provides private AI, 100% offline, 100% free, with 3.2 billion parameters, on flash drives starting at 4GB—a true technological milestone.

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Contato

Contact

MultiCortex LLC

United States of America and Brazil

1207 Delaware Ave Wilmington DE 19806

Follow MultiCortex on Instagram:

www.instagram.com/multicortex