Best Laptops for Running Large Language Models in 2024

Large language models (LLMs) are powerful AI tools that can be used for a variety of tasks, including conversation, roleplay, text generation, and many other things related to language. However, LLMs can be very demanding on hardware, so it is important to choose the right laptop for running them.

The most important factor to consider when choosing a laptop for running LLMs is the amount of VRAM (video RAM) available. LLMs typically require at least 10GB of VRAM to run comfortably, but 8 GB can also work. If you are on a budget, there are some laptops available with less VRAM, but they may not be able to run LLMs as quickly or efficiently.

In addition to VRAM, you will also need to consider the other specifications of your laptop, such as the processor, RAM, and storage. LLMs can be very demanding on processing power, so you will need a laptop with a decently powerful processor. You will also need a laptop with at least 16GB of RAM that will make your laptop do many more tasks comfortably. Finally, you will need a laptop with a large storage drive to store the LLM models.

Once you have considered all of these factors, you can start shopping for a laptop that is suitable for running LLMs. There are many different laptops available, so you should be able to find one that meets your needs and budget.

In this article, we explore the top laptops in the market designed for running these models. Discover the features and specifications that set these laptops apart and empower you to push the boundaries of AI innovation.

Related: Best Budget GPU For LLM

Best Laptop For Running LLM

MSI GF65 Thin

The MSI GF65 Thin is a powerful laptop that offers excellent performance for running large language models. Equipped with an NVIDIA GeForce RTX 3060 graphics card, this laptop provides the necessary graphical processing power required for the comfortable usage of large language models. With a dedicated graphics coprocessor and a minimum of 8GB of video RAM, the GF65 Thin meets the requirements to handle models ranging from 7 billion to 13 billion parameters.

Key Features:

• Display: The 15.6-inch screen of the MSI GF65 Thin boasts a maximum resolution of 1920 x 1080 pixels, ensuring crisp and clear visuals while working with large language models.
• Processing Power: Powered by an Intel Xeon Platinum 8160M processor running at 2.5 GHz, the laptop delivers high-performance computing, enabling the smooth handling of complex language models.
• Memory and Storage: With 8GB DDR4 RAM operating at 3200 MHz, the GF65 Thin provides sufficient memory capacity for running large language models effectively. Additionally, it comes equipped with a 512GB SSD, offering fast and ample storage space to accommodate the models and associated data.
• Connectivity: The laptop supports 802.11ax wireless connectivity, ensuring fast and reliable internet access for downloading language models and accessing online resources.
• Portability: Weighing just 4.18 pounds and measuring 0.84 inches thin, the MSI GF65 Thin is a lightweight and portable option, making it convenient to carry around for on-the-go work.

Considerations: While the MSI GF65 Thin meets the minimum requirements for running large language models, it’s important to note that it falls at the lower end of the recommended VRAM capacity. It provides 8GB of video RAM, which may limit its performance when handling more demanding language models or tasks that heavily rely on GPU acceleration. However, for small to medium-sized models within the 7 billion to 13 billion parameter range, the GF65 Thin offers a decent solution.

Expectations: The MSI GF65 Thin provides a balance between performance and affordability, making it suitable for users who primarily work with small to medium-sized language models. You can expect smooth multitasking, efficient model processing, and quick storage access for a productive workflow. However, for larger models or more GPU-intensive tasks, you may experience limitations due to the 8GB video RAM. Overall, the MSI GF65 Thin is a reliable option for running language models within its capacity.

Acer Nitro 17 Gaming Laptop

The Acer Nitro 17 Gaming Laptop is a robust option for running large language models, offering a spacious 17.3-inch display and impressive hardware specifications. With a powerful AMD Ryzen 7 processor clocked at 4.75 GHz, this laptop delivers high-speed performance ideal for handling language models in the range of 7 billion to 13 billion parameters.

Key Features:

• Display: The Acer Nitro 17 features a large 17.3-inch screen with a maximum resolution of 2560 x 1440 pixels, providing an immersive visual experience while working with large language models.
• Processing Power: Powered by an AMD Ryzen 7 processor, this laptop offers a clock speed of 4.75 GHz, ensuring efficient processing of complex language models and enabling smooth multitasking.
• Memory and Storage: With 16GB DDR5 RAM, the Acer Nitro 17 provides ample memory capacity to handle large language models effectively. Additionally, it comes equipped with a 1TB SSD, offering both speed and generous storage space to accommodate the models and associated data.
• Graphics Capability: The laptop features an NVIDIA GeForce RTX 4070 graphics card with 8GB of dedicated video RAM, providing sufficient graphics power for the comfortable execution of large language models.
• Connectivity: The Acer Nitro 17 supports Bluetooth and 802.11ax wireless connectivity, ensuring seamless internet access and data transfer while working with language models.
• Port Selection: With one USB 2.0 port and four USB 3.0 ports, the laptop offers ample options for connecting peripherals and external storage devices.

Considerations: The Acer Nitro 17 is well-equipped to handle medium-sized language models within the 7 billion to 13 billion parameter range. However, it’s important to note that the laptop falls slightly short of the recommended 10GB of video RAM for optimal performance with larger models. While the 8GB of video RAM is capable, it may limit the laptop’s performance when dealing with more demanding language models or GPU-intensive tasks.

Expectations: The Acer Nitro 17 Gaming Laptop provides a spacious display, powerful processing capabilities, and sufficient memory and storage for running large language models comfortably. You can expect smooth and efficient execution of models within their capacity, enabling productive workflow and multitasking. Although it may face limitations with larger models, the Nitro 17 offers an overall reliable performance for running language models in the medium-sized range.

ASUS ROG Zephyrus S17 (2021)

ASUS ROG Zephyrus S17 (2021) is a high-performance machine specifically designed to handle the demands of running large language models. With its impressive specifications and robust hardware, this laptop provides a powerful computing environment for researchers, data scientists, and AI enthusiasts.

Key Features:

• Display: The laptop features a large 17.3-inch screen with a resolution of 2560 x 1440 pixels, offering a spacious and immersive workspace for working with complex language models.
• Processing Power: Powered by an Intel Core i9 processor clocked at 4.9 GHz, the Acer Nitro 17 delivers exceptional processing performance, allowing for swift and efficient execution of demanding language models.
• Memory and Storage: With 32 GB of DDR4 RAM operating at 3200 MHz, this laptop offers ample memory capacity to handle large language models with ease. Furthermore, it is equipped with a spacious 2 TB SSD, providing substantial storage space to store not only the models but also associated datasets.
• Graphics Capability: ASUS ROG Zephyrus S17 features the powerful NVIDIA GeForce RTX 3080 graphics card with 16 GB of dedicated video RAM. This ensures smooth GPU acceleration for running large language models comfortably and efficiently.
• Connectivity: The laptop supports Bluetooth and 802.11ax wireless connectivity options, enabling seamless internet access and fast data transfers.
• Portability: Although the ROG Zephyrus is not the most lightweight option, it offers a portable solution for those who require mobility while working on large language models.

Considerations: ASUS ROG Zephyrus S17 (2021) provides an excellent hardware configuration for running large language models. However, it’s important to note that the laptop’s weight and size might make it less ideal for frequent travel or on-the-go usage. Additionally, while the laptop’s GPU specifications are powerful, some of the largest language models with billions of parameters might still require more VRAM for optimal performance.

Expectations: With the ASUS ROG Zephyrus S17 (2021), you can expect exceptional performance when working with small to medium-sized language models, typically within the 7 billion to 13 billion parameter range. The substantial RAM capacity and ample storage space ensure smooth model processing and efficient handling of associated data. The powerful GPU, featuring the NVIDIA GeForce RTX 3080, offers excellent acceleration for large language models, contributing to faster training and inference times. Overall, the Acer Nitro 17 is a reliable and capable choice for running large language models, providing a seamless and productive experience for users in the field of AI and natural language processing.

HP OMEN 17t

The HP OMEN 17t 17.3 is a high-performance laptop specifically designed to handle the demands of running large language models. With its powerful hardware and impressive specifications, this laptop offers exceptional capabilities for users working with extensive language models.

Key Features:

• Display: The laptop features a 17.3-inch 2K Quad HD (2560×1440) IPS display with a 240Hz refresh rate, providing sharp and smooth visuals, which is advantageous when analyzing and generating large language models.
• Processing Power: Equipped with a 13th Gen Intel Core i9-13900HX processor, the OMEN 17t offers a base clock speed of 2.20GHz that can reach up to 5.4GHz when boosted. With 24 cores and 32 threads, this laptop delivers powerful computing performance, allowing for the efficient handling of complex language models.
• Graphics: The OMEN 17t features the NVIDIA GeForce RTX 4090 with 16GB GDDR6X VRAM, providing ample graphical processing power. This allows for the comfortable execution of large language models and enables users to work with more substantial models beyond the 7 billion to 13 billion parameter range.
• Memory and Storage: With a massive 64GB DDR5 SODIMM RAM, this laptop ensures smooth multitasking and efficient model processing. It also offers substantial storage capacity with a 2TB PCIe NVMe SSD, providing ample space to store large language models and related data.
• Connectivity and Ports: The OMEN 17t includes essential connectivity options such as Wi-Fi 6E, Bluetooth 5.3, Ethernet LAN (RJ-45), HDMI, mini DisplayPort, Thunderbolt 4 (Type-C), and an SD card reader. These connections enable fast data transfer and easy integration with external devices.
• Operating System: The laptop comes with Windows 11 Home-64 pre-installed, offering a user-friendly interface and compatibility with the latest software and tools.

Considerations: The HP OMEN 17t 17.3 is a high-end laptop suitable for running large language models. However, it’s important to note that the laptop’s specifications far exceed the minimum requirements for most language models. It may be more suitable for users working with exceptionally large models or requiring extensive computational resources. Additionally, the laptop’s size and weight may limit its portability compared to smaller and lighter options.

Expectations: With its top-of-the-line hardware and robust specifications, the HP OMEN 17t 17.3 provides exceptional performance for running large language models. Users can expect smooth and efficient processing, effortless multitasking, and the ability to handle more substantial models beyond the typical parameter range. The ample storage capacity allows for storing multiple models and associated data. Overall, this laptop is well-suited for professionals and researchers who require significant computational power and storage capabilities for their language modeling tasks.