Best Laptops for AI in 2026: 13 Picks Ranked by GPU Memory

By Paul Syverson · Last updated Oct 20, 2026

The Lenovo ThinkPad P16 Gen 3 with an NVIDIA RTX PRO 5000 is our top pick for local AI work: its listing states 24GB of GPU memory, 128GB of system memory and 4TB of storage, so a mid-sized language model fits on the GPU and there is room for datasets and model files. If you need to carry it daily, the ROG Zephyrus G14 brings 12GB of GPU memory at a stated 1.57kg. Every pick was chosen from stated specifications and makers' published information; nobody at wikilaptop has used these units.

13 picks from 44 laptops that match this guide with a price we can quote today. Every price below is live and carries the moment it was read.

The picks at a glance

Which one should you buy?

• For the largest models a laptop GPU can hold: The ThinkPad P16 Gen 3 with the RTX PRO 5000 pairs 24GB of GPU memory with 128GB of system memory, so a model that outgrows the GPU still has somewhere to go. See pick 1
• For AI work you carry every day: The ROG Zephyrus G14 is the lightest laptop in the pool with 12GB or more of stated GPU memory, at 1.57kg, and its listing calls it a Copilot+ PC. See pick 9
• For 24GB without a heavy 18-inch chassis: This reseller configuration of the ASUS ProArt P16 puts an RTX 5090 with 24GB into a 16-inch laptop at a stated 1.85kg. See pick 3
• For models that spill into system memory: The Dell Precision 7780 has 12GB of GPU memory but 128GB of system memory and 4TB of storage, useful when a runtime splits a model between GPU and CPU. See pick 13

The 13 picks

1 Best overall

Lenovo ThinkPad P16 Gen 3 Intel Core Ultra 9 275HX

CPU

Intel Core Ultra 9 275HX

GPU

RTX PRO 5000

GPU memory

24 GB

RAM

128 GB

Storage

4000 GB

Screen

16 in

Refresh

120 Hz

Weight

2.54 kg

$8,299.00 (as of 10/20/2026 15:22 PDT - Details)

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It is the only pick that combines 24GB of GPU memory with 128GB of system memory and 4TB of storage. The RTX PRO 5000 is NVIDIA's professional line, and the Core Ultra 9 275HX is stated as a 24-core chip in the listing. The Legion 9i and ProArt P16 match its GPU memory but carry half the system memory.

Pros

• 24GB of GPU memory, tied for the most in this list
• 128GB of system memory, tied for the most in this list
• 4TB of storage for model files and datasets
• Stated weight of 2.54kg, lighter than both 18-inch picks

Cons

• Windows edition not stated by the seller
• Battery capacity not stated by the seller
• Heavier than the ProArt P16, which has the same GPU memory

Good fit if

• Engineers who run large language models locally for privacy or offline work
• Researchers who fine-tune small models and keep big datasets on the machine

Skip if

• You mainly call cloud AI services and never run models locally
• You carry your laptop all day and want to stay under 2kg

Verdict: The most complete local AI machine in the pool: top-tier GPU memory backed by the most system memory.

2 Best 18-inch with 24GB

Lenovo Legion 9i 18" WQUXGA IPS 240Hz Gaming Notebook Intel Core Ultra 9

CPU

Intel Core Ultra 9 290HX

GPU

GeForce RTX 5090

RAM

64 GB

Storage

2000 GB

Screen

18 in

Refresh

240 Hz

Weight

3.49 kg

$6,099.99 (as of 10/20/2026 15:21 PDT - Details)

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The Legion 9i pairs a GeForce RTX 5090 (24GB) with an Intel Core Ultra 9 290HX, 64GB of memory and 2TB of storage on an 18-inch screen. It is the maker's own configuration rather than a reseller build, which is why we chose it over the several RTX 5090 reseller listings in the pool.

Pros

• GeForce RTX 5090 with 24GB of GPU memory
• 18-inch screen, tied for the largest in this list
• Intel Core Ultra 9 290HX and 64GB of memory

Cons

• Stated weight of 3.49kg, the heaviest pick
• Windows 11 Home: Hyper-V cannot be installed
• 64GB of system memory, half of the ThinkPad P16 Gen 3

Good fit if

• Developers who want the largest screen with 24GB of GPU memory
• Anyone who keeps the laptop on a desk as a desktop replacement

Skip if

• You travel with your laptop
• Your workflow depends on Hyper-V virtual machines

Verdict: A desk-bound 24GB machine with the biggest screen here.

3 Lightest RTX 5090 pick

HIDevolution [2025] ASUS ProArt P16 H7606WX Black 16" 4K 120Hz OLED

CPU

AMD Ryzen AI 9 HX 370

GPU

RTX 5090

GPU memory

24 GB

RAM

64 GB

Storage

4000 GB

Screen

16 in

Refresh

120 Hz

Touchscreen

Yes

$6,199.00 (as of 10/20/2026 15:21 PDT - Details)

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This is a reseller configuration of the ASUS ProArt P16 with 64GB of memory and 4TB of storage. We include it because, at a stated 1.85kg, it is tied for the lightest RTX 5090 laptop in the pool with a stated weight, well below the 2.54kg to 3.49kg of the other 24GB picks.

Pros

• RTX 5090 with 24GB of GPU memory at a stated 1.85kg
• 4TB of storage and 64GB of memory
• AMD Ryzen AI 9 HX 370 and Windows 11 Pro
• 16-inch 4K OLED touchscreen, per the listing

Cons

• A reseller configuration, not a maker-configured unit
• Battery capacity not stated by the seller

Good fit if

• AI developers who travel but need 24GB of GPU memory
• Creators who run image generation models on an OLED screen

Skip if

• You prefer a laptop configured and sold as the maker built it
• You need more than 64GB of system memory

Verdict: The way to carry 24GB of GPU memory without an 18-inch chassis.

4 Only stated battery in the pool

Eluktronics HYDROC 16 G2R RTX 5090 Gaming Laptop

CPU

Intel Core Ultra 9 290HX

GPU

RTX 5090

GPU memory

24 GB

RAM

64 GB

Storage

4000 GB

Screen

16 in

Refresh

300 Hz

Weight

2.83 kg

$6,999.00 (as of 10/20/2026 15:21 PDT - Details)

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The Eluktronics HYDROC 16 is the one listing in the whole pool that states a battery capacity, 99Wh, and it pairs that with an RTX 5090 (24GB), an Intel Core Ultra 9 290HX, 64GB of memory and 4TB of storage. It sits between the ProArt P16 and the Legion 9i in weight.

Pros

• Stated 99Wh battery, the only stated capacity in the pool
• RTX 5090 with 24GB of GPU memory
• 4TB of storage and 64GB of memory
• Windows 11 Pro

Cons

• Stated weight of 2.83kg, nearly 1kg more than the ProArt P16
• 300Hz gaming panel, which adds nothing to model work

Good fit if

• Buyers who want a stated battery figure before they buy
• Developers who run inference on the go and then plug in

Skip if

• Weight is your first concern
• You want a workstation-class GPU and 128GB of memory

Verdict: A 24GB laptop that states its battery capacity, which almost no listing here does.

5 Best 16GB workstation

Lenovo ThinkPad P16 Gen 3

CPU

Intel Core Ultra 9 285HX

GPU

RTX PRO 4000

GPU memory

16 GB

RAM

128 GB

Storage

4000 GB

Screen

16 in

Refresh

120 Hz

Touchscreen

Yes

$7,899.00 (as of 10/20/2026 15:22 PDT - Details)

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This ThinkPad P16 Gen 3 uses the RTX PRO 4000 with 16GB of GPU memory, with the same 128GB of system memory and 4TB of storage as our top pick. It suits people who want the workstation platform but whose models fit in 16GB.

Pros

• RTX PRO 4000 with 16GB of GPU memory
• 128GB of system memory, tied for the most in this list
• 4TB of storage
• Windows 11 Pro and a touchscreen, per the listing

Cons

• 16GB of GPU memory, less than the 24GB picks
• Stated weight of 2.54kg
• Battery capacity not stated by the seller

Good fit if

• Teams that standardize on ThinkPad workstations
• Data scientists who train mid-sized models and need lots of system memory

Skip if

• You plan to run models that need more than 16GB of GPU memory
• You want a light machine

Verdict: The ThinkPad workstation for models that fit in 16GB.

6 Best RTX 5080 with 64GB

Lenovo Legion Pro 7i Gen 10 16" Gaming Laptop

CPU

Intel Core Ultra 9 275HX

GPU

GeForce RTX 5080

GPU memory

16 GB

RAM

64 GB

Storage

2000 GB

Screen

16 in

Refresh

240 Hz

OS

Windows 11 Pro

$4,398.00 (as of 10/20/2026 15:21 PDT - Details)

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The Legion Pro 7i Gen 10 states a GeForce RTX 5080 with 16GB, an Intel Core Ultra 9 275HX, 64GB of memory, 2TB of storage and Windows 11 Pro. It is the Lenovo gaming-line option in the 16GB tier.

Pros

• GeForce RTX 5080 with 16GB of GPU memory
• 64GB of system memory
• Windows 11 Pro
• Intel Core Ultra 9 275HX, stated as 24 cores

Cons

• Weight not stated by the seller
• Battery capacity not stated by the seller
• 2TB of storage, half of the MSI Vector 16 HX AI RTX 5080 pick

Good fit if

• Developers who run 7B to 13B class models locally in reduced precision
• Students who train models and also want a gaming laptop

Skip if

• You need to know the weight before you buy
• You need 24GB of GPU memory

Verdict: A strong 16GB GeForce machine from the maker, with room in memory for datasets.

7 Most storage among RTX 5080 picks

msi Vector 16 HX AI 16" QHD+ 240Hz Gaming Laptop

CPU

Intel Core Ultra 9 275HX

GPU

GeForce RTX 5080

GPU memory

16 GB

RAM

64 GB

Storage

4000 GB

Screen

16 in

Refresh

240 Hz

Weight

2.7 kg

$4,699.00 (as of 10/20/2026 15:22 PDT - Details)

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The MSI Vector 16 HX AI has the same 16GB RTX 5080 and 64GB of memory as the Legion Pro 7i but doubles storage to 4TB, and it states its weight (2.7kg). Model checkpoints and datasets add up quickly, so the extra drive space matters for local AI.

Pros

• 4TB of storage, double the Legion Pro 7i
• GeForce RTX 5080 with 16GB of GPU memory
• 64GB of memory and Windows 11 Pro

Cons

• Stated weight of 2.7kg
• Battery capacity not stated by the seller
• 240Hz gaming panel that model work does not use

Good fit if

• Developers who keep many model versions on the laptop
• Anyone who works with large image or audio datasets

Skip if

• You want a laptop under 2.5kg
• You need workstation drivers from a professional GPU

Verdict: The 16GB pick with the most room for model files.

8 16GB on a 17.3-inch screen

GIGABYTE - AORUS 17X

CPU

Intel Core i9-14900HX

GPU

GeForce RTX 4090

GPU memory

16 GB

RAM

32 GB

Storage

2000 GB

Screen

17.3 in

Refresh

240 Hz

Weight

2.8 kg

$3,429.21 (as of 10/20/2026 15:21 PDT - Details)

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The AORUS 17X uses the previous-generation GeForce RTX 4090 laptop GPU, which also has 16GB of memory, with an Intel Core i9-14900HX, 32GB of memory and 2TB of storage. It is the only 17-inch class pick in the 16GB tier.

Pros

• GeForce RTX 4090 with 16GB of GPU memory
• 17.3-inch QHD screen, per the listing
• 2TB of storage

Cons

• 32GB of system memory, the lowest tier in this list
• Windows 11 Home
• A 2024 model with a previous-generation GPU

Good fit if

• Anyone who wants 16GB of GPU memory with a large screen
• Developers who mostly run inference rather than large data jobs

Skip if

• You need 64GB or more of system memory
• You want the current GPU generation

Verdict: A large-screen 16GB option, held back by 32GB of system memory.

9 Lightest with 12GB or more

ASUS ROG Zephyrus G14 14" 3K OLED 120Hz Copilot+ PC Gaming Laptop

CPU

AMD Ryzen AI 9 HX 370

GPU

GeForce RTX 5070 Ti

GPU memory

12 GB

RAM

32 GB

Storage

1000 GB

Screen

14 in

Refresh

120 Hz

Weight

1.57 kg

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At a stated 1.57kg, the Zephyrus G14 is the lightest laptop in the pool with 12GB or more of GPU memory, from its GeForce RTX 5070 Ti. Its AMD Ryzen AI 9 HX 370 and the Copilot+ PC label in its listing also cover the Windows NPU features.

Pros

• Stated weight of 1.57kg, the lightest in this list
• GeForce RTX 5070 Ti with 12GB of GPU memory
• Copilot+ PC per the listing title
• 14-inch 3K OLED at 120Hz, per the listing

Cons

• 32GB of system memory and 1TB of storage, the lowest tier here
• Windows edition not stated beyond Windows 11

Good fit if

• Students and developers who carry their laptop every day
• Anyone who wants both CUDA and the Copilot+ features

Skip if

• You need more than 12GB of GPU memory
• You keep large datasets locally

Verdict: The portable entry point to local AI with CUDA.

10 Best 12GB all-rounder

Acer Predator Helios Neo 16S AI Gaming Laptop

CPU

Intel Core Ultra 9 275HX

GPU

RTX 5070 Ti

GPU memory

12 GB

RAM

64 GB

Storage

2000 GB

Screen

16 in

Refresh

240 Hz

Weight

2.3 kg

View on Amazon

The Predator Helios Neo 16S AI pairs a 12GB RTX 5070 Ti with 64GB of memory, 2TB of storage and Windows 11 Pro at a stated 2.3kg. No other 12GB pick offers 64GB of memory under 2.5kg.

Pros

• 64GB of memory at a stated 2.3kg
• RTX 5070 Ti with 12GB of GPU memory
• 2TB of storage and Windows 11 Pro
• 16-inch 2.5K OLED, per the listing

Cons

• 12GB of GPU memory limits model size
• Battery capacity not stated by the seller

Good fit if

• Developers who mix model work with heavy multitasking
• Buyers who want Windows 11 Pro on a 12GB laptop

Skip if

• You need 16GB or more of GPU memory
• You want the lightest 12GB option (the Zephyrus G14)

Verdict: The balanced 12GB choice: plenty of system memory in a manageable weight.

11 Largest screen with 12GB

ASUS ROG Strix G18 18” Gaming Laptop

CPU

Intel Core Ultra 9 275HX

GPU

RTX 5070 Ti

GPU memory

12 GB

RAM

32 GB

Storage

2000 GB

Screen

18 in

Refresh

240 Hz

Weight

3 kg

$3,199.99 (as of 10/20/2026 15:20 PDT - Details)

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The ROG Strix G18 puts a 12GB RTX 5070 Ti on an 18-inch screen with an Intel Core Ultra 9 275HX, 32GB of memory and 2TB of storage. It suits people who want a big display for notebooks and dashboards and whose models fit in 12GB.

Pros

• 18-inch screen, tied for the largest in this list
• RTX 5070 Ti with 12GB of GPU memory
• 2TB of storage

Cons

• Stated weight of 3kg
• Windows edition not stated by the seller
• 32GB of system memory

Good fit if

• Developers who work at a desk and want a large screen
• Learners running small and quantized models

Skip if

• You carry the laptop often
• You need more than 32GB of system memory

Verdict: A big-screen 12GB machine for desk work.

12 Best AMD Ryzen 9 pick

msi Vector 16 HX AI 16" 240Hz QHD+ Gaming Laptop

CPU

AMD Ryzen 9 8940HX

GPU

GeForce RTX 5070 Ti

GPU memory

12 GB

RAM

32 GB

Storage

1000 GB

Screen

16 in

Refresh

240 Hz

Weight

2.7 kg

View on Amazon

The Vector 16 HX AI in this configuration uses an AMD Ryzen 9 8940HX with a 12GB RTX 5070 Ti, 32GB of memory and 1TB of storage. It is the only Ryzen 9 HX processor among our picks, for buyers who prefer AMD.

Pros

• AMD Ryzen 9 8940HX processor
• RTX 5070 Ti with 12GB of GPU memory
• 16-inch 240Hz QHD+ screen, per the listing

Cons

• 32GB of memory and 1TB of storage
• Stated weight of 2.7kg
• Windows edition not stated beyond Windows 11

Good fit if

• Buyers who prefer an AMD processor with an NVIDIA GPU
• Students starting with small models

Skip if

• You need room for large datasets
• You want 64GB of memory with 12GB of GPU memory (see the Predator)

Verdict: A straightforward 12GB CUDA laptop with an AMD processor.

13 Most system memory with 12GB

Dell Precision 7780 Laptop

CPU

Intel Core i9-13950HX

GPU

RTX 3500 Ada

GPU memory

12 GB

RAM

128 GB

Storage

4000 GB

Screen

17.3 in

Weight

3.05 kg

OS

Windows 11 Pro

$6,299.99 (as of 10/20/2026 15:21 PDT - Details)

View on Amazon

The Precision 7780 uses the RTX 3500 Ada, a previous-generation professional GPU with 12GB, but backs it with 128GB of memory and 4TB of storage and an Intel Core i9-13950HX. That makes it a fit for runtimes that can keep part of a model in system memory.

Pros

• 128GB of system memory, tied for the most in this list
• 4TB of storage
• Professional RTX 3500 Ada GPU with 12GB
• Windows 11 Pro

Cons

• Stated weight of 3.05kg
• Previous-generation (Ada) GPU
• Battery capacity not stated by the seller

Good fit if

• Engineers who work with large datasets and moderate models
• Companies that standardize on Dell Precision workstations

Skip if

• You need 16GB or more of GPU memory
• You want the current GPU generation

Verdict: A memory-heavy workstation for AI work where system memory matters more than GPU size.

Side by side

How we picked

How we picked: 62 laptops in our catalogue matched this guide's rule, a listing that states a graphics card with 12GB of memory or more, because GPU memory is what limits the size of model you can load. We set aside listings that leave GPU memory out or state less than 12GB. We preferred established makers in new condition; many matching listings are reseller builds that add memory and storage to a maker's laptop, and we took one of those only where nothing else matched it (the lightest RTX 5090 option). We dropped near-duplicates of the same model and then chose machines across three GPU memory tiers: 4 picks with 24GB, 4 with 16GB and 5 with 12GB. Prices on this page are live and read from the store listing with the time shown. Nobody tested these units: the ranking compares stated specifications with the published requirements of AI frameworks.

How to choose

GPU memory decides which models fit

A model's weights must sit in memory while it runs. Hugging Face describes weights stored in full precision (32-bit), half precision (16-bit) or reduced integer formats such as 8-bit and 4-bit. At 16-bit each parameter takes 2 bytes, so an 8-billion-parameter model needs about 16GB for its weights alone; at 4-bit the same model needs about 4GB. The context window and the runtime need memory on top of that.

That is why this list is grouped by GPU memory: 4 picks have 24GB, 4 have 16GB and 5 have 12GB. NVIDIA states 24GB for the GeForce RTX 5090 laptop GPU, 16GB for the RTX 5080 and 12GB for the RTX 5070 Ti. If you are unsure which tier you need, buy more GPU memory rather than a faster processor.

System memory: where models go when the GPU is full

Some runtimes, including llama.cpp through the GGUF format, can run on the CPU as well as the GPU, so part of a model can live in system memory when it does not fit on the GPU. That makes system memory the second number to check. In this list, 3 picks have 128GB, 6 have 64GB and 4 have 32GB.

System memory also holds your datasets, notebooks and containers. If you run Linux tools through WSL 2, Microsoft sets the WSL virtual machine to half of Windows memory by default.

Why every pick has an NVIDIA GPU

PyTorch and most AI tooling support NVIDIA GPUs through the CUDA platform. NVIDIA's cuDNN support matrix lists Windows 10, Windows 11 and Linux, and NVIDIA supports CUDA inside WSL 2 with only the Windows driver installed, so a Windows laptop can run the same Linux-based AI tooling.

Macs take a different path: PyTorch's MPS backend runs on Apple silicon GPUs under macOS 14 or later, using the Mac's unified memory. No MacBook is in this pool because the rule here is a stated discrete GPU with 12GB or more; see our data science guide if a Mac suits your work better.

NPUs and the Copilot+ PC label

Microsoft defines Copilot+ PCs as Windows 11 laptops with an NPU that can perform more than 40 trillion operations per second (TOPS). The NPU runs Windows AI features and models converted for it, often to 8-bit integer formats, through Windows ML and ONNX Runtime.

For running and training your own models with PyTorch, the NVIDIA GPU does the heavy work. Treat the NPU as a battery-friendly extra, not as a replacement for GPU memory. Among our picks, the Zephyrus G14 listing states the Copilot+ PC label.

Weight, screen and battery

Big GPUs bring weight. Stated weights in this list run from 1.57kg (Zephyrus G14) to 3.49kg (Legion 9i 18), and one pick, the Legion Pro 7i, does not state a weight. Only one listing in the whole pool states a battery capacity: the Eluktronics HYDROC 16, at 99Wh.

High refresh rates of 240Hz or 300Hz come from the gaming side of these machines and do nothing for model work; screen size and resolution matter more if you spend the day in notebooks.

Questions

Can a laptop run a large language model locally?

Yes, if the model fits in memory. At 16-bit precision each parameter takes 2 bytes, so an 8-billion-parameter model needs about 16GB for weights, which fits on the 24GB picks here and is tight on 16GB. Reduced-precision formats such as 4-bit shrink that to about a quarter, so larger models become possible on 12GB and 16GB GPUs, with some loss of accuracy.

Is 12GB of GPU memory enough for AI?

For learning, small models and quantized models in the 7B to 8B range, 12GB is a workable start. It gets tight for 16-bit models of that size, for image generation at high resolution and for fine-tuning. If you expect to grow into larger models, the 16GB or 24GB picks give you room without changing laptops.

Do I need a Copilot+ PC or an NPU for AI work?

Not for running your own models with PyTorch or similar frameworks; those use the NVIDIA GPU. Microsoft's Copilot+ label requires an NPU above 40 TOPS and unlocks Windows AI features and NPU-targeted apps. It is useful for battery-friendly features, but it does not replace GPU memory for local model work.

Mac or Windows laptop for AI?

Choose Windows with an NVIDIA GPU if your tools depend on CUDA, which covers most training code and many inference tools; NVIDIA supports CUDA inside WSL 2 as well. Choose a Mac if you mainly run models and value unified memory; PyTorch supports Apple GPUs through its MPS backend on macOS 14 or later. This pool only contains laptops with a discrete GPU, so no Macs appear here.

Should I train models on a laptop at all?

For experiments, fine-tuning small models and running inference, a laptop with enough GPU memory works and keeps data on your machine. Long training runs on large models belong on desktop or cloud GPUs with more memory and cooling. Many developers prototype locally on a laptop like these and move the big jobs elsewhere.

Is a desktop worth considering for AI work?

This site covers laptops only. When the work does not need to travel, look at a laptop and desktop comparison for AI work before you decide; it lists both kinds of machine, each price with the moment it was read.

Recent updates

• 2026-09-28: Added a question on choosing a desktop instead.
• 2026-09-28: First published.

Sources

• NVIDIA: GeForce RTX 50 Series laptops (GPU memory per model)
• NVIDIA: cuDNN support matrix (operating systems and GPU architectures)
• NVIDIA: CUDA on WSL user guide
• PyTorch: MPS backend (Apple silicon, macOS 14 or later)
• Microsoft Learn: Copilot+ PCs developer guide (40+ TOPS NPU)
• Microsoft Learn: Advanced settings configuration in WSL (default memory)
• Hugging Face Transformers: Quantization overview (precision formats)