Global Graphics Cards
NVIDIA
NVIDIA GeForce RTX 5080 Laptop GPU
16 GB • Blackwell • 80-150 W
16 GBMemory
BlackwellArchitecture
80-150 WPower
16 GB • Blackwell • 80-150 W
A summary of NVIDIA's official product description.
Announced at CES on January 6, 2025, the GeForce RTX 5080 Laptop GPU pairs 7,680 CUDA cores with 16GB of GDDR7 memory on a 256-bit bus, at a manufacturer-configurable power range of 80-150W.
Manufacturer's official processing unit and architecture information.
Blackwell — Architecture · 7680 — Shading Unit
Values decisive at high resolutions and high textures.
16 GB — GDDR7 · 256 bit — Memory bus
Official values determining power supply and case selection.
80-150 W — Card Power Consumption
A usage guide built from the specs and the editors' tags; not a test result.
For gaming; tagged from the display's refresh rate and the chip's class. We have not measured frame rates or heat ourselves.
Good fitAn editor's tag for hardware that is well priced for what it offers. We do not track current prices; check the price before you buy.
Good fitThe Kacbu editors' assessment of the specifications the maker publishes. We do not test devices ourselves, so nothing here is a measured result. Anything taken from an independent review is shown with its publication and date in the Press section.
Instead of tracking today's retail price, Kacbu keeps the product's official launch information as a reference.
The manufacturer's official announcement date.
The start of the initial sales period.
NVIDIA is headquartered in the US and designs the GPU there; it does not fabricate it itself — the GB203 die is made at TSMC's fabs in Taiwan. Laptop integration is done by each notebook manufacturer.
Click a linked value to see other products that share that same spec, and leave a comment on that spec.
What the numbers on the spec sheet actually mean in day-to-day use.
Other products in the same category.
Models built on the same part. The difference is not the part — it is the device around it.
Whether a model runs on your machine is decided first by the graphics card's memory: the model file has to fit in VRAM with room left for the context window and the runtime. The states below are computed from memory alone; software support (CUDA, ROCm, Vulkan) is a separate matter.
Largest model that runs comfortably: Qwen3.5 9B
Rule: 1.5× the requirement in memory is Comfortable, 1.15× Runs, 0.6× Limited; the requirement is the default package size, or the maker's stated minimum where there is one (a stated minimum counts as fitting at exactly that figure). Package sizes are the Ollama library's, minimums the maker's own statement; read on 2026-09-11. Sources: ollama.com/library/qwen3.5, ollama.com/library/gpt-oss, openai.com/index/introducing-gpt-oss