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NVIDIA

NVIDIA GeForce RTX 5090 Laptop GPU

24 GB • Blackwell • 95-150 W

24 GBMemory
BlackwellArchitecture
95-150 WPower
KACBU

Should I buy it?

NVIDIA GeForce RTX 5090 Laptop GPU
CONSIDER
  • Current model — 19 months on the market
Great choice if these matter:
  • Gaming
  • Content Creation
  • Work / Productivity
Watch out for:
  • The 95-150W range is a 58% spread — two laptops with this exact GPU can differ enormously in real performance.
  • Despite the name it uses the GB203 die, not the desktop RTX 5090's GB202: this is a different, smaller chip.
19 months on the market
Regret riskLOWlimited data
Main risks
  • The 95-150W range is a 58% spread — two laptops with this exact GPU can differ enormously in real performance.
  • Despite the name it uses the GB203 die, not the desktop RTX 5090's GB202: this is a different, smaller chip.
  • Only appears in large, heavy chassis that can feed and cool 150W.
  • Battery gaming performance falls far below plugged-in performance.
The risk level is computed from the release date and verified weaknesses. The confidence score appears only once enough owner reports exist.
This box relies only on verified specs, the release date and editorial assessment; owner reports join them as they come in. We do not predict prices.
What NVIDIA SaysGPUMemoryPowerLaunchSpecificationsFAQAlternatives
Official Statement

What does NVIDIA say about the product?

A summary of NVIDIA's official product description.

Official NVIDIA source

NVIDIA positions the RTX 50 Laptop GPUs around doubled frame rates and halved workflow times.

Announced at CES on January 6, 2025, the GeForce RTX 5090 Laptop GPU leads the mobile Blackwell line with 10,496 CUDA cores and 24GB of GDDR7 memory, at a manufacturer-configurable power range of 95-150W.

“Game with double the FPS. Create content and complete workflows in half the time. And finish generative AI tasks 2.5X faster.”
Open NVIDIA's official statement
Graphics Processor

What's inside the card's core?

Manufacturer's official processing unit and architecture information.

GRAPHICS PROCESSOR

The actual hardware that determines frame rate.

10496 Processing Unit

Blackwell — Architecture · 10496 — Shading Unit

Blackwell10496
BlackwellArchitecture
10496Shading Unit
Memory

How much and what speed memory?

Values decisive at high resolutions and high textures.

MEMORY

This determines the limit in 4K and high texture settings.

24 GB Memory

24 GB — GDDR7 · 256 bit — Memory bus

24 GB256 bit
24 GBGDDR7
256 bitMemory bus
Power and Cooling

How much power does it draw?

Official values determining power supply and case selection.

POWER AND COOLING

These values determine the power supply budget.

95-150 W

95-150 W — Card Power Consumption

95-150 W
95-150 WCard Power Consumption
Who Is It For?

Where does it stand out?

A usage guide built from the specs and the editors' tags; not a test result.

Gaming

For gaming; tagged from the display's refresh rate and the chip's class. We have not measured frame rates or heat ourselves.

Good fit
Content Creation

For creators who need professional video formats and fast transfer.

Good fit
Work / Productivity

For heavy work use; tagged from the battery and display specs. We have not timed the battery ourselves.

Good fit
Editorial Analysis

Strengths and points to consider

The 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.

Strengths based on the specs
24GB of GDDR7 is the largest memory pool in any laptop GPU, opening up local AI models and 8K editing.
10,496 CUDA cores with full DLSS 4 multi-frame generation support.
Blackwell's neural rendering features arrive on laptops with this generation.
Even at the low end of its power range it outperforms every previous-generation laptop GPU.
Things to consider
The 95-150W range is a 58% spread — two laptops with this exact GPU can differ enormously in real performance.
Despite the name it uses the GB203 die, not the desktop RTX 5090's GB202: this is a different, smaller chip.
Only appears in large, heavy chassis that can feed and cool 150W.
Battery gaming performance falls far below plugged-in performance.
Historical Product Info

Official launch details

Instead of tracking today's retail price, Kacbu keeps the product's official launch information as a reference.

AnnouncedJanuary 6, 2025

The manufacturer's official announcement date.

ReleaseMarch 1, 2025

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.

This is not the current retail price — it shows the product's historical, official launch information.
Specifications

NVIDIA GeForce RTX 5090 Laptop GPU specifications

Click a linked value to see other products that share that same spec, and leave a comment on that spec.

General

Family
GeForce RTX 50 Laptop
Release Year
2025
Manufacturer

Graphics Processor

GPU Chip
GB203
Manufacturing Process
TSMC 4N
Architecture
Shading Units

Memory

Memory Bus
Memory Size
Memory Type

Power

Board Power
TGP Note
Varies by laptop manufacturer's configuration
FAQ

The most common questions about this product

What the numbers on the spec sheet actually mean in day-to-day use.

Is this the same as a desktop RTX 5090?
No, and the naming hides a real difference. The desktop RTX 5090 uses the much larger GB202 die with 21,760 CUDA cores and 32GB of memory at 575W. This laptop chip is a GB203 with 10,496 cores at 95-150W. It is an excellent laptop GPU, but it is roughly half the desktop card.
Why does the power range matter so much?
Because it is the single biggest variable in laptop GPU performance. The same RTX 5090 Laptop GPU at 150W can deliver far more than at 95W. Every laptop we list records its actual TGP, because the GPU name alone does not tell you what you are buying.
What is 24GB of memory useful for?
Beyond gaming, it is what allows large local AI models, 8K video timelines and heavy 3D scenes to fit entirely in graphics memory. For pure gaming it is more than current titles need — the value is in creative and AI workloads that no other laptop GPU can hold in memory.
Shared Hardware

Products that share this hardware

This product's standout specs. You can jump to other models that use the same value.

Alternatives

Other models in the same category

Other products in the same category.

Products using this part

6 models with the NVIDIA GeForce RTX 5090 Laptop GPU

Models built on the same part. The difference is not the part — it is the device around it.

See them all on the Graphics page
Local AI

Which models run on this card?

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.

VRAM: 24 GB

Largest model that runs comfortably: gpt-oss-20b

  • Qwen3.5 0.8B1 GB packageComfortable
  • Qwen3.5 2B2.7 GB packageComfortable
  • Qwen3.5 4B3.4 GB packageComfortable
  • Qwen3.5 9B6.6 GB packageComfortable
  • gpt-oss-20b14 GB package · the maker states a 16 GB memory minimumComfortable
  • Qwen3.5 27B17 GB packageRuns
  • Qwen3.5 35B24 GB packageLimited
  • gpt-oss-120b65 GB package · the maker states a 80 GB memory minimumNot suitable
  • Qwen3.5 122B81 GB packageNot suitable
  • ComfortableRoom for the model file and a long context
  • RunsFits; the context window may need to stay short
  • LimitedNot enough memory; part of the model spills to system RAM and runs slowly
  • Not suitableNot a GPU-run model on this card

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

All cards and models