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NVIDIA GeForce RTX 4080 Laptop GPU for local LLMs

Written by Jakub Rusinowski · Last updated

With 12 GB of GDDR6 at 432 GB/s, the RTX 4080 Laptop GPU runs 76 catalogued models at Q4_K_M with 8K context. The largest that fits is Qwen 3 14B (~11.1 GB), and the top pick is Cosmos 3 Nano at 38–73 tok/s.

12 GB of GDDR6 on a 192-bit bus, 432 GB/s. Not the 16 GB desktop RTX 4080. Power depends on the chassis and is not stored.

Models that run on the RTX 4080 Laptop GPU

Q4_K_M, 8K context, 12 GB usable. Ranked by quality and speed.

ModelVRAMSpeed
Cosmos 3 Nano
Cosmos 3
10.5 GB38–73 tok/s
Ministral 3 14B
Ministral 3
9.3 GB26–49 tok/s
DeepSeek R1 Distill Qwen 14B
DeepSeek R1
10.6 GB26–49 tok/s
Mellum2.1 12B Thinking
Mellum2.1
9 GB109–209 tok/s
Gemma 4 12B (Unified)
Gemma 4
8.7 GB31–60 tok/s
Mistral NeMo 12B
Mistral Family
9.4 GB29–56 tok/s
Gemma 3 12B Instruct
Gemma 3
9.1 GB30–57 tok/s
Bielik PL 11B v3.0 Instruct
Bielik
7.4 GB31–60 tok/s
Llama 3.2 Vision 11B
Llama 3.2 Vision
8.5 GB32–61 tok/s
Llama 3.2 11B Vision Instruct
Llama 3.2 Family
8.5 GB32–61 tok/s
Falcon 3 10B Instruct
Falcon 3
8.4 GB32–62 tok/s
Qwen 3.5 9B
Qwen 3.5
6.6 GB41–79 tok/s
Showing 12 of 76

Buy it or rent the same memory

Buy the card, or rent a GPU with the same memory by the hour to try models first.

Speed vs other GPUs

Llama 3.1 8B, Q4_K_M. Estimated ranges. How this is calculated

Specifications

Specs last updated 2026-10-07.

Memory
12 GB GDDR6
Memory bandwidth
432 GB/s
Memory bus
192-bit
Architecture
Ada Lovelace AD104
Series
RTX 40-series (Laptop)
Release year
2023
Compute backends
CUDA
Usable for models
12 GB
Best for12 GB laptop AI

Similar GPUs

Frequently asked questions

Can the NVIDIA GeForce RTX 4080 Laptop GPU run local LLMs?

Yes. With 12 GB (12 GB usable by a model) it runs 76 of the catalogued models at Q4_K_M with 8K context; the largest is Qwen 3 14B, needing about 11.1 GB.

How fast is the NVIDIA GeForce RTX 4080 Laptop GPU for AI inference?

It is estimated to run Llama 3.1 8B at 44–84 tok/s at Q4_K_M. Llama 3.3 70B does not fit: it needs about 44 GB against 12 GB usable. These are modelled estimates from memory bandwidth, not measurements; the methodology page shows the formula.

What LLMs can I run on 12 GB?

Among the best that fit: Cosmos 3 Nano, Ministral 3 14B, DeepSeek R1 Distill Qwen 14B, Mellum2.1 12B Thinking, Gemma 4 12B (Unified).