NVIDIA GeForce RTX 4060 Laptop GPU — Local LLM Performance & Compatibility

Written by Jakub Rusinowski · Last updated September 19, 2026

8 GB GDDR6 on a 128-bit bus: 256 GB/s, against the desktop RTX 4060's 272 GB/s. Configurable from 35 W to 115 W, a range wide enough that the same model number performs very differently between thin and thick chassis.

Technical Specifications

VRAM8 GB
Memory Bandwidth256 GB/s
TDP115 W
ArchitectureAda Lovelace AD107
Release Year2023
MSRP at Launch$0
Inference Speed (Llama 3.1 8B Q4_K_M)28–53 tok/s (estimated)
Inference Speed (Llama 3.3 70B Q4_K_M)Does not fit — needs ~44 GB of 8 GB usable
Buy This HardwareIntel Arc B570 10GB — 10 GB VRAM · 150 W board powerDeploy in the Cloud NowRTX 4090 on RunPod — from $0.34/hr · rate checked 2026-07

or compare on Vast.ai from $0.35/hr (typical low · varies)

As an Amazon Associate we earn from qualifying purchases. Cloud GPU links are referral links — we may earn a commission at no extra cost to you.

LLMs Compatible with 8 GB VRAM

All models below run comfortably in 8 GB VRAM with Q4_K_M quantization.

BielikBielik PL 11B v3.0 Instruct · 7 GB VRAM · Q4_K_M · bielik
Llama 3.2 FamilyLlama 3.2 11B Vision Instruct · 7 GB VRAM · Q4_K_M · llama-3-2
Llama 3.2 VisionLlama 3.2 Vision 11B · 7 GB VRAM · Q4_K_M · ollama run llama3.2-vision:11b
Falcon 3Falcon 3 10B Instruct · 7 GB VRAM · Q4_K_M · ollama run falcon3:10b
Gemma 2 FamilyGemma 2 9B IT · 6 GB VRAM · Q4_K_M · ollama run gemma2
GLM-4.7 / GLM-Z1GLM-4 9B · 6 GB VRAM · Q4_K_M · ollama run glm4:9b
Qwen 3.5Qwen 3.5 9B · 6 GB VRAM · Q4_K_M · ollama run qwen3.5:9b
GLM-4.6VGLM-4.6V-Flash 9B · 6 GB VRAM · Q4_K_M · glm-4-6v

34 more families also fit 8 GB — browse the full model library.

Best Use Cases

FAQ

Can the NVIDIA GeForce RTX 4060 Laptop GPU run local LLMs?

Yes — the NVIDIA GeForce RTX 4060 Laptop GPU has 8 GB VRAM and runs 8 GB GDDR6 on a 128-bit bus: 256 GB/s, against the desktop RTX 4060's 272 GB/s. Configurable from 35 W to 115 W, a range

How fast is the NVIDIA GeForce RTX 4060 Laptop GPU for AI inference?

The NVIDIA GeForce RTX 4060 Laptop GPU is estimated to run Llama 3.1 8B at 28–53 tok/s with Q4_K_M quantization. Llama 3.3 70B does not fit: it needs about 44 GB against 8 GB usable. These are modelled estimates, not measurements — see /en/methodology.

What LLMs can I run on 8 GB VRAM?

With 8 GB you can run: Bielik, Llama 3.2 Family, Llama 3.2 Vision, Falcon 3, Gemma 2 Family. Use Ollama for the easiest setup: ollama run llama3.1:8b.

Compare Similar GPUs

VRAM Tier

Buying Guide

← All GPU Reviews | All Hardware | Check Your Hardware | Full Benchmarks | Can I Run It?