NVIDIA GeForce RTX 4080 — Local LLM Performance & Compatibility

Name: LLM Configurator — GPU VRAM Checker
Author: LLM Configurator

Written by Jakub Rusinowski · Last updated July 12, 2026

16 GB VRAM equivalent to 4080 Super in model compatibility. Strong for 7–14B models.

Technical Specifications

VRAM	16 GB
Memory Bandwidth	717 GB/s
TDP	320 W
Architecture	Ada Lovelace AD103
Release Year	2022
MSRP at Launch	$1,199
Inference Speed (Llama 3.1 8B Q4_K_M)	66–127 tok/s (estimated)
Inference Speed (Llama 3.3 70B Q4_K_M)	Does not fit — needs ~44 GB of 16 GB usable

Buy This HardwareNVIDIA GeForce RTX 4080 16GB — 16 GB VRAM · 320 W board power Deploy 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.

Affiliate disclosure: Some links on this page are affiliate links — if you buy through them, LLM Configurator may earn a commission at no extra cost to you. As an Amazon Associate, LLM Configurator earns from qualifying purchases.

NVIDIA GeForce RTX 4080 16GB

16 GB VRAM · 320 W board power

2026 prices are volatile — check the current listing.

Check price on Amazon

LLMs Compatible with 16 GB VRAM

All models below run comfortably in 16 GB VRAM with Q4_K_M quantization.

Llama 3.1 Family	Llama 3.1 8B Instruct · 6 GB VRAM · Q4_K_M · `ollama run llama3.1`
Qwen 3	Qwen 3 14B · 10 GB VRAM · Q4_K_M · `ollama run qwen3:14b`
Gemma 3	Gemma 3 12B Instruct · 8 GB VRAM · Q4_K_M · `ollama run gemma3:12b`
Phi-4 Family	Phi-4 (14B) · 9 GB VRAM · Q4_K_M · `ollama run phi4`
Phi-4 Mini	Phi-4 Mini (3.8B) · 3 GB VRAM · Q4_K_M · `ollama run phi4-mini`
Mistral Family	Mistral Small 3 (24B) · 15 GB VRAM · Q4_K_M · `ollama run mistral-small`
DeepSeek R1	DeepSeek R1 Distill Qwen 14B · 9 GB VRAM · Q4_K_M · `ollama run deepseek-r1:14b`
Qwen 2.5 Family	Qwen 2.5 14B Instruct · 9 GB VRAM · Q4_K_M · `ollama run qwen2.5:14b`

Best Use Cases

14B models
coding
productivity

Quick Start with Ollama

Install Ollama then run the recommended model for this GPU:

ollama run qwen3:14b

FAQ

Can the NVIDIA GeForce RTX 4080 run local LLMs?

Yes — the NVIDIA GeForce RTX 4080 has 16 GB VRAM and runs 16 GB VRAM equivalent to 4080 Super in model compatibility. Strong for 7–14B models.

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

The NVIDIA GeForce RTX 4080 is estimated to run Llama 3.1 8B at 66–127 tok/s with Q4_K_M quantization. Llama 3.3 70B does not fit: it needs about 44 GB against 16 GB usable. These are modelled estimates, not measurements — see /en/methodology.

What LLMs can I run on 16 GB VRAM?

With 16 GB you can run: Llama 3.1 Family, Qwen 3, Gemma 3, Phi-4 Family, Phi-4 Mini. Use Ollama for the easiest setup: ollama run qwen3:14b.

Can I Run It? — NVIDIA GeForce RTX 4080

Compare Similar GPUs

VRAM Tier

Best LLMs for 16 GB VRAM

Buying Guide

Best GPU Buyer Guide 2026

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