Can NVIDIA GeForce RTX 4060 Ti 8GB run Qwen 2.5 14B?
14B parameter LLM model on 8GB GDDR6
Barely — requires CPU/RAM offloading
~1-3 tok/s (offload)
SpeedVery slow — expect 1-3 tokens/sec
QualityQuality is fine but the speed makes it impractical for interactive use
VRAM Requirements
Qwen 2.5 14B is a 14B parameter model. At full precision (FP16), it requires 28GB of VRAM. Your NVIDIA GeForce RTX 4060 Ti 8GB only has 8GB — not enough even at maximum compression.
FP16 (Full Precision)28GB (need 20GB more)
Maximum quality, no quantization
Q8 (8-bit)14GB (need 6GB more)
Near-lossless, ~50% size reduction
Q4 (4-bit)9GB (need 1GB more)
Good quality, ~75% size reduction
Your GPU VRAM: 8GB GDDR6 at 288 GB/s bandwidth
Recommended system RAM: 32GB DDR5 (2x GPU VRAM minimum for model overflow)
Recommended system RAM: 32GB DDR5 (2x GPU VRAM minimum for model overflow)
How to Set It Up
Step 1: Install Ollama
curl -fsSL https://ollama.com/install.sh | shOllama is the easiest way to run local LLMs. Works on Linux, macOS, and Windows.
Step 2: Download and run Qwen 2.5 14B
ollama run qwen2.5:14b:q4_K_MThis downloads the model (~14GB). First run takes a few minutes.
Step 3: Verify GPU is being used
nvidia-smiCheck that VRAM usage increases when the model loads. You should see ~9GB used.
NVIDIA GeForce RTX 4060 Ti 8GB Specs
VRAM8GB GDDR6
Memory Bandwidth288 GB/s
TDP160W
CUDA Cores4,352
Street Price~$370
AI Rating3/10
Other GPUs That Run Qwen 2.5 14B
Other LLM Models on NVIDIA GeForce RTX 4060 Ti 8GB
About Qwen 2.5 14B
Good balance of quality and speed. Fits on 12–16GB GPUs at Q4-Q8.
Category: LLM · Parameters: 14B · CUDA required: No (runs via llama.cpp/GGUF)