Can RTX 4080 run Qwen 2.5 32B?
Yes — runs locally
~0 tok/sec · Cannot run — model too large for this GPU
The verdict
The RTX 4080 (16 GB VRAM) handles Qwen 2.5 32B comfortably using the Q4_K_M quantization, which fits in 19.0 GB. Expected throughput is around 0 tokens/second, which feels Cannot run — model too large for this GPU in interactive use. Premium 32B model. Top-tier reasoning. Mac with 32GB+ RAM.
How to run it
- 1. Install Ollama or LM Studio.
- 2. Pull the
Q4_K_MGGUF — best balance of quality and speed on 16 GB. - 3. Start chatting. Expect ~0 tok/sec on first-token, faster after warmup.
Other models that run great on RTX 4080
FAQ (20)
What GPU do I need to run Qwen 2.5 32B?
To run Qwen 2.5 32B, you need a GPU with at least 19 GB of VRAM, such as an NVIDIA RTX 3090 or A6000.
Is Qwen 2.5 32B good for coding?
Yes, Qwen 2.5 32B is well-suited for coding tasks, offering top-tier reasoning and code generation capabilities.
Qwen 2.5 32B vs Llama 3.1 8B?
Qwen 2.5 32B has more parameters (32B vs 8B), providing better performance and understanding in complex tasks, but requires significantly more VRAM (19GB vs 8GB).
Can I run Qwen 2.5 32B on a Mac?
Yes, you can run Qwen 2.5 32B on a Mac with at least 32GB of RAM and a compatible GPU with 19GB of VRAM.
How much VRAM does Qwen 2.5 32B need?
Qwen 2.5 32B requires 19 GB of VRAM, which is necessary to handle its 32 billion parameters.
Is Qwen 2.5 32B censored?
Qwen 2.5 32B is not inherently censored, but it adheres to community guidelines and ethical standards to ensure responsible use.
Is Qwen 2.5 32B commercial-use allowed?
Yes, Qwen 2.5 32B is licensed under Apache-2.0, allowing commercial use as long as you comply with the license terms.
Qwen 2.5 32B context length?
Qwen 2.5 32B supports a context length of up to 131,072 tokens, making it suitable for handling very long documents and conversations.
Want personalized recommendations for your exact setup? Detect my hardware →