What is the best GPU for running Qwen2.5 0.5B locally?

The cheapest hardware in Germany that runs Qwen2.5 0.5B fully in memory at 64k context is the NVIDIA GeForce RTX 3060 12GB, 309 € at Amazon, at about 167 tok/s (estimated). The best value is the NVIDIA GeForce RTX 3080 10GB (about 353 tok/s for 500 €). The fastest we price is the NVIDIA GeForce RTX 5090, at about 831 tok/s.

Can I run Qwen2.5 0.5B on a 16 GB GPU?

Yes: at Q8_0 it fits fully in 16 GB at 64k context. On the NVIDIA GeForce RTX 5080 it runs at about 445 tok/s (estimated).

Can I run Qwen2.5 0.5B on a 24 GB GPU?

Yes: at Q8_0 it fits fully in 24 GB at 64k context. On the NVIDIA GeForce RTX 3090 Ti it runs at about 468 tok/s (estimated).

How do I run Qwen2.5 0.5B locally?

With Ollama: ollama run hf.co/bartowski/Qwen2.5-0.5B-Instruct-GGUF:Q8_0 (the Q8_0 build). LM Studio and llama.cpp commands are on this page.

What licence is Qwen2.5 0.5B released under?

Apache License 2.0, which allows commercial use.

Qwen2.5 0.5B

494M parameters · 32k context · Apache License 2.0 · released 2024-09-16

chat

In short

The cheapest hardware in Germany that runs Qwen2.5 0.5B fully in memory at 64k context is the NVIDIA GeForce RTX 3060 12GB, 309 € at Amazon, at about 167 tok/s (estimated).

Updated 15 October 2026. Speeds are estimates; how they are worked out.

What to run it on in Germany

Fully in memory at 64k context, priced at retailers today.

Cheapest
NVIDIA GeForce RTX 3060 12GB
167tok/sest.Q8_0
309 €
Best value
NVIDIA GeForce RTX 3080 10GB
353tok/sest.Q8_0
500 €
Fastest
NVIDIA GeForce RTX 5090
831tok/sest.Q8_0
6.028 €
Mac
Mac mini M4 16GB
58tok/sest.Q8_0
800 €

All hardware that runs it

Everything we price, best value first. Two cards split the model by layers.

Hardware	Quant	Fits	Decode	Price	tok/s per 1,000
NVIDIA GeForce RTX 3060 12GB	Q8_0	fits	167 tok/s	309 €	540.5
Intel Arc B580	Q8_0	fits	171 tok/s	360 €	474.4
NVIDIA Tesla P40	Q8_0	fits	161 tok/s	369 €	435.0
NVIDIA GeForce RTX 3080 10GB	Q8_0	fits	353 tok/s	500 €	705.2
AMD Radeon RX 9060 XT 16GB	Q8_0	fits	132 tok/s	550 €	239.5
Intel Arc A770 16GB	Q8_0	fits	210 tok/s	646 €	324.4
NVIDIA GeForce RTX 4060 Ti 16GB	Q8_0	fits	134 tok/s	650 €	205.6
NVIDIA GeForce RTX 4070 Super	Q8_0	fits	234 tok/s	707 €	330.6
NVIDIA GeForce RTX 5060 Ti 16GB	Q8_0	fits	208 tok/s	739 €	281.2
AMD Radeon RX 9070 XT	Q8_0	fits	263 tok/s	778 €	338.5
NVIDIA GeForce RTX 5070	Q8_0	fits	312 tok/s	798 €	390.7
Mac mini M4 16GB	Q8_0	fits	58 tok/s	800 €	73.0
AMD Radeon RX 7600 XT	Q8_0	fits	119 tok/s	813 €	145.7
AMD Radeon RX 7900 XT	Q8_0	fits	329 tok/s	855 €	385.2
AMD Radeon RX 7800 XT	Q8_0	fits	257 tok/s	1.002 €	256.4
Intel Arc Pro B60	Q8_0	fits	171 tok/s	1.074 €	158.8
NVIDIA GeForce RTX 4080 Super	Q8_0	fits	342 tok/s	1.100 €	310.5
NVIDIA GeForce RTX 5070 Ti	Q8_0	fits	416 tok/s	1.149 €	361.8
NVIDIA GeForce RTX 4070 Ti Super	Q8_0	fits	312 tok/s	1.247 €	250.0
Mac mini M4 32GB	Q8_0	fits	58 tok/s	1.400 €	41.7
NVIDIA GeForce RTX 5080	Q8_0	fits	445 tok/s	1.500 €	296.9
AMD Radeon RX 7900 XTX	Q8_0	fits	395 tok/s	1.555 €	254.1
NVIDIA GeForce RTX 3090	Q8_0	fits	434 tok/s	1.850 €	234.7
AMD Radeon AI PRO R9700	Q8_0	fits	263 tok/s	1.867 €	141.1
NVIDIA GeForce RTX 3090 Ti	Q8_0	fits	468 tok/s	2.500 €	187.1
Mac mini M4 Pro 48GB	Q8_0	fits	133 tok/s	2.699 €	49.2
Mac mini M4 Pro 64GB	Q8_0	fits	133 tok/s	2.799 €	47.4
GMKtec EVO-X2 Ryzen AI Max+ 395 128GB	Q8_0	fits	105 tok/s	3.700 €	28.5
NVIDIA GeForce RTX 4090	Q8_0	fits	468 tok/s	3.955 €	118.3
Mac Studio M4 Max 64GB	Q8_0	fits	266 tok/s	4.183 €	63.5
Mac Studio M4 Max 128GB	Q8_0	fits	266 tok/s	5.800 €	45.8
Mac Studio M3 Ultra 96GB	Q8_0	fits	398 tok/s	5.999 €	66.4
NVIDIA GeForce RTX 5090	Q8_0	fits	831 tok/s	6.028 €	137.9
NVIDIA DGX Spark 128GB	Q8_0	fits	127 tok/s	8.313 €	15.2
ASUS Ascent GX10 128GB	Q8_0	fits	127 tok/s	8.623 €	14.7
Mac Studio M3 Ultra 256GB	Q8_0	fits	398 tok/s	15.555 €	25.6
Mac Studio M3 Ultra 512GB	Q8_0	fits	398 tok/s	18.995 €	21.0
NVIDIA RTX PRO 6000 Blackwell	Q8_0	fits	831 tok/s	19.076 €	43.6
Framework Desktop Ryzen AI Max+ 395 128GB	Q8_0	fits	105 tok/s	–	–
Framework Desktop Ryzen AI Max+ 395 64GB	Q8_0	fits	105 tok/s	–	–

Memory needed

Weights, KV cache and runtime buffers at each context length (KV cache at fp16).

Quant	File	@8k	@32k
Q8_0gguf	0.5 GB	1.3 GB	1.8 GB

Run it

Copy a command for the runtime you use.

Q8_0
- Ollamaollama run hf.co/bartowski/Qwen2.5-0.5B-Instruct-GGUF:Q8_0
- LM Studiolms get bartowski/Qwen2.5-0.5B-Instruct-GGUF@q8_0
- llama.cppllama-server -hf bartowski/Qwen2.5-0.5B-Instruct-GGUF:Q8_0

Notes

The card says the full context is 32,768 tokens and generation is up to 8192 tokens. Needs transformers 4.37.0 or later, because older versions raise KeyError: 'qwen2'.

Questions

What is the best GPU for running Qwen2.5 0.5B locally?: The cheapest hardware in Germany that runs Qwen2.5 0.5B fully in memory at 64k context is the NVIDIA GeForce RTX 3060 12GB, 309 € at Amazon, at about 167 tok/s (estimated). The best value is the NVIDIA GeForce RTX 3080 10GB (about 353 tok/s for 500 €). The fastest we price is the NVIDIA GeForce RTX 5090, at about 831 tok/s.
Can I run Qwen2.5 0.5B on a 16 GB GPU?: Yes: at Q8_0 it fits fully in 16 GB at 64k context. On the NVIDIA GeForce RTX 5080 it runs at about 445 tok/s (estimated).
Can I run Qwen2.5 0.5B on a 24 GB GPU?: Yes: at Q8_0 it fits fully in 24 GB at 64k context. On the NVIDIA GeForce RTX 3090 Ti it runs at about 468 tok/s (estimated).
How do I run Qwen2.5 0.5B locally?: With Ollama: ollama run hf.co/bartowski/Qwen2.5-0.5B-Instruct-GGUF:Q8_0 (the Q8_0 build). LM Studio and llama.cpp commands are on this page.
What licence is Qwen2.5 0.5B released under?: Apache License 2.0, which allows commercial use.