Budget Pick
NVIDIA GeForce GTX 1060 3GB3 GB VRAM · ~76.8 tok/s
Lowest cost that meets recommended VRAM
Check price on AmazonCompatibility Check
Can I Run Qwen3 4B?
Qwen3 4B is a 4B parameter model from the Qwen family. Check if your hardware can handle it.
Share this hardware check
Send this page to a friend or teammate so they can check whether Qwen3 4B fits their hardware too.
Social proof
78% of 998 scanned PCs run Qwen3 4B fully on GPU.
787 keep at least some work on GPU. Based on anonymous compatibility checks.
Full GPU
781Hybrid CPU+GPU
6CPU Only
180Can't Run
31Test Your Hardware
Detecting your hardware...
Hardware Requirements
Beginner tip: minimum values mean the model can start, while recommended values usually feel smoother during real use. VRAM is your GPU's dedicated memory; RAM is your system memory used as fallback. See the full glossary.
| Quantization | File Size | Min VRAM | Recommended VRAM | Min RAM | Context |
|---|---|---|---|---|---|
| Q4_K_MEasiest | 2 GB | 2.3 GB | 2.6 GB | 3 GB | 8K / 8K |
| Q5_K_M | 2.5 GB | 2.9 GB | 3.3 GB | 4 GB | 8K / 8K |
| Q8_0 | 4 GB | 4.6 GB | 5.2 GB | 6 GB | 8K / 8K |
| FP16 | 8 GB | 9.2 GB | 10.4 GB | 12 GB | 8K / 8K |
Not sure your GPU has enough VRAM? Compare GPUs that can run Qwen3 4B.
Recommended GPUs for Qwen3 4B
These GPUs meet the recommended 2.6 GB VRAM for the Q4_K_M quantization. Estimated speeds are approximate and assume full GPU offloading.
Fastest Pick
NVIDIA GeForce RTX 509032 GB VRAM · ~716.8 tok/s
Highest estimated throughput
Check price on AmazonBest Value
NVIDIA GeForce RTX 3080 Ti12 GB VRAM · ~364.8 tok/s
Best speed per dollar of VRAM
Check price on AmazonNeed a detailed comparison? See all GPU rankings for Qwen3 4B.
Strong OpenClaw Model Candidate
Qwen3 4B is a common OpenClaw pick for local agent workflows. Use this model with Ollama, llama.cpp, or LM Studio, then confirm full OpenClaw hardware compatibility.
Why choose Qwen3 4B?
General-purpose local model brief
- • Pilot testing with your own tasks
- • Controlled local experiments
Quantization tip: Benchmark at least two quantizations and validate with a task-specific eval set before production use.