qwen
4B parameters
Commercial OK
Qwen 3 4B
Compact Qwen 3 for edge and laptop deployment. Outperforms many 7B models from prior generations.
License: Apache 2.0·Released Apr 29, 2025·Context: 131,072 tokens
Overview
Compact Qwen 3 for edge and laptop deployment. Outperforms many 7B models from prior generations.
Strengths
- Edge-class footprint
- Apache 2.0
Weaknesses
- Reasoning weaker than 8B+
Quantization variants
Each quantization trades model quality for file size and VRAM. Q4_K_M is the most popular starting point.
| Quantization | File size | VRAM required |
|---|---|---|
| Q4_K_M | 2.5 GB | 4 GB |
| Q8_0 | 4.4 GB | 6 GB |
Get the model
Ollama
One-line install
ollama run qwen3:4bRead our Ollama review →HuggingFace
Original weights
huggingface.co/Qwen/Qwen3-4B
Source repository — direct quantization required.
Hardware that runs this
Cards with enough VRAM for at least one quantization of Qwen 3 4B.
Compare alternatives
Models worth comparing
Same parameter band, plus what's one tier above and below — so you can decide what actually fits your hardware.
Same tier
Models in the same parameter band as this one
Step up
More capable — bigger memory footprint
Step down
Smaller — faster, runs on weaker hardware
Frequently asked
What's the minimum VRAM to run Qwen 3 4B?
4GB of VRAM is enough to run Qwen 3 4B at the Q4_K_M quantization (file size 2.5 GB). Higher-quality quantizations need more.
Can I use Qwen 3 4B commercially?
Yes — Qwen 3 4B ships under the Apache 2.0, which permits commercial use. Always read the license text before deployment.
What's the context length of Qwen 3 4B?
Qwen 3 4B supports a context window of 131,072 tokens (about 131K).
How do I install Qwen 3 4B with Ollama?
Run `ollama pull qwen3:4b` to download, then `ollama run qwen3:4b` to start a chat session. The default quantization is Q4_K_M.
Source: huggingface.co/Qwen/Qwen3-4B
Reviewed by RunLocalAI Editorial. See our editorial policy for how we research and verify model claims.