Qwen3 4B
Alibaba · Text generation · 4B · 131k context · Released 29 April 2025
A 4-billion-parameter model from the Qwen3 family that punches above its weight, with an optional thinking mode and a 128k context window. Light enough for laptops and 8GB cards, and Apache 2.0 licensed.
Strengths
- Runs on laptops and 8GB cards with room to spare
- Optional thinking mode brings real reasoning to a very small model
- Apache 2.0, with a long 128k context window
Weaknesses
- Still a small model, so it will struggle with harder, longer tasks
- More prone to factual mistakes than the 8B and larger siblings
- Thinking mode adds latency and token use
Hardware requirements
| Quantisation | Approx. VRAM | Notes |
|---|---|---|
| Q4_K_M | ~2.5GB | Runs on almost anything, including CPU |
| Q8_0 | ~4.3GB | Near-lossless and still very light |
| FP16 | ~8GB | Full precision, comfortable on an 8GB card |
Also runs on CPU (slower). Optimised builds available for Apple Silicon.
What you'd need to run this
Roughly what a machine to run this would need, at up to three levels of quality. Memory is the deciding factor.
Minimum to run it
Q4_K_M · ~2.5GB needed
One 12GB GPU
NVIDIA GeForce RTX 3060 12GBor a Mac or mini-PC with unified memory, if you prefer no discrete GPU, Mac mini M5 Pro .
At least 32GB of system RAM alongside the card.
around £700–£1,100
What else 12GB runs →For good quality
Q8_0 · ~4.3GB needed
One 12GB GPU
NVIDIA GeForce RTX 3060 12GBor a Mac or mini-PC with unified memory, if you prefer no discrete GPU, Mac mini M5 Pro .
At least 32GB of system RAM alongside the card.
around £700–£1,100
What else 12GB runs →Best quality
FP16 · ~8GB needed
One 12GB GPU
NVIDIA GeForce RTX 3060 12GBor a Mac or mini-PC with unified memory, if you prefer no discrete GPU, Mac mini M5 Pro .
At least 32GB of system RAM alongside the card.
around £700–£1,100
What else 12GB runs →Licence
Apache 2.0 — read the licence
Qwen3 4B: common questions
- What hardware do I need to run Qwen3 4B?
- At its most compressed (Q4_K_M) it needs roughly 2.5GB of VRAM, and about 4.3GB for good quality. VRAM figures are approximate and depend on context length and settings.
- Is Qwen3 4B free for commercial use?
- Yes. Qwen3 4B is licensed under Apache 2.0, which permits commercial use with no meaningful conditions.
- Can I run Qwen3 4B on Apple Silicon?
- Yes. Qwen3 4B has builds optimised for Apple Silicon, through MLX or GGUF on a Mac.
- Does Qwen3 4B run on CPU?
- Yes, Qwen3 4B can run on the CPU, though generation is slower than on a GPU.
- What is Qwen3 4B's context window?
- Qwen3 4B has a context window of 131,072 tokens, about 131k.
Availability
- Official page
- Hugging Face
- ollama run qwen3:4b
Where to get quantised weights
Some of the best quantised weights are made by the community, not the model’s authors. Look this model up on these providers:
- Unsloth GGUF (Dynamic 2.0, imatrix)
Dynamic and imatrix GGUF quants that often hold quality better than a plain quant at the same bit-width, especially at 4-bit and below.
- Bartowski GGUF Q2-Q8 (imatrix)
A wide, reliable range of imatrix GGUF quants, typically Q2 through Q8.
- MLX community MLX 4-bit and 8-bit
MLX quants for Apple Silicon, usually 4-bit and 8-bit.
Recommended for
- A capable first local model on a laptop
- Running alongside other software with memory to spare
- Tasks where you want light reasoning without heavy hardware
Related guides
Glossary
Catalogue entry last verified 30 July 2026. Specifications change; verify anything you are about to spend money on.