👁 Alibaba
Alibaba
Qwen 3 4B
Current
5.5MDownloads886LikesApr 2025Released33K tokensContextApache 2.0License74 StrongQuality
Qwen 3 4B (4B parameters) requires approximately 6.1 GB of VRAM with Q4_K_M quantization. For the best balance of quality and speed, we recommend hardware with at least 8 GB of VRAM.
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— copy & paste to run locallyCopy-paste commands to run Qwen 3 4B on your machine.
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ollama run qwen3:4bQuick specs
Parameters4B
Architecturedense
Context33K tokens
Modalitytext
Min RAM1.6 GB
Rec. RAM2.4 GB (Q4_K_M)
LicenseApache 2.0
FamilyQwen
✓ Chat✓ Reasoning
About this model
- •Significant improvements: in general capabilities, including **instruction following, logical reasoning, text comprehension, mathematics, science,...
- •Substantial gains: in long-tail knowledge coverage across multiple languages
- •Markedly better alignment: with user preferences in subjective and open-ended tasks, enabling more helpful responses and higher-quality text...
- •Enhanced capabilities: in 256K long-context understanding
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Quantization options
VRAM estimates by quant level
No hardware detected — fit column shows raw VRAM estimates
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 1.6 GB | Low | — |
Q3_K_S | 3 | 2.0 GB | Low | — |
NVFP4 | 4 | 2.2 GB | Medium | — |
Q4_K_M | 4 | 2.4 GB | Medium | — |
Q5_K_M | 5 | 2.9 GB | High | — |
Q6_K | 6 | 3.3 GB | High | — |
Q8_0 | 8 | 4.3 GB | Very High | — |
F16 | 16 | 8.2 GB | Maximum | — |
Quality benchmarks
Qwen 3 4B benchmark scores
Coding
SWE-bench Verified—
HumanEval+—
Aider Polyglot—
LiveCodeBench35.1%
Reasoning
MMLU-Pro69.6%
GPQA Diamond62.0%
MATH-50068.0%
ARC Challenge—
General
Chatbot Arena—
IFEval83.4%
Source: official · 2025-07-14
Hardware compatibility
Fit estimates across all hardware
Computing compatibility...
Memory breakdown
Reference: RTX 2060 6GB
Weights2.4 GB
KV Cache2.2 GB
Runtime0.9 GB
Headroom0.6 GB
Frequently asked questions
FAQ — Qwen 3 4B
See also