
ai/qwen3!logo
Qwen3 is the latest generation in the Qwen LLM family, designed for top-tier performance in coding, math, reasoning, and language tasks. It includes both dense and Mixture-of-Experts (MoE) models, offering flexible deployment from lightweight apps to large-scale research.
Qwen3 introduces dual reasoning modes—"thinking" for complex tasks and "non-thinking" for fast responses—giving users dynamic control over performance. It outperforms prior models in reasoning, instruction following, and code generation, while excelling in creative writing and dialogue.
With strong agentic and tool-use capabilities and support for over 100 languages, Qwen3 is optimized for multilingual, multi-domain applications.
| Attribute | Value |
|---|---|
| Provider | Alibaba Cloud |
| Architecture | qwen3 |
| Cutoff date | April 2025 (est.) |
| Languages | 119 languages from multiple families (Indo European, Sino-Tibetan, Afro-Asiatic, Austronesian, Dravidian, Turkic, Tai-Kadai, Uralic, Astroasiatic) including others like Japanese, Basque, Haitian,... |
| Tool calling | ✅ |
| Input modalities | Text |
| Output modalities | Text |
| License | Apache 2.0 |
| Model variant | Parameters | Quantization | Context window | VRAM¹ | Size |
|---|---|---|---|---|---|
ai/qwen3:8B-Q4_K_Mai/qwen3:latest | 8B | MOSTLY_Q4_K_M | 41K tokens | 5.80 GiB | 4.68 GB |
ai/qwen3:0.6B-Q4_0 | 0.6B | MOSTLY_Q4_0 | 41K tokens | 1.51 GiB | 441.67 MB |
ai/qwen3:0.6B-Q4_K_M | 0.6B | MOSTLY_Q4_K_M | 41K tokens | 1.53 GiB | 456.11 MB |
ai/qwen3:0.6B-F16 | 0.6B | MOSTLY_F16 | 41K tokens | 2.27 GiB | 1.40 GB |
ai/qwen3:4B-F16 | 4B | MOSTLY_F16 | 262K tokens | 8.92 GiB | 7.49 GB |
ai/qwen3:4B-UD-Q4_K_XL | 4B | MOSTLY_Q4_K_M | 262K tokens | 3.80 GiB | 2.37 GB |
ai/qwen3:8B-F16 | 8B | MOSTLY_F16 | 41K tokens | 15.54 GiB | 15.26 GB |
ai/qwen3:14B-Q6_K | 14B | MOSTLY_Q6_K | 41K tokens | 12.27 GiB | 11.28 GB |
ai/qwen3:30B-A3B-F16 | 30B-A3B | MOSTLY_F16 | 41K tokens | 57.55 GiB | 56.89 GB |
ai/qwen3:30B-A3B-Q4_K_M | 30B-A3B | MOSTLY_Q4_K_M | 41K tokens | 18.35 GiB | 17.28 GB |
ai/qwen3:4B-UD-Q8_K_XL | 4B | MOSTLY_Q8_0 | 262K tokens | 6.13 GiB | 4.70 GB |
ai/qwen3:8B-Q4_0 | 8B | MOSTLY_Q4_0 | 41K tokens | 5.56 GiB | 4.44 GB |
¹: VRAM estimated based on model characteristics.
latest→8B-Q4_K_M
Qwen3-8B is designed for a wide range of advanced natural language processing tasks:
/think and /no_think prompts (when enable_thinking=True). This allows dynamic control over the model's reasoning depth during multi-turn conversations.Note: Qwen3 models use a new naming convention: post-trained models no longer include the
-Instructsuffix (e.g.,Qwen3-32BreplacesQwen2.5-32B-Instruct), and base models now end with-Base.
First, pull the model:
bashdocker model pull ai/qwen3
Then run the model:
bashdocker model run ai/qwen3
For more information, check out the Docker Model Runner docs.
| Category | Benchmark | Qwen3 |
|---|---|---|
| General Tasks | MMLU | 87.81 |
| MMLU-Redux | 87.40 | |
| MMLU-Pro | 68.18 | |
| SuperGPQA | 44.06 | |
| BBH | 88.87 | |
| Mathematics & Science Tasks | GPQA | 47.47 |
| GSM8K | 94.39 | |
| MATH | 71.84 | |
| Multilingual Tasks | MGSM | 83.53 |
| MMMLU | 86.70 | |
| INCLUDE | 73.46 | |
| Code Tasks | EvalPlus | 77.60 |
| MultiPL-E | 65.94 | |
| MBPP | 81.40 | |
| CRUX-O | 79.00 |






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