| --- |
| license: apache-2.0 |
| library_name: transformers |
| --- |
| # Qwen3-4B-Base |
|
|
| ## Qwen3 Highlights |
|
|
| Qwen3 is the latest generation of large language models in Qwen series, offering a comprehensive suite of dense and mixture-of-experts (MoE) models. |
| Building upon extensive advancements in training data, model architecture, and optimization techniques, Qwen3 delivers the following key improvements over the previously released Qwen2.5: |
|
|
| - **Expanded Higher-Quality Pre-training Corpus:** Qwen3 is pre-trained on 36 trillion tokens across 119 languages — tripling the language coverage of Qwen2.5 — with a much richer mix of high-quality data, including coding, STEM, reasoning, book, multilingual, and synthetic data. |
| - **Training Techniques and Model Architecture:** Qwen3 incorporates a series of training techiques and architectural refinements, including global-batch load balancing loss for MoE models and qk layernorm for all models, leading to improved stability and overall performance. |
| - **Three-stage Pre-training:** Stage 1 focuses on broad language modeling and general knowledge acquisition, Stage 2 improves reasoning skills like STEM, coding, and logical reasoning, and Stage 3 enhances long-context comprehension by extending training sequence lengths up to 32k tokens. |
| - **Scaling Law Guided Hyperparameter Tuning:** Through comprehensive scaling law studies across the three-stage pre-training pipeline, Qwen3 systematically tunes critical hyperparameters — such as learning rate scheduler and batch size — separately for dense and MoE models, resulting in better training dynamics and final performance across different model scales. |
|
|
| ## Model Overview |
|
|
| **Qwen3-4B-Base** has the following features: |
| - Type: Causal Language Models |
| - Training Stage: Pretraining |
| - Number of Parameters: 4.0B |
| - Number of Paramaters (Non-Embedding): 3.6B |
| - Number of Layers: 36 |
| - Number of Attention Heads (GQA): 32 for Q and 8 for KV |
| - Context Length: 32,768 |
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| For more details, including benchmark evaluation, hardware requirements, and inference performance, please refer to our [blog](https://qwenlm.github.io/blog/qwen3/), [GitHub](https://github.com/QwenLM/Qwen3), and [Documentation](https://qwen.readthedocs.io/en/latest/). |
|
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| ## Requirements |
|
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| The code of Qwen3 has been in the latest Hugging Face `transformers` and we advise you to use the latest version of `transformers`. |
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| With `transformers<4.51.0`, you will encounter the following error: |
| ``` |
| KeyError: 'qwen3' |
| ``` |
|
|
| ## Evaluation & Performance |
|
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| Detailed evaluation results are reported in this [📑 blog](https://qwenlm.github.io/blog/qwen3/). |
|
|
| ### Citation |
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|
| If you find our work helpful, feel free to give us a cite. |
|
|
| ``` |
| @misc{qwen3, |
| title = {Qwen3}, |
| url = {https://qwenlm.github.io/blog/qwen3/}, |
| author = {Qwen Team}, |
| month = {April}, |
| year = {2025} |
| } |
| ``` |
