Qwen model names usually combine a generation label, a parameter-size label, and sometimes a task family or training variant. In a name such as Qwen3-30B-A3B, “30B” is the total parameter count and “A3B” is the number of activated parameters—not a second model size. Labels such as VL, Audio, Coder, Base, and Instruct add different clues, but the exact model card is the authority for each checkpoint.
How to read a Qwen model name
Read the name as a set of clues, not as a complete specification. In the cited Qwen3 release examples, Qwen3 identifies the generation and 14B indicates a parameter scale. Other parts of a name may identify an architecture or task family, modality, or post-training variant. Not every Qwen family uses every label, so confirm the specific checkpoint rather than applying one naming rule to all releases.
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Generation and parameter scale
The generation prefix helps distinguish model releases. A size such as 14B means approximately 14 billion parameters; it does not, by itself, tell you whether a model handles images or audio, whether it is instruction-tuned, how long its context is, or what hardware it needs. Qwen’s 2025 Qwen3 launch listed dense models at 0.6B, 1.7B, 4B, 8B, 14B, and 32B. These are release examples, not a promise that every Qwen generation offers those sizes. See the Qwen3 launch materials.
What A means in Qwen3-30B-A3B
For the Qwen3 mixture-of-experts (MoE) examples, the number before “A” is the model’s total parameter count, while the A-number is the activated parameter count. Qwen’s April 29, 2025 launch describes Qwen3-30B-A3B as 30 billion total parameters with 3 billion activated, and Qwen3-235B-A22B as 235 billion total with 22 billion activated. The activated count is not the total model size or the checkpoint’s full parameter count.
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That distinction matters when comparing MoE and dense names: the A-number tells you about activated parameters in the cited MoE naming convention, not a directly interchangeable total-size figure. Use the individual model documentation for deployment and hardware requirements; the name alone does not establish them. The figures and naming examples are from the Qwen3 launch materials.
What Qwen family labels tell you
Family labels often point to the model’s intended tasks or input types. They are useful for narrowing a choice, but they do not replace the checkpoint card’s description of supported capabilities.
| Label or family | What it indicates in the cited sources |
|---|---|
| VL | Vision-language; the cited Qwen2.5-VL release included 3B, 7B, and 72B sizes. Qwen2.5-VL announcement |
| Audio | Audio-language family. Qwen2-Audio announcement |
| Coder | Models oriented to coding; Qwen3-Coder is described as focused on coding and agentic coding. Qwen3-Coder announcement |
| Embedding | Models for embedding, retrieval, or reranking. Qwen3 Embedding announcement |
Base versus Instruct
In the Qwen2.5-Coder repository’s model table, Base and Instruct are separate types. Base is a pretrained foundation model; Instruct is intended for instruction-following use. In practical terms, choose based on whether you want a foundation checkpoint for a workflow that uses further training or customization, or a variant prepared to follow user instructions. Availability and exact behavior vary by family and checkpoint, so check its card rather than assuming the same suffixes exist everywhere. See the Qwen2.5-Coder repository.
Thinking mode is not a size suffix
Qwen3’s launch materials describe thinking and non-thinking modes as behavior options that users can control. They do not add another parameter count to the model name. Check the release documentation for the interface and controls supported by the checkpoint you are using: Qwen3 launch materials.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How to compare two Qwen checkpoints
Compare models in this order so a similar-looking size label does not obscure a meaningful difference:
- Task and modality: determine whether you need general text, vision-language, audio-language, coding, embedding, retrieval, or reranking functionality.
- Architecture: establish whether the checkpoint is dense or MoE. For the cited Qwen3 MoE names, keep total parameters separate from activated parameters.
- Training variant: check whether the checkpoint is Base, Instruct, or another explicitly documented variant.
- Context and capabilities: read the model card for context length and supported inputs. Qwen3’s launch lists different context lengths among its documented dense sizes, so context cannot be safely inferred from the size label.
- Deployment fit: check the card for compatibility and requirements for your intended setup. A parameter label alone is not a hardware recommendation.
Qwen’s official launch materials provide examples, but the naming evidence here covers releases through July 2025 and does not establish whether later releases changed or extended these conventions. For a current decision, verify the exact repository or model card for the checkpoint you plan to use.
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