Compare
Qwen3-8B vs Qwen3 32B
Put two to four models side by side on the fields that decide a deployment: context, price, region, license, languages, hosting, and what is verified.
| Qwen3-8B | Qwen3 32B | |
|---|---|---|
| Provider | Alibaba Qwen | Alibaba Qwen |
| Parameters | 8.19B | 32.8B |
| Context window | 33k | Not verified: the provider has not documented this claim. |
| License | apache-2.0 | apache-2.0 |
| Modalities | text | text |
| Release date | 27 Apr 2025 | 27 Apr 2025 |
| Languages | Strong: en, zh Adequate: de, fr, es, it, pt, ru, ja, ko, ar, nl, pl, tr, vi, hi | Not verified: the provider has not documented this claim. |
| Open weights | yes | yes |
| Tasks | Low cost, Reasoning, Multilingual support, Summarisation | Reasoning, Multilingual support, Coding |
Where two models differ, this table shows the difference and stops. LLM EU publishes no winner badge without a documented score for that task, and a missing figure stays missing instead of becoming a zero.
When to use it
Qwen3-8B
Strengths
- hybrid thinking and non-thinking modes
- Apache-2.0 licence
- runs on a single mid-range GPU
Limits
- 32,768-token native context; longer inputs need YaRN configuration
- behind Qwen3.5 and Qwen3.8 releases on reasoning
- no evaluation has been run by LLM EU
Tasks
Qwen3 32B
Strengths
- open weights are published on Hugging Face and can be downloaded without a vendor agreement
- Apache-2.0 licence, so commercial self-hosting is permitted without a separate agreement
Limits
- catalogue only — LLM EU does not run this model, and nothing on this card implies an LLM EU endpoint
- no evaluation has been run by LLM EU
- the published configuration records no context window, so the card carries none
- at 32.8B parameters, self-hosting needs a high-memory accelerator
Tasks
Tasks: Reasoning, Multilingual support