Qwen: Qwen3 30B A3B Instruct 2507
Qwen3 30B A3B Instruct 2507 is a compact, affordable model with tool use and a large 262K context window, offering reasonable instruction-following capability for lighter business tasks — though its benchmark scores indicate limited reasoning depth compared to larger models.
Assessment date: March 12, 2026
Our methodology takes into account a range of factors including pricing, functionality, capabilities, benchmark performance, and real-world applicability. Rankings are reviewed and updated regularly as new models are released. Issues with our rankings? Contact us
Qwen3-30B-A3B-Instruct-2507 is a 30.5B-parameter mixture-of-experts language model from Qwen, with 3.3B active parameters per inference. It operates in non-thinking mode and is designed for high-quality instruction following, multilingual understanding, and agentic tool use. Post-trained on instruction data, it demonstrates competitive performance across reasoning (AIME, ZebraLogic), coding (MultiPL-E, LiveCodeBench), and alignment (IFEval, WritingBench) benchmarks. It outperforms its non-instruct variant on subjective and open-ended tasks while retaining strong factual and coding performance.
Capabilities
Architecture
| Modality | Text → Text |
| Tokenizer | Qwen3 |
| Parameters | 30B |
Performance Indices
Source: Artificial Analysis
Benchmark Scores
Evaluations
Benchmark data from Artificial Analysis and Hugging Face
Model Information
Pricing
| Token Type | Cost per 1M tokens | Cost per 1K tokens |
|---|---|---|
| Input | $0.09 | $0.000090 |
| Output | $0.30 | $0.000300 |
Live Performance
Live endpoint metrics — refreshed every 30 minutes.
