Key takeaways

• Qwen3 14B is a 14.8B parameter causal language model designed for complex reasoning and efficient dialogue, capable of switching between 'thinking' (analytical) and 'non-thinking' (conversational) modes. It supports instruction-following, agent tool use, creative writing, and multilingual tasks across 100+ languages.
• The model uses a Transformer-based architecture, natively handling 32K token contexts and extendable to 131K using YaRN-based scaling.
• Notable capabilities include strong performance in complex reasoning (84.64% on Big Bench Hard) and understanding fundamental audit concepts. However, it struggles with pronoun resolution, complex causal reasoning, accurate alphabetization, simple date arithmetic, and exhibits hallucination in specialized domains like SAP and Banking.
• The model achieved its best performance with 86.67% accuracy on the 'Accounting Audit' financial reasoning benchmark, demonstrating accurate identification of correct audit opinions and understanding of revenue recognition principles.
• The worst performance was 0% accuracy on the 'Hypothetical Scenario Analysis' benchmark (due to an undefined scoring methodology) and on the 'ITC Infotech User Stories' benchmark due to hallucination and factual inaccuracies in specialized contexts (SAP, Banking).

Technical specifications

Context length

41k tokens

Max output

—

Architecture

Transformer

Modalities

text->text

Parameters

~13B

Open weights

Yes

Licence

Apache 2.0

Regions

China

Vendor

Qwen

Provider model key

qwen/qwen3-14b