Discover Qwen3 – a revolutionary large language model with hybrid thinking capabilities, Mixture-of-Experts (MoE) architecture, and 128K context window. Supports 119 languages. Free under Apache 2.0.
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Qwen3 is a revolutionary large language model series featuring hybrid thinking capabilities, Mixture-of-Experts (MoE) architecture, and support for 119 languages.
Qwen3 is a cutting-edge family of large language models (LLMs) developed for maximum performance and efficiency. With up to 235 billion parameters and trained on 36 trillion tokens, Qwen3 blends hybrid reasoning, Mixture-of-Experts architecture, and 128K context length to deliver industry-leading results in reasoning, coding, mathematics, and multilingual NLP.
Whether you're building advanced AI agents, language-based tools, or simply exploring next-gen generative AI, Qwen3 offers the flexibility and power to meet the challenge.
🚀 Hybrid Thinking Modes
Dynamically switch between deep reasoning and rapid response, with flexible control via enable_thinking or /think commands.
🧠 Mixture-of-Experts (MoE) Architecture Activates only the most relevant model “experts” per task, significantly reducing computation without compromising quality.
🌐 119-Language Multilingual Support Full coverage across major and regional languages, ideal for global applications.
📚 Advanced Pretraining Trained on diverse datasets from code, web, and structured documents — supporting robust generalization and factual grounding.
📏 128K Token Context Length Perfect for processing and reasoning over long documents, multi-page reports, or entire conversations.
🏗️ Scalable Model Family From lightweight 0.6B models to powerful 235B MoE models — choose the model that fits your use case.
Superior Benchmark Performance Tops charts on Arena-Hard, MMLU-Pro, GPQA-Diamond, LiveBench, and more.
Reduced Inference Costs Thanks to MoE’s selective activation, even large models remain computationally efficient.
Advanced Agentic Capabilities Supports Model Context Protocol (MCP), multi-tool orchestration, and intelligent memory integration.
Open-Source Friendly Fully released under Apache 2.0 license, allowing free use, modification, and redistribution for commercial or research purposes.
You can use Qwen3 models online or deploy them locally:
Deploy via:
What makes Qwen3 different from other LLMs? Hybrid reasoning + MoE + 128K context + multilingual support = unmatched versatility and performance.
How can I enable hybrid reasoning?
Use the parameter enable_thinking=True or insert /think into prompts to activate deeper reasoning. /no_think can be used to revert.
Can I use Qwen3 for commercial products? Yes, all models are open-source under Apache 2.0, suitable for commercial and research usage.
What’s required to run Qwen3 locally? High-end GPUs are recommended for large models. Smaller models (0.6B, 1.7B) run on consumer-grade GPUs.
Is Qwen3 good for multilingual tasks? Absolutely — with 119 languages covered, it's one of the most multilingual AI models available.
| Model Name | Parameters | Type | Context Length | Architecture |
|---|---|---|---|---|
| Qwen3-235B-A22B | 235B | MoE | 128K | Hybrid + MoE |
| Qwen3-30B-A3B | 30B | MoE | 128K | Hybrid + MoE |
| Qwen3-32B | 32B | Dense | 128K | Standard |
| Qwen3-14B | 14B | Dense | 128K | Standard |
| Qwen3-8B | 8B | Dense | 128K | Standard |
| Qwen3-4B | 4B | Dense | 128K | Standard |
| Qwen3-1.7B | 1.7B | Dense | 128K | Standard |
| Qwen3-0.6B | 0.6B | Dense | 128K | Lightweight |
"Qwen3's hybrid reasoning gives us the flexibility to build intelligent systems that can think and act dynamically." – AI Researcher, University of Tokyo
"The MoE architecture really cuts costs while keeping output quality top-tier. Impressive performance!" – Startup CTO, AI Tools Company
