Models / QwenQwen / / Qwen3 30B A3B Base API
Qwen3 30B A3B Base API
30.5B-parameter Mixture-of-Experts base model with 3.3B activated parameters trained on 36T tokens across 119 languages for efficient pretraining.

This model is not currently supported on Together AI.
Visit our Models page to view all the latest models.
To run this model you first need to deploy it on a Dedicated Endpoint.
Qwen3 30B A3B Base API Usage
Endpoint
How to use Qwen3 30B A3B Base
Model details
Architecture Overview:
• Mixture-of-Experts with 48 layers, 32/4 Q/KV heads, 128 experts (8 activated)
• 128K context window for extensive document processing
• Sparse activation patterns for computational efficiency
• Designed for fine-tuning and custom training pipelines
Training Foundation:
• Trained on 36 trillion tokens across 119 languages for foundational modeling
• Optimized for downstream fine-tuning across diverse domains
• Expert specialization enables efficient knowledge transfer
• Superior baseline performance for specialized model development
Fine-Tuning Capabilities:
• Efficient fine-tuning through expert-specific adaptation
• Supports supervised fine-tuning, reinforcement learning, and custom training approaches
• Excellent foundation for domain-specific model creation
• Maintains computational efficiency during adaptation processes
Prompting Qwen3 30B A3B Base
Base Model Characteristics:
• Foundation model designed for fine-tuning and custom applications
• No special prompting required for base model text completion
• Requires task-specific fine-tuning for optimal performance
• Supports various downstream training methodologies
Fine-Tuning Approaches:
• Supervised fine-tuning for specific task adaptation
• Reinforcement learning for behavior optimization
• Domain-specific training for specialized applications
• Custom training pipelines for unique requirements
Development Considerations:
• Excellent starting point for advanced AI model development
• Efficient expert utilization during fine-tuning processes
• Supports extensive customization for specialized domains
• Foundation for creating proprietary conversational AI systems
Applications & Use Cases
Research & Development:
• Academic research in natural language processing and AI
• Custom AI training pipelines for specialized applications
• Foundation for domain-specific model development
• Large-scale language model research and experimentation
Enterprise Customization:
• Multilingual AI applications requiring extensive customization
• STEM reasoning applications for scientific computing
• Coding assistance tools requiring specialized training
• Model fine-tuning for proprietary business applications
Advanced Applications:
• Foundation for specialized conversational AI systems
• Custom training for industry-specific requirements
• Research in mixture-of-experts architectures
• Development of next-generation AI applications requiring extensive domain adaptation