OP12138/qwen3-1.7b-base

TEXT GENERATIONPricing:Input $0.32 / Cached $0.064 / Output $1.6Concurrent Unit Cost:1Model Size:2BQuant:BF16Context Size:32kTool Calling:SupportedPublished:Aug 20, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold

Qwen3-1.7B is a 1.7 billion parameter causal language model from the Qwen series, developed by Qwen. It uniquely supports seamless switching between a 'thinking mode' for complex reasoning, math, and coding, and a 'non-thinking mode' for efficient general-purpose dialogue. This model excels in reasoning capabilities, human preference alignment, and agent functionalities, supporting over 100 languages with a 32,768 token context length.

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Qwen3-1.7B: A Versatile Language Model with Adaptive Reasoning

Qwen3-1.7B is a 1.7 billion parameter causal language model from the Qwen series, designed for advanced reasoning, instruction-following, and agent capabilities. A key differentiator is its unique ability to seamlessly switch between a 'thinking mode' for complex logical reasoning, mathematics, and code generation, and a 'non-thinking mode' for efficient, general-purpose dialogue. This adaptive approach ensures optimal performance across diverse scenarios.

Key Capabilities

  • Adaptive Reasoning: Dynamically engages a 'thinking mode' for intricate problems and a 'non-thinking mode' for general conversation, enhancing efficiency and accuracy.
  • Enhanced Performance: Demonstrates significant improvements in reasoning, instruction-following, and human preference alignment compared to previous Qwen models.
  • Multilingual Support: Offers strong capabilities across 100+ languages and dialects, including multilingual instruction following and translation.
  • Agent Integration: Excels in tool-calling and agent-based tasks, with recommended integration via Qwen-Agent for simplified development.
  • Extended Context: Features a substantial context length of 32,768 tokens, allowing for processing and generating longer, more complex texts.

When to Use This Model

  • Complex Problem Solving: Ideal for tasks requiring deep logical reasoning, mathematical computations, or code generation, leveraging its 'thinking mode'.
  • General Conversational AI: Efficiently handles standard dialogue and instruction-following in its 'non-thinking mode'.
  • Multilingual Applications: Suitable for global applications needing robust multilingual understanding and generation.
  • Agentic Workflows: Excellent for integrating with external tools and building sophisticated AI agents.

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