geekomka/Mindable

TEXT GENERATIONConcurrent Unit Cost:1Model Size:4BQuant:BF16Context Size:32kTool Calling:SupportedPublished:Aug 1, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold

Qwen3-4B is a 4.0 billion parameter causal language model developed by Qwen, featuring a unique dual-mode architecture that seamlessly switches between a 'thinking mode' for complex reasoning, math, and coding, and a 'non-thinking mode' for general dialogue. It supports a native context length of 32,768 tokens, extendable to 131,072 tokens with YaRN, and excels in reasoning, instruction-following, agent capabilities, and multilingual support across 100+ languages.

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Qwen3-4B: Dual-Mode Language Model

Qwen3-4B is a 4.0 billion parameter causal language model from the Qwen series, distinguished by its innovative ability to operate in two distinct modes: a 'thinking mode' for complex logical reasoning, mathematics, and code generation, and a 'non-thinking mode' for efficient, general-purpose dialogue. This unique architecture allows the model to optimize performance across diverse tasks by dynamically adapting its approach.

Key Capabilities

  • Enhanced Reasoning: Significantly improves upon previous Qwen models in mathematical problem-solving, code generation, and commonsense logical reasoning, particularly when operating in thinking mode.
  • Superior Human Preference Alignment: Excels in creative writing, role-playing, multi-turn conversations, and instruction following, providing a more natural and engaging user experience.
  • Advanced Agent Capabilities: Demonstrates strong performance in integrating with external tools, achieving leading results among open-source models for complex agent-based tasks in both thinking and non-thinking modes.
  • Multilingual Support: Capable of processing and generating content in over 100 languages and dialects, with robust multilingual instruction following and translation abilities.
  • Extended Context Length: Natively supports a context window of 32,768 tokens, which can be expanded to 131,072 tokens using the YaRN method for processing very long texts.

When to Use This Model

Qwen3-4B is ideal for applications requiring flexible intelligence, where both deep reasoning and efficient general conversation are needed. Its dual-mode functionality makes it suitable for:

  • Complex Problem Solving: Leverage the 'thinking mode' for tasks involving intricate logic, mathematical computations, or code development.
  • Interactive Applications: Utilize its strong human preference alignment for chatbots, creative writing assistants, and role-playing scenarios.
  • Agentic Workflows: Integrate with external tools for advanced automation and task execution.
  • Multilingual Applications: Deploy for global use cases requiring robust language understanding and generation across many languages.