Mahesh111000/qwen3-8b-hanabi-tinker-step105

TEXT GENERATIONPricing:Input $0.468 / Output $1.82Concurrent Unit Cost:1Model Size:8BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Aug 22, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold

Mahesh111000/qwen3-8b-hanabi-tinker-step105 is an 8.2 billion parameter causal language model from the Qwen3 series, developed by Qwen. This model uniquely supports seamless switching between a 'thinking mode' for complex logical reasoning, math, and coding, and a 'non-thinking mode' for efficient general-purpose dialogue. It features enhanced reasoning capabilities, superior human preference alignment for creative writing and multi-turn dialogues, and strong agent capabilities with support for over 100 languages, making it versatile for diverse conversational and analytical tasks.

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Qwen3-8B: A Versatile Language Model with Dynamic Thinking Modes

Mahesh111000/qwen3-8b-hanabi-tinker-step105 is an 8.2 billion parameter model from the Qwen3 series, designed to offer advanced capabilities across a wide range of applications. A standout feature is its ability to dynamically switch between a 'thinking mode' for intricate logical reasoning, mathematics, and code generation, and a 'non-thinking mode' for more efficient, general-purpose dialogue. This flexibility ensures optimized performance for various scenarios.

Key Capabilities

  • Dynamic Thinking Modes: Seamlessly transitions between a reasoning-focused mode and an efficient general dialogue mode, configurable via enable_thinking or in-prompt /think and /no_think commands.
  • Enhanced Reasoning: Demonstrates significant improvements in mathematical problem-solving, code generation, and commonsense logical reasoning.
  • Superior Human Alignment: Excels in creative writing, role-playing, multi-turn conversations, and instruction following, providing a natural and engaging user experience.
  • Advanced Agent Capabilities: Integrates precisely with external tools, achieving leading performance in complex agent-based tasks among open-source models.
  • Multilingual Support: Supports over 100 languages and dialects, offering robust multilingual instruction following and translation abilities.
  • Extended Context Length: Natively handles up to 32,768 tokens, with validated performance up to 131,072 tokens using the YaRN method for long text processing.

Good For

  • Applications requiring both complex problem-solving and efficient general conversation.
  • Creative writing, role-playing, and interactive dialogue systems.
  • Agentic workflows and tool-use scenarios.
  • Multilingual applications, including translation and instruction following in diverse languages.
  • Tasks benefiting from long context understanding, such as document analysis or extended conversations.

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