kyoganath786/Qwen2.5-3B-Instruct

TEXT GENERATIONPricing:Input $0.32 / Cached $0.064 / Output $1.6Concurrent Unit Cost:1Model Size:3.1BQuant:BF16Context Size:32kTool Calling:SupportedPublished:Sep 1, 2026License:otherArchitecture:Transformer Featherless Exclusive Cold

The kyoganath786/Qwen2.5-3B-Instruct is a 3.09 billion parameter instruction-tuned causal language model from the Qwen2.5 series, developed by Qwen. It features a 32,768 token context length and is significantly improved in coding, mathematics, and instruction following. This model excels at generating long texts, understanding structured data, and producing structured outputs like JSON, with robust multilingual support for over 29 languages.

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Qwen2.5-3B-Instruct: An Enhanced Instruction-Tuned LLM

This model is the instruction-tuned 3.09 billion parameter variant from the Qwen2.5 series, building upon the Qwen2 architecture. Developed by Qwen, it incorporates transformers with RoPE, SwiGLU, RMSNorm, and attention QKV bias, supporting a full context length of 32,768 tokens and generating up to 8,192 tokens.

Key Capabilities and Improvements

  • Enhanced Knowledge & Reasoning: Significantly improved capabilities in coding and mathematics, leveraging specialized expert models.
  • Superior Instruction Following: Demonstrates marked improvements in adhering to instructions and is more resilient to diverse system prompts, enhancing role-play and chatbot condition-setting.
  • Advanced Text Generation: Excels at generating long texts (over 8K tokens) and understanding/generating structured data, particularly JSON.
  • Multilingual Support: Offers robust support for over 29 languages, including major global languages like Chinese, English, French, Spanish, German, Japanese, and Korean.

Ideal Use Cases

  • Code Generation & Mathematical Problem Solving: Due to its specialized training in these domains.
  • Complex Instruction Following: For applications requiring precise adherence to user prompts and system instructions.
  • Long-form Content Creation: Generating detailed articles, reports, or creative writing pieces.
  • Structured Data Processing: Tasks involving parsing or generating JSON and other structured formats.
  • Multilingual Applications: Deployments requiring broad language support for chatbots or content generation.

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