NexaAI/Qwen3-0.6B

Quickstart

Run them directly with nexa-sdk installed In nexa-sdk CLI:

NexaAI/Qwen3-0.6B

Available Quantizations

Filename	Quant type	File Size	Split	Description
Qwen3-0.6B-Q8_0.gguf	Q8_0	805 MB	false	High quality 8-bit quantization. Recommended for efficient inference.
Qwen3-0.6B-f16.gguf	f16	1.51 GB	false	Half-precision (FP16) format. Better accuracy, requires more memory.

Overview

Qwen3 is the latest generation of large language models in Qwen series, offering a comprehensive suite of dense and mixture-of-experts (MoE) models. Built upon extensive training, Qwen3 delivers groundbreaking advancements in reasoning, instruction-following, agent capabilities, and multilingual support, with the following key features:

• Uniquely support of seamless switching between thinking mode (for complex logical reasoning, math, and coding) and non-thinking mode (for efficient, general-purpose dialogue) within single model, ensuring optimal performance across various scenarios.
• Significantly enhancement in its reasoning capabilities, surpassing previous QwQ (in thinking mode) and Qwen2.5 instruct models (in non-thinking mode) on mathematics, code generation, and commonsense logical reasoning.
• Superior human preference alignment, excelling in creative writing, role-playing, multi-turn dialogues, and instruction following, to deliver a more natural, engaging, and immersive conversational experience.
• Expertise in agent capabilities, enabling precise integration with external tools in both thinking and unthinking modes and achieving leading performance among open-source models in complex agent-based tasks.
• Support of 100+ languages and dialects with strong capabilities for multilingual instruction following and translation.

Model Overview

Qwen3-0.6B has the following features:

• Type: Causal Language Models
• Training Stage: Pretraining & Post-training
• Number of Parameters: 0.6B
• Number of Paramaters (Non-Embedding): 0.44B
• Number of Layers: 28
• Number of Attention Heads (GQA): 16 for Q and 8 for KV
• Context Length: 32,768

For more details, including benchmark evaluation, hardware requirements, and inference performance, please refer to our blog, GitHub, and Documentation.

Benchmark Results

Reference

Original model card: Qwen/Qwen3-0.6B