qwen3:0.6b

2M 1 week ago

Qwen3 is the latest generation of large language models in Qwen series, offering a comprehensive suite of dense and mixture-of-experts (MoE) models.

tools thinking 0.6b 1.7b 4b 8b 14b 30b 32b 235b

1 week ago

7df6b6e09427 · 523MB

model
qwen3
·
752M
·
Q4_K_M
template
{{- $lastUserIdx := -1 -}} {{- range $idx, $msg := .Messages -}} {{- if eq $msg.Role "user" }}{{ $l
license
Apache License Version 2.0, January 2004
params
{ "repeat_penalty": 1, "stop": [ "<|im_start|>", "<|im_end|>" ], "te

Readme

Qwen 3 logo

This model requires Ollama 0.6.6 or later. Download Ollama

Qwen 3 is the latest generation of large language models in Qwen series, offering a comprehensive suite of dense and mixture-of-experts (MoE) models. The flagship model, Qwen3-235B-A22B, achieves competitive results in benchmark evaluations of coding, math, general capabilities, etc., when compared to other top-tier models such as DeepSeek-R1, o1, o3-mini, Grok-3, and Gemini-2.5-Pro. Additionally, the small MoE model, Qwen3-30B-A3B, outcompetes QwQ-32B with 10 times of activated parameters, and even a tiny model like Qwen3-4B can rival the performance of Qwen2.5-72B-Instruct.

  • 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.

Evaluation 1

Evaluation 2

Models

0.6B parameter model

ollama run qwen3:0.6b

1.7B parameter model

ollama run qwen3:1.7b

4B parameter model

ollama run qwen3:4b

8B parameter model

ollama run qwen3:8b

14B parameter model

ollama run qwen3:14b

32B parameter model

ollama run qwen3:32b

30B mixture-of-experts model with 3B active parameters

ollama run qwen3:30b-a3b

235B mixture-of-experts model with 22B active parameters

ollama run qwen3:235b-a22b

Reference