content.raw: Qwen 3 models released🔥
content.type: text
content.value: Qwen 3 models released🔥
content.type: new_line
content.raw: It offers 2 MoE and 6 dense models with following parameter sizes: 0.6B, 1.7B, 4B, 8B, 14B, 30B(MoE), 32B, and 235B(MoE). 
content.type: text
content.value: It offers 2 MoE and 6 dense models with following parameter sizes: 0.6B, 1.7B, 4B, 8B, 14B, 30B(MoE), 32B, and 235B(MoE). 
content.type: new_line
content.raw: Models: 
content.type: text
content.value: Models: 
content.raw: https://huggingface.co/collections/Qwen/qwen3-67dd247413f0e2e4f653967f
content.id: Qwen/qwen3-67dd247413f0e2e4f653967f
content.type: collection
content.type: resource
content.url: https://huggingface.co/collections/Qwen/qwen3-67dd247413f0e2e4f653967f
content.type: new_line
content.raw: Blog: 
content.type: text
content.value: Blog: 
content.href: https://qwenlm.github.io/blog/qwen3/
content.raw: https://qwenlm.github.io/blog/qwen3/
content.type: link
content.type: new_line
content.raw: Demo: 
content.type: text
content.value: Demo: 
content.raw: https://huggingface.co/spaces/Qwen/Qwen3-Demo
content.id: Qwen/Qwen3-Demo
content.type: space
content.type: resource
content.url: https://huggingface.co/spaces/Qwen/Qwen3-Demo
content.type: new_line
content.raw: GitHub: 
content.type: text
content.value: GitHub: 
content.href: https://github.com/QwenLM/Qwen3
content.raw: https://github.com/QwenLM/Qwen3
content.type: link
content.type: new_line
content.type: new_line
content.raw: ✅ Pre-trained 119 languages(36 trillion tokens) and dialects with strong translation and instruction following abilities. (Qwen2.5 was pre-trained on 18 trillion tokens.)
content.type: text
content.value: ✅ Pre-trained 119 languages(36 trillion tokens) and dialects with strong translation and instruction following abilities. (Qwen2.5 was pre-trained on 18 trillion tokens.)
content.type: new_line
content.raw: ✅Qwen3 dense models match the performance of larger Qwen2.5 models. For example, Qwen3-1.7B/4B/8B/14B/32B perform like Qwen2.5-3B/7B/14B/32B/72B.
content.type: text
content.value: ✅Qwen3 dense models match the performance of larger Qwen2.5 models. For example, Qwen3-1.7B/4B/8B/14B/32B perform like Qwen2.5-3B/7B/14B/32B/72B.
content.type: new_line
content.raw: ✅ Three stage done while pretraining:
content.type: text
content.value: ✅ Three stage done while pretraining:
content.type: new_line
content.raw: 	•	Stage 1: General language learning and knowledge building. 
content.type: text
content.value: 	•	Stage 1: General language learning and knowledge building. 
content.type: new_line
content.raw: 	•	Stage 2: Reasoning boost with STEM, coding, and logic skills. 
content.type: text
content.value: 	•	Stage 2: Reasoning boost with STEM, coding, and logic skills. 
content.type: new_line
content.raw: 	•	Stage 3: Long context training 
content.type: text
content.value: 	•	Stage 3: Long context training 
content.type: new_line
content.raw: ✅ It supports MCP  in the model 
content.type: text
content.value: ✅ It supports MCP  in the model 
content.type: new_line
content.raw: ✅ Strong agent skills 
content.type: text
content.value: ✅ Strong agent skills 
content.type: new_line
content.raw: ✅ Supports seamless between thinking mode (for hard tasks like math and coding) and non-thinking mode (for fast chatting) inside chat template. 
content.type: text
content.value: ✅ Supports seamless between thinking mode (for hard tasks like math and coding) and non-thinking mode (for fast chatting) inside chat template. 
content.type: new_line
content.raw: ✅ Better human alignment for creative writing, roleplay, multi-turn conversations, and following detailed instructions. 
content.type: text
content.value: ✅ Better human alignment for creative writing, roleplay, multi-turn conversations, and following detailed instructions. 
content.type: new_line
rawContent: Qwen 3 models released🔥
  It offers 2 MoE and 6 dense models with following parameter sizes: 0.6B, 1.7B, 4B, 8B, 14B, 30B(MoE), 32B, and 235B(MoE). 
  Models: https://huggingface.co/collections/Qwen/qwen3-67dd247413f0e2e4f653967f
  Blog: https://qwenlm.github.io/blog/qwen3/
  Demo: https://huggingface.co/spaces/Qwen/Qwen3-Demo
  GitHub: https://github.com/QwenLM/Qwen3
  
  ✅ Pre-trained 119 languages(36 trillion tokens) and dialects with strong translation and instruction following abilities. (Qwen2.5 was pre-trained on 18 trillion tokens.)
  ✅Qwen3 dense models match the performance of larger Qwen2.5 models. For example, Qwen3-1.7B/4B/8B/14B/32B perform like Qwen2.5-3B/7B/14B/32B/72B.
  ✅ Three stage done while pretraining:
  	•	Stage 1: General language learning and knowledge building. 
  	•	Stage 2: Reasoning boost with STEM, coding, and logic skills. 
  	•	Stage 3: Long context training 
  ✅ It supports MCP  in the model 
  ✅ Strong agent skills 
  ✅ Supports seamless between thinking mode (for hard tasks like math and coding) and non-thinking mode (for fast chatting) inside chat template. 
  ✅ Better human alignment for creative writing, roleplay, multi-turn conversations, and following detailed instructions. 
  
reactions.reaction: 🔥
reactions.users: merterbak DmitryRyumin agentlans Fishtiks John6666 aust-t zhanglu Saikat Makar7 Kastakin AdinaY olamedia kw1004 uzvisa iky1e Haloons victor
reactions.reaction: 🚀
reactions.users: merterbak John6666 Makar7 BuiDoan