Alibaba Cloud

En son yapay zeka haberleri, modeller ve sürümler Alibaba Cloud. ['CMS 2.0', 'GLM-4.7-Flash', 'Qwen 122B', 'Qwen2.5-0.5B', 'Qwen2.5-14B', 'Qwen2.5-1.5B', 'Qwen2.5-32B', 'qwen2.5:3b', 'Qwen2.5-3B', 'Qwen2.5-72B', 'qwen2.5:7b', 'Qwen2.5-7B', 'Qwen2.5-Coder', 'Qwen2.5-Max', 'Qwen2.5-VL-3B', 'Qwen2-Math', 'Qwen 3', 'Qwen3', 'Qwen3 0.6B', 'Qwen3-0.6B', 'Qwen-3 14B', 'Qwen3-14B', 'Qwen3-235B-A22B-FP8', 'Qwen3-235B-A22B-Thinking-2507', 'Qwen3 235B-Instruct', 'Qwen3-30B-A3B', 'qwen3-32b', 'Qwen3-32B', 'Qwen3-4B', 'Qwen3.5', 'Qwen3.5-122B-A17B', 'Qwen3.5-27B', 'Qwen3.5-35B-A3B', 'Qwen3.5-397B-A17B', 'qwen 3.5 4B', 'Qwen3.5-4B', 'Qwen3.5-9B', 'Qwen3.5-Flash-02-23', 'Qwen3.5-Plus-02-15', 'Qwen3.6']

Araştırma 🇺🇸

Managing Reasoning Levels in Large Language Models

Sebastian Raschka explains how reasoning modes of varying complexity (low, medium, high) work in large language models. He discusses reinforcement learning methods with verifiable rewards, as well as mechanisms for switching between modes, including approaches used in models like DeepSeek-R1, Qwen3, and GPT-5.6.

OpenAI

DeepSeek

Moonshot AI

Sebastian Raschka27.07 · 20:04

Modeller 🇨🇳

Qwen3-Coder: Alibaba Qwen's Most Agentic Model for Code

Alibaba Qwen has released Qwen3-Coder, a flagship code model with 480 billion total parameters and 35 billion active parameters, achieving state-of-the-art results among open models in agentic coding tasks, browser use, and tool use. The model supports 256K token context (up to 1M with extrapolation), was trained on 7.5 trillion tokens with 70% code, and uses large-scale reinforcement learning, including long-horizon RL for multi-step interaction in environments. Alongside the model, the Qwen Code tool based on Gemini Code has been open-sourced.

Alibaba/Qwen

Alibaba Qwen27.07 · 18:03

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