CodeQwen1.5: Alibaba's Open-Source Code LLM Release
Alibaba's Qwen team released CodeQwen1.5, an open-source large language model specialized for code generation and programming assistance. The release is positioned as a transparent, accessible alternative to proprietary coding assistants like GitHub Copilot, addressing concerns around cost, privacy, security, and copyright. The model is available on GitHub, HuggingFace, and ModelScope.
Related guides (4)
Related events (8)
Qwen2.5-Coder Released: Next-Generation Open-Source Coding Model
Alibaba's Qwen team has released Qwen2.5-Coder, the next generation of their open-source coding-specialized language model, succeeding CodeQwen1.5 which launched in April 2024. The release also marks a rebranding from CodeQwen to Qwen-Coder. The model is available on GitHub, Hugging Face, and ModelScope.
Introducing the Qwen Series: Overview of Alibaba's Open-Source LLM Journey
Alibaba's Qwen team published a retrospective introduction to the Qwen series of large language models, four months after the initial Qwen-7B open-source release. The post consolidates links to their paper, GitHub, Hugging Face, and ModelScope repositories, and outlines the team's objectives for the open-source LLM program. It serves as a canonical reference point for the Qwen model family's public positioning.
Qwen2.5-Coder Series Open-Sourced: 32B Model Claims SOTA, Matches GPT-4o on Coding
Alibaba's Qwen team has open-sourced the Qwen2.5-Coder family of code-specialized language models, with the flagship 32B-Instruct variant claiming state-of-the-art performance among open-source code models and parity with GPT-4o on coding benchmarks. The release spans multiple model sizes, expanding on previously released smaller variants. The models are described as combining strong coding ability with general reasoning and mathematical skills.
Qwen2.5: Large-Scale Open-Source Foundation Model Family Release
Alibaba's Qwen team has released Qwen2.5, described as potentially the largest open-source model release in history, following three months of development after Qwen2. The release encompasses a family of foundation models with improvements in knowledge and reasoning capabilities. The announcement targets developers who have been building on Qwen2 and incorporates feedback from that community.
Qwen3-Coder: 480B MoE Agentic Coding Model Released by Alibaba/Qwen Team
Alibaba's Qwen team has released Qwen3-Coder, a family of code-focused models with the flagship variant being Qwen3-Coder-480B-A35B-Instruct, a 480B-parameter Mixture-of-Experts model with 35B active parameters. It supports 256K native context length and up to 1M tokens via extrapolation. The model claims state-of-the-art results among open-weight models on agentic coding, browser-use, and tool-use benchmarks, with performance described as comparable to Claude Sonnet 4.
Qwen1.5-32B: Alibaba's 30B-Parameter Capstone for the Qwen1.5 Series
Alibaba's Qwen team released Qwen1.5-32B, a ~30 billion parameter open-weights language model positioned as the capstone of the Qwen1.5 series. The model targets the emerging consensus around 30B parameters as an optimal balance between performance, memory footprint, and inference efficiency. It is released alongside code on GitHub, weights on HuggingFace and ModelScope, and an interactive demo.
Qwen2.5-Math: Open-Source Mathematical LLM Series Released
Alibaba's Qwen team has released Qwen2.5-Math, an upgraded series of open-source mathematical LLMs including base and instruction-tuned models at 1.5B, 7B, and 72B parameter scales, plus a mathematical reward model. The models support Chain-of-Thought (CoT) and Tool-Integrated Reasoning (TIR) for English and Chinese math problem solving. This follows the Qwen2-Math release approximately one month prior and is claimed to be the leading open-source mathematical LLM series.
Introducing Qwen1.5: Open-Source Models Across Eight Sizes Including MoE
Alibaba's Qwen team released Qwen1.5, open-sourcing both base and chat models in eight sizes ranging from 0.5B to 110B parameters, plus a Mixture-of-Experts (MoE) variant. The release emphasizes developer experience improvements alongside model quality. Models are available on GitHub, Hugging Face, and ModelScope.