CodeQwen

CodeQwen

Alibaba
QwenCloud

QwenCloud

Alibaba
+
+

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About

CodeQwen is the code version of Qwen, the large language model series developed by the Qwen team, Alibaba Cloud. It is a transformer-based decoder-only language model pre-trained on a large amount of data of codes. Strong code generation capabilities and competitive performance across a series of benchmarks. Supporting long context understanding and generation with the context length of 64K tokens. CodeQwen supports 92 coding languages and provides excellent performance in text-to-SQL, bug fixes, etc. You can just write several lines of code with transformers to chat with CodeQwen. Essentially, we build the tokenizer and the model from pre-trained methods, and we use the generate method to perform chatting with the help of the chat template provided by the tokenizer. We apply the ChatML template for chat models following our previous practice. The model completes the code snippets according to the given prompts, without any additional formatting.

About

QwenCloud is an AI-native cloud platform that provides models, tools, apps, APIs, and infrastructure for building AI agents and applications. The platform offers access to featured models across LLMs, image generation, video generation, audio, speech, and multimodal workflows. QwenCloud includes flagship models such as Qwen3.8-Max, along with models for text-to-video, image generation, text-to-speech, document insight, and agentic coding. Developers can use Try AI, API keys, production-ready docs, and integrations to experiment with models and ship applications quickly. The platform also supports enterprise needs with isolated VPCs, dedicated infrastructure, compliance certifications, stable performance, and deployment monitoring. Built for developers, AI teams, enterprises, and agent builders, QwenCloud helps organizations create, test, deploy, and scale AI-native products.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

Anyone seeking an AI tool to improve their natural language understanding operations and text generation tasks

Audience

Developers, AI agent builders, startups, enterprises, product teams, engineering teams, multimodal AI teams, creators, cloud architects, and organizations that need LLM APIs, image generation, video generation, speech synthesis, document insight, agentic coding, API keys, token plans, free model credits, cloud infrastructure, enterprise security, compliance, low-latency inference, and scalable AI application deployment

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

Free
Free Version
Free Trial

Pricing

No information available.
Free Version
Free Trial

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

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Reviews/Ratings

Overall 5.0 / 5
ease 4.0 / 5
features 5.0 / 5
design 4.0 / 5

Pros & Cons from Real Users

Pros

  • QwenCloud looks really useful because it puts the Qwen ecosystem into a more complete developer platform. Instead of just testing a model in isolation, you get access to Qwen LLMs, multimodal models, APIs, agent tools, and cloud services in one place. I like that it is clearly built for AI apps and agents. The platform is positioned around low-latency inference, scaling, model access, deployment, monitoring, and ready-to-use AI capabilities, which is exactly what teams need when moving from prototype to production. The Qwen model ecosystem is also a big advantage. Qwen already has strong momentum across text, coding, image, video, and multimodal use cases, and QwenCloud gives developers a more direct way to build products around that stack.

Cons

  • I would still want to test pricing, latency, uptime, regional availability, documentation quality, and API reliability before building anything critical on it. A cloud AI platform can sound great on paper, but production use always comes down to stability and developer experience. I would also want more clarity around which models are available, how quickly new Qwen releases show up, and how easy it is to move workloads if requirements change.

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

Alibaba
Founded: 1999
China
github.com/QwenLM/CodeQwen1.5

Company Information

Alibaba
Founded: 1999
China
www.qwencloud.com

Alternatives

CodeGemma

CodeGemma

Google

Alternatives

QwenWork

QwenWork

Alibaba
Qwen-7B

Qwen-7B

Alibaba
Qwen3.5

Qwen3.5

Alibaba
Qwen2.5-Max

Qwen2.5-Max

Alibaba
Qwen3.8-Max

Qwen3.8-Max

Alibaba
Qwen2

Qwen2

Alibaba
Qwen3.6-27B

Qwen3.6-27B

Alibaba
Qwen

Qwen

Alibaba
Qwen3-VL

Qwen3-VL

Alibaba

Categories

Categories

Integrations

Qwen Studio
Alibaba Cloud
AtCoder
Code Llama
Codeforces
Conda
DeepSeek Coder
GPT-4
LeetCode
PyTorch
Python
Qwen
Qwen-Audio-3.0-TTS-Flash
Qwen-Audio-3.0-TTS-Plus
Qwen-Image-2.0
Qwen-Image-3.0
Qwen3.8-27B
Qwen3.8-Max
StarCoder
Wan3.0-Video

Integrations

Qwen Studio
Alibaba Cloud
AtCoder
Code Llama
Codeforces
Conda
DeepSeek Coder
GPT-4
LeetCode
PyTorch
Python
Qwen
Qwen-Audio-3.0-TTS-Flash
Qwen-Audio-3.0-TTS-Plus
Qwen-Image-2.0
Qwen-Image-3.0
Qwen3.8-27B
Qwen3.8-Max
StarCoder
Wan3.0-Video
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