computer science

Qwen

Qwen is a computer science topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Qwen rather than just read about it. In short: Qwen (also known as Tongyi Qianwen, Chinese: 通义千问; pinyin: Tōngyì Qiānwèn) is a family of predominantly open weights large and small language models (LLM and SLM) developed by Alibaba Cloud. Its latest version, Qwen3.8; the 2.4 trillion parameter model was the second largest and second most powerful open weights LLM and Chinese LLM released by 12 August 2026, after Kimi K3.

Key takeaways

Qwen belongs to computer science; place it in that map before memorising details.
Learn the definition first, then one example that makes the definition concrete.
Connect Qwen to a quantity you can measure, compute or draw — that is where exam questions come from.
Reproduce the core statement of Qwen from memory before moving on to harder problems.

Reference excerpt

Qwen (also known as Tongyi Qianwen, Chinese: 通义千问; pinyin: Tōngyì Qiānwèn) is a family of predominantly open weights large and small language models (LLM and SLM) developed by Alibaba Cloud. Its latest version, Qwen3.8; the 2.4 trillion parameter model was the second largest and second most powerful open weights LLM and Chinese LLM released by 12 August 2026, after Kimi K3. Larger versions often a revenue sharing agreement from providers generating more than US$50 million annually. The distilled Qwen3.8 27B was released under a more permissive Apache License. The first iteration of Qwen, based on Meta AI's Llama 1, launched a beta in April 2023, releasing the weights of its 72B model that December. A local version of Qwen used by Apple Intelligence in China, integrated with the operating system. Permissive licenses and smaller releases make them a common starting point for further fine-tuned and abliterated models in the open-source community.

Models

Qwen Alibaba launched a beta of Qwen in April 2023 under the name Tongyi Qianwen, then opened it for public use in September 2023 after regulatory clearance. The model's architecture was based on the Llama architecture developed by Meta AI. In December 2023, it released its 72B and 1.8B models for download, while Qwen 7B weights were released in August.

Qwen2 Qwen2 was released in June 2024, and in September it released some of its models with open weights, while keeping its most advanced models proprietary. Qwen2 contains both dense and sparse models. In November 2024, QwQ-32B-Preview, a model focusing on reasoning similar to OpenAI's o1, was released under the Apache 2.0 License, although only the weights were released, not the dataset or training method. QwQ has a 32K token context length and performs better than o1 on some benchmarks. It was also in November 2024 that the Accio application was launched. The Qwen-VL series is a line of visual language models that combines a vision transformer with an LLM. Alibaba released Qwen2-VL with variants of 2 billion and 7 billion parameters. In January 2025, Qwen2.5-VL was released with variants of 3, 7, 32, and 72 billion parameters. All models except the 72B variant are licensed under the Apache 2.0 license. Qwen-VL-Max is Alibaba's flagship vision model as of 2024, and is sold by Alibaba Cloud at a cost of US$0.41 per million input tokens. Alibaba has released several other model types such as Qwen-Audio and Qwen2-Math. In total, it has released more than 100 open weight models, with its models having been downloaded more than 40 million times. Fine-tuned versions of Qwen have been developed by enthusiasts, such as "Liberated Qwen", developed by San Francisco-based Abacus AI, which is a version that responds to any user request without content restrictions. On 29 January 2025, Alibaba launched Qwen2.5-Max. On 24 March 2025, Alibaba launched Qwen2.5-VL-32B-Instruct as a successor to the Qwen2.5-VL model. It was released under the Apache 2.0 license. On 26 March 2025, Qwen2.5-Omni-7B was released under the Apache 2.0 license and made available through chat.qwen.ai, as well as platforms like Hugging Face, GitHub, and ModelScope. The Qwen2.5-Omni model accepts text, images, videos, and audio as input and can generate both text and audio as output, allowing it to be used for real-time voice chatting.

Qwen3 On 28 April 2025, the Qwen3 model family was released, with all models licensed under the Apache 2.0 license. The Qwen3 model family includes both dense and MoE models. The sizes of the dense models include 0.6B, 1.7B, 4B, 8B, 14B, and 32B, and the MoE models include 30B-A3B (30B with 3B activated parameters) and 235B-A22B (235B with 22B activated parameters). They were trained on 36 trillion tokens in 119 languages and dialects. The Qwen3 collection includes:

Qwen3, which supports switching between thinking and non-thinking mode Qwen3 Base, the pretrained base model Qwen3 Instruct, which supports only non-thinking mode Qwen3 Thinking, which supports only thinking mode In addition to open-weights models, Qwen3 also includes Qwen3-Max, a proprietary large model with over 1T parameters, trained with about 36T tokens, that is available through API, and Qwen3-Max-Thinking, its reasoning variant that can generate text, pictures, or video. In February 2026, Alibaba released the open-weights Qwen3.5 and the proprietary Qwen3.5-Plus. Alibaba stated that Qwen 3.5 is able to operate desktop and mobile applications. Qwen3.5-Omni and Qwen3.6-Plus were released in April 2026 as proprietary; access to these tools is limited to the chatbots' websites and the Alibaba cloud platform. The Qwen3.6 model was released under the Apache License in the same month. Alibaba released the proprietary Qwen3.7 models in Max and Plus variants in May and June 2026, respectively. Fine-tuned and abliterated versions were released by open-source contributors, including "Qwable", incorporating tuning data from Anthropic's Fable 5. Alibaba previewed its 2.4-trillion-parameter model Qwen3.8-Max in July 2026 and announced that it would release the weights of the model. The announcement occurred a few days after Moonshot AI released its competing Kimi K3 model. The cloud version of Qwen3.8-Max was released on 3 August 2026. It uses a sparse mixture-of-experts architecture, with approximately 95 billion parameters active per forward pass, and supports a context window of up to one million tokens. Alibaba released the weights of Qwen3.8-Max as Qwen3.8-2.4T-A95B on 12 August 2026, and the open-weights model omits certain features of the cloud model, such as image input and a non-thinking mode. Qwen3.8-2.4T-A95B's license requires model providers generating more than US$50 million in revenue within 12 months to obtain a commercial license with Alibaba. On 14 August 2026, Alibaba followed up on the release of Qwen3.8-Max with the release of Qwen3.8-27B, which includes both the image input and non-thinking mode omitted in the larger model release. In contrast to the more restrictive lines of Qwen3.8-Max, this model was released with the Apache 2.0 license.

List of models

… excerpt ends here. Continue reading the full article.

Illustrations

Worked examples

Example 1 — a first encounter with Qwen

Start with the simplest possible case. Write down what Qwen claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In computer science, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Qwen before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Qwen ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Qwen

In research: Qwen appears in computer science research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry: Engineering practice reuses Qwen in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom: Qwen is common in secondary-school and first-year university syllabi. It links to neighbouring topics 2023 in artificial intelligence, 2023 software, Alibaba Group, so understanding it makes those chapters shorter.
In everyday life: Look for Qwen outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

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How to study Qwen in 20 minutes

Read the reference excerpt below once, without taking notes.
Close the page and write down what Qwen means in your own words.
Compare your version with the excerpt and mark what you missed.
Work through the three examples above with pen and paper.
Explain Qwen out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Qwen in simple terms?

Why does Qwen matter?

Because it connects several computer science ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Qwen?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Qwen.