Qwen is Alibaba’s family of artificial intelligence models and products. It began as Tongyi Qianwen, a Chinese and English large language model announced in April 2023. The project soon developed into an open-weight model family for general language work, coding, mathematics, vision, audio, reasoning, image generation, and AI agents.
Qwen3.7 is Alibaba’s latest general Qwen generation. The proprietary Qwen3.7-Max arrived on May 20, 2026, followed by the multimodal Qwen3.7-Plus on June 1. A June 10 Max snapshot added visual understanding. These hosted models focus on long-running agents, coding, office workflows, visual understanding, and tool use. Qwen3.6-27B, released on April 22, 2026, is the latest open-weight general Qwen model.
This Qwen timeline tracks the main model release dates, specialist families, reasoning models, and products that shaped the project. We separate downloadable models from hosted services and explain how Qwen Coder, Qwen VL, QwQ, Omni, Qwen Chat, and Qwen Code fit into the larger family.
Last Updated: July 12, 2026
Qwen in Brief
| Milestone | Details |
|---|---|
| First public announcement | Tongyi Qianwen was unveiled on April 11, 2023. |
| First open-weight release | Qwen-7B and Qwen-7B-Chat arrived on August 3, 2023. |
| Qwen3 release | Qwen3 was announced on April 28, 2025. Its public repositories record the release on April 29. |
| Latest general generation | Qwen3.7, whose Max and Plus flagships are hosted proprietary models. |
| Latest open-weight general model | Qwen3.6-27B, released on April 22, 2026. |
| Qwen Code launch | Qwen Code launched with Qwen3-Coder on July 22, 2025. |
Qwen Timeline at a Glance
| Milestone | Date and significance |
|---|---|
| Tongyi Qianwen announced | April 11, 2023 Alibaba Cloud publicly introduced the large language model that became the Qwen family. |
| First open-weight Qwen model | August 3, 2023 Qwen-7B and Qwen-7B-Chat began Qwen’s public model release history. |
| Qwen-VL | August 22, 2023 The first vision-language branch added image understanding, text reading, and visual grounding. |
| Qwen1.5 | February 4, 2024 A wider size range and direct Transformers support reduced setup and hardware barriers. |
| Qwen2 | June 7, 2024 The second generation expanded multilingual support, context length, coding, and mathematics. |
| Qwen2.5 | September 19, 2024 General, Coder, and Math models arrived as a coordinated family. |
| QwQ-32B-Preview | November 28, 2024 Qwen opened a separate research line for longer, step-by-step reasoning. |
| Qwen2.5-Omni | March 27, 2025 One end-to-end model could process text, images, audio, and video and return text or speech. |
| Qwen3 | April 28, 2025 Thinking and non-thinking behavior entered the main general-purpose model family. |
| Qwen3-Coder and Qwen Code | July 22, 2025 The agent-oriented coding model launched alongside an open-source terminal coding tool. |
| Qwen-Image | August 4, 2025 Qwen gained a dedicated open-weight image generation and editing model. |
| Qwen3-VL and Qwen3-Omni | September 2025 The visual and full multimodal branches added deeper reasoning, agent use, and real-time speech. |
| Qwen3.5 | February 15, 2026 The main open-weight family became natively multimodal and more focused on agents. |
| Qwen3.6 | April 2026 Hosted and open-weight releases strengthened agentic coding and multimodal work. |
| Qwen3.7 | May-June 2026 Qwen3.7-Max and Qwen3.7-Plus moved the hosted flagship line toward long-running multimodal agents. |
Qwen Model Release History
| Release | What changed |
|---|---|
| Qwen3.7-Max visual snapshot June 10, 2026 General / multimodal agent | Updated the hosted Max model with visual understanding and multimodal agent interaction. |
| Qwen3.7-Plus June 1, 2026 General / multimodal agent | Hosted vision-language agent model based on the Qwen3.7 generation, with stronger visual understanding and agent work. |
| Qwen3.7-Max May 20, 2026 General / agent | Proprietary flagship for coding, office automation, tool use, and autonomous tasks that may run for hundreds or thousands of steps. |
| Qwen3.6 open models April 2026 General / multimodal | Open-weight MoE and dense models brought Qwen3.6’s coding, reasoning, and visual capabilities to local deployment. |
| Qwen3.6-Max-Preview April 18, 2026 General / agent | Hosted preview with stronger coding agents, knowledge, and instruction following than Qwen3.6-Plus. |
| Qwen3.6-Plus April 2, 2026 General / multimodal agent | Hosted production model with a one-million-token context window and an emphasis on repository work, visual coding, and multi-step execution. |
| Qwen3.5 February 15, 2026 General / native multimodal | Introduced a natively multimodal main generation for text, images, video, reasoning, coding, and agent tasks. The first open model was Qwen3.5-397B-A17B. |
| Qwen3-VL-Embedding and Reranker January 7, 2026 Retrieval | Extended semantic search and reranking from text to mixed text, image, screenshot, and video inputs. |
| Qwen3-Omni September 21, 2025 Omni | Native end-to-end model for text, images, audio, and video, with streamed text and speech output. |
| Qwen3-VL September 22, 2025 Vision-language | Added stronger visual perception, spatial and video reasoning, longer context, and visual agent behavior. |
| Qwen3-Max September 24, 2025 General / hosted flagship | The proprietary trillion-parameter flagship launched in an Instruct version, with a separate Thinking version in development. |
| Qwen3-Next September 10, 2025 General / architecture research | Introduced a highly sparse hybrid-attention architecture designed for faster long-context inference. Its design later informed Qwen3.5. |
| Qwen-Image August 4, 2025 Image generation | Dedicated open-weight model for text-to-image generation and image editing, with particular attention to text inside images. |
| Qwen3-Coder and Qwen Code July 22, 2025 Coder / developer tool | Paired an agent-oriented coding model with an open-source command-line coding agent. |
| Qwen VLo Preview June 26, 2025 Vision / image generation | Experimental Qwen Chat model combined visual understanding, image generation, and instruction-based editing. |
| Qwen3-Embedding and Reranker June 2025 Retrieval | Added multilingual text embeddings and reranking models for search, retrieval, clustering, and classification. |
| Qwen3 April 28, 2025 General / reasoning | Unified thinking and non-thinking modes in the main family and expanded agent, coding, multilingual, dense, and MoE options. |
| QVQ-Max March 28, 2025 Visual reasoning | Hosted visual reasoning model that analyzed images and videos before answering. |
| Qwen2.5-Omni March 27, 2025 Omni | First open Qwen model to accept text, images, audio, and video and stream both text and speech responses. |
| QwQ-32B March 6, 2025 Reasoning | Open-weight reasoning model trained with reinforcement learning for mathematics, coding, general problem solving, and tool use. |
| Qwen2.5-VL January 26, 2025 Vision-language | Improved document, chart, long-video, localization, structured-output, and visual agent capabilities. |
| QwQ-32B-Preview November 28, 2024 Reasoning | Experimental open-weight model that introduced Qwen’s dedicated text reasoning branch. |
| Qwen2.5-Coder full family November 12, 2024 Coder | Completed the coding family with six sizes from 0.5B to 32B. |
| Qwen2.5 September 19, 2024 General / Coder / Math | Released a coordinated family with better structured output, longer generation, code, mathematics, and instruction following. |
| Qwen2-VL August 29, 2024 Vision-language | Added dynamic image resolution, video understanding, visual localization, and wider multilingual text recognition. |
| Qwen2-Audio August 9, 2024 Audio-language | Accepted speech, sound, music, and text as input and returned text without requiring a separate speech-recognition stage. |
| Qwen2 June 7, 2024 General | Expanded multilingual coverage and improved long-context, coding, mathematics, and model-size choices. |
| CodeQwen1.5 April 16, 2024 Coder | Established Qwen’s first dedicated open coding model family. |
| Qwen1.5 February 4, 2024 General | Expanded the size range, improved developer compatibility, and later added Qwen’s first MoE release. |
| Qwen-72B and Qwen-1.8B November 30, 2023 General | Extended the first generation to both a small model and a much larger flagship. |
| Qwen-14B and Qwen-Agent September 25, 2023 General / agent framework | Added a mid-sized language model and released the framework used to build Qwen assistants with tools. |
| Qwen-VL August 22, 2023 Vision-language | First open Qwen models for image understanding, text reading, grounding, and multimodal chat. |
| Qwen-7B and Qwen-7B-Chat August 3, 2023 General | First public open-weight Qwen language models. |
| Tongyi Qianwen April 11, 2023 Hosted language model | Alibaba Cloud publicly introduced the original model and opened enterprise beta access in China. |
Current Qwen Model and Product Lineup
| Model or product line | What it is for |
|---|---|
| General Qwen models Foundation models | Language, reasoning, coding, tool use, and increasingly native visual understanding. Examples: Qwen3.5, Qwen3.6, Qwen3.7 |
| Qwen Coder Specialist models | Code generation, completion, repair, repository understanding, and coding agents. Examples: Qwen2.5-Coder, Qwen3-Coder |
| Qwen VL Vision-language models | Images, documents, charts, video, visual localization, and visual reasoning. Examples: Qwen2.5-VL, Qwen3-VL |
| Qwen Omni Full multimodal models | Text, image, audio, and video input with text and natural speech output. Examples: Qwen2.5-Omni, Qwen3-Omni |
| Qwen reasoning Reasoning models or modes | Longer inference for mathematics, coding, planning, problem solving, and visual reasoning. Examples: QwQ, QVQ, Qwen3 Thinking |
| Media models Generative and speech models | Image generation and editing, speech recognition, speech generation, and audio understanding. Examples: Qwen-Image, Qwen3-ASR, Qwen3-TTS |
| Retrieval and safety Specialist models | Embeddings, reranking, multimodal retrieval, and content safety classification. Examples: Qwen3-Embedding, Qwen3Guard |
| Qwen Studio User product | Web, desktop, and mobile access to hosted Qwen models and tools. Examples: Chat, files, images, agents |
| Qwen-Agent Developer framework | Tool calling, planning, memory, code execution, retrieval, and MCP-based applications. Examples: Browser Assistant, Code Interpreter |
| Qwen Code Developer tool | Terminal-based coding agent for inspecting repositories, editing files, running commands, and completing development tasks. Examples: Qwen Code CLI |
| Model Studio Cloud platform | Hosted Qwen APIs, deployment services, model evaluation, tuning, and access to third-party models. Examples: Alibaba Cloud Model Studio |
Qwen3.7-Plus, Qwen Studio, Qwen Code, and Model Studio are different types of products. Qwen3.7-Plus is a hosted model. Qwen Studio provides web, desktop, and mobile access to Qwen. Qwen Code is a coding agent that works with repositories and terminal commands. Model Studio provides cloud APIs and deployment services.
How to Read Qwen Model Names
Qwen names combine a generation, a size or service tier, and sometimes a training or capability label. For example, Qwen3.6-35B-A3B belongs to the Qwen3.6 generation, has about 35 billion total parameters, and activates about 3 billion parameters for each token. Qwen3-VL-8B-Thinking identifies an 8B vision-language model tuned for longer visual reasoning.
| Name or suffix | Meaning |
|---|---|
| 0.5B, 7B, 32B | The approximate number of model parameters. Larger numbers usually require more memory, but size alone does not determine quality. |
| A3B or A22B | The approximate number of active parameters in a mixture-of-experts model. Qwen3-30B-A3B has about 30B total parameters but uses about 3B for each token. |
| Base | A pretrained checkpoint intended for research, adaptation, or further training rather than ordinary chat. |
| Chat or Instruct | A post-trained model designed to follow instructions and respond conversationally. |
| Thinking | A model or mode that spends more inference time on multi-step reasoning before giving its final answer. |
| VL | Vision-language. These models understand images, documents, charts, and video alongside text. |
| Omni | A full multimodal line that can combine text, image, audio, and video and may return speech as well as text. |
| Coder, Math, ASR, TTS | Specialist lines for programming, mathematics, speech recognition, and speech generation. |
| Plus, Max, Flash, Turbo | Hosted service tiers. Max usually identifies a flagship, Plus a general production model, and Flash or Turbo a faster service. These names do not guarantee downloadable weights. |
| Preview or a dated suffix | An early model or a fixed service snapshot. Its announcement date, API availability date, and later stable release may differ. |
Qwen is the international model name and a shortened form of Qianwen. Tongyi Qianwen is the original Chinese product name. Qwen Studio is the user application, while Qwen model names refer to the systems available inside the product, through APIs, or as downloadable weights.
Qwen Timeline by Year
Table Of Contents
- 2026: Qwen3.5, Qwen3.6, and Qwen3.7 Shift Toward Multimodal Agents
- 2025: Reasoning, Agents, Coder, VL, Omni, and Image Generation
- 2024: Qwen1.5, Qwen2, Qwen2.5, and the First Reasoning Models
- 2023: Tongyi Qianwen Becomes an Open Model Family
- General Qwen Models
- Qwen Coder Models
- Qwen VL and Qwen Omni Models
- Qwen Reasoning Models
- Specialized Qwen Models
- Qwen Studio and Qwen Chat
- Qwen-Agent
- Qwen Code
- Alibaba Cloud Model Studio
- From Hosted Model to Open-Weight Family
- Qwen2.5 Brought the Specialist Lines Together
- Qwen VL Moved Beyond Image Recognition
- Reasoning Moved into the Main Model Line
- Qwen Code Connected the Models to Software Work
2026: Qwen3.5, Qwen3.6, and Qwen3.7 Shift Toward Multimodal Agents
| Release | What changed |
|---|---|
| Qwen3.7-Max visual snapshot June 10 | The dated API snapshot added visual understanding to the Max line. Qwen3.7-Max could now perceive real-world scenes and support multimodal agent interactions instead of remaining text-only. |
| Qwen3.7-Plus June 1 | The Plus model added vision-language capabilities to the Qwen3.7 generation. It is a multimodal agent model for visual understanding, coding, and tool-based tasks. It is a hosted model rather than a downloadable open-weight checkpoint. |
| Qwen3.7-Max May 20 | Alibaba introduced its new proprietary flagship for the agent era. The model targets code development, office automation, tool use, and autonomous workflows that continue across long sequences of actions. |
| Qwen3.6-27B April 22 | This dense open-weight model brought Qwen3.6’s multimodal reasoning and agentic coding to a widely used local-deployment size. Its dense architecture also avoided the routing requirements of an MoE model. |
| Qwen3.6-Max-Preview April 18 | The hosted preview improved coding-agent performance, world knowledge, and instruction following over Qwen3.6-Plus. It remained a proprietary preview under active development. |
| Qwen3.6 open models April | Qwen released selected Qwen3.6 weights, including an efficient 35B-A3B MoE model and a 27B dense model. The open family retained text and visual reasoning while placing more emphasis on real repository work. |
| Qwen3.6-Plus April 2 | The hosted Plus model combined a one-million-token context window with stronger repository-level coding, visual coding, document analysis, video reasoning, and multi-step tool work. It was released through Qwen’s user product and Alibaba Cloud Model Studio. |
| Qwen3.5 February 15 | Qwen3.5 made native multimodality part of the main open-weight family rather than a separate VL extension. The first release, Qwen3.5-397B-A17B, combined text, image, and video understanding with reasoning, coding, and agent abilities. |
| Qwen3-ASR and Qwen3-TTS January | Dedicated open speech families separated automatic speech recognition and speech generation from the audio and Omni models. ASR covered multilingual transcription and alignment, while TTS focused on expressive and streaming speech synthesis. |
| Qwen3-VL-Embedding and Reranker January 7 | The retrieval line gained a shared representation for text, images, screenshots, documents, and video. This supported cross-modal search and ranking rather than conversational generation. |
2025: Reasoning, Agents, Coder, VL, Omni, and Image Generation
| Release | What changed |
|---|---|
| Qwen3-Max September 24 | The proprietary Max line scaled the Qwen3 architecture beyond the downloadable flagship models. The initial hosted release centered on instruction following, coding, agents, and general knowledge, with a separate Thinking version developed for heavier reasoning. |
| Qwen3-VL September 22 | The third VL generation added stronger image and video reasoning, spatial understanding, visual agent behavior, and long-context support. Instruct and Thinking variants separated direct visual responses from longer visual reasoning. |
| Qwen3-Omni September 21 | The native Omni model handled text, images, audio, and video in one end-to-end system. It could return text and speech in real time, so Qwen no longer needed a chain of separate models for every conversational modality. |
| Qwen3-Next September 10 | This experimental architecture combined hybrid attention, greater MoE sparsity, and multi-token prediction. It reduced the cost of long-context inference and became an architectural step toward Qwen3.5. |
| Qwen-Image August 4 | Qwen released a dedicated open-weight image model instead of limiting visual generation to a Qwen Chat preview. The model supported generation and editing and paid particular attention to Chinese and English text rendering. |
| Qwen3-Coder and Qwen Code July 22 | Qwen3-Coder was trained for repository-scale coding, browser use, tool calls, and multi-step software tasks. Qwen Code added a terminal agent that could apply those capabilities to files and commands. |
| Qwen VLo Preview June 26 | VLo connected image understanding with image creation and editing inside Qwen Chat. It was a hosted preview, not the same release as the later open-weight Qwen-Image model. |
| Qwen3-Embedding and Reranker June | These models added multilingual vector representations and relevance scoring for search and retrieval systems. They served a different role from Qwen’s generative chat models. |
| Qwen3 April 28 | Qwen brought deliberate reasoning into its main model generation. Most initial models could switch between thinking and non-thinking behavior, while the family also expanded language coverage, agent use, and efficient MoE deployment. |
| QVQ-Max March 28 | The visual reasoning line moved beyond ordinary image description. QVQ-Max inspected images and videos and used longer reasoning to solve visual mathematics, charts, code, and practical questions. |
| Qwen2.5-Omni March 27 | The first open Omni model accepted text, images, audio, and video and returned streamed text or speech. Its Thinker-Talker design joined perception and spoken response within one end-to-end model. |
| QwQ-32B March 6 | The production-oriented open reasoning release used reinforcement learning for mathematics, code, general problem solving, and tools. It replaced the earlier preview as the clearest separate Qwen reasoning model before Qwen3. |
| Qwen2.5-VL January 26 | The updated VL family improved document parsing, charts, long video, object localization, and structured output. It could also act as a visual agent that selected actions from screen content. |
2024: Qwen1.5, Qwen2, Qwen2.5, and the First Reasoning Models
| Release | What changed |
|---|---|
| QwQ-32B-Preview November 28 | QwQ, short for Qwen with Questions, was Qwen’s first public model built around extended text reasoning. The experimental release exposed both the promise and early problems of long reasoning, including loops and mixed-language output. |
| Qwen2.5-Coder full family November 12 | The Coder line expanded to six sizes from 0.5B through 32B. Developers could choose between compact local models and a larger model for code generation, repair, completion, and code-agent research. |
| Qwen2.5 September 19 | Qwen2.5 arrived with general language, Coder, and Math models under one generation. It improved structured data, JSON output, long responses, instruction following, coding, mathematics, and the range of available model sizes. |
| Qwen2-VL August 29 | The second visual family processed images at dynamic resolutions and added video understanding and visual localization. Smaller models were open under Apache 2.0, while the largest model initially appeared through the API. |
| Qwen2-Audio August 9 | The new audio-language model interpreted speech, environmental sounds, and music from direct audio input. It also allowed spoken instructions without a separate transcription module. |
| Qwen2 June 7 | Qwen2 improved coding and mathematics, supported many more languages, and extended selected models to 128K context. The family included both dense models and an MoE option. |
| CodeQwen1.5 April 16 | The first dedicated Qwen coding family separated code training from the general chat line. It included base and chat checkpoints and laid the groundwork for the later Qwen-Coder name. |
| Qwen1.5 February 4 | Qwen1.5 expanded the model range and reduced setup friction through direct integration with Hugging Face Transformers. A later MoE checkpoint introduced Qwen’s first public mixture-of-experts model. |
| Qwen-VL-Plus and Qwen-VL-Max January 25 | Hosted upgrades improved high-resolution image reading, document analysis, and visual reasoning. They extended the first VL generation while Qwen2-VL was still in development. |
2023: Tongyi Qianwen Becomes an Open Model Family
| Release | What changed |
|---|---|
| Qwen-72B and Qwen-1.8B November 30 | The first generation expanded in both directions. Qwen-72B became its large open flagship, while Qwen-1.8B supplied a compact option for hardware with tighter memory limits. |
| Qwen-14B and Qwen-Agent September 25 | Qwen added a model between 7B and 72B and released its application framework. Qwen-Agent supported tool use and became the base for examples such as a browser assistant and code interpreter. |
| Qwen-VL and Qwen-VL-Chat August 22 | The first visual branch accepted images and text and returned natural-language answers or locations inside an image. It supported document text, multiple images, and visual grounding in Chinese and English. |
| Qwen-7B and Qwen-7B-Chat August 3 | These were the first publicly released Qwen weights. The base checkpoint served research and adaptation, while the Chat version was tuned for instructions and conversation. |
| Tongyi Qianwen unveiled April 11 | Alibaba Cloud introduced the original hosted large language model and opened enterprise beta applications in China. The company planned to connect it with services such as DingTalk and Tmall Genie and offer cloud access to developers. |
Qwen Model Families Explained
General Qwen Models
The general line began with Qwen-7B, Qwen-14B, and Qwen-72B. Qwen1.5 improved model choice and compatibility, while Qwen2 added languages, longer context, and stronger code and math abilities. Qwen2.5 turned the release into a coordinated family of general and specialist models.
Qwen3 changed the role of the main line because reasoning no longer required a separate QwQ model. Initial Qwen3 checkpoints could use a thinking mode for difficult work or answer directly when extra reasoning was unnecessary. Qwen3-Next then tested a more efficient hybrid architecture, which became part of the foundation for Qwen3.5.
Qwen3.5 made image and video understanding native to the main family. Qwen3.6 placed more emphasis on multimodal agents and software work. Qwen3.7 continued that direction with proprietary Max and Plus models for sustained agent execution. The latest general models now handle some work once reserved for Coder and VL, although the specialist names still identify models built for those tasks.
Qwen Coder Models
CodeQwen1.5 established the separate coding branch in April 2024. Qwen2.5-Coder replaced the CodeQwen name later that year and expanded the family across six sizes. These models targeted code completion, generation, debugging, repair, and many programming languages.
Qwen3-Coder moved from code output toward agentic software work. Its training and long context supported repository-scale tasks, tool calls, browser use, and repeated interaction with an execution environment. Qwen Code supplied the terminal interface, while Qwen3-Coder supplied the model intelligence behind the original release.
The general Qwen3.6 and Qwen3.7 models also emphasize agentic coding. Qwen3-Coder remains the specialist coding line, while repository work and software agents have become core capabilities in the flagship models.
Qwen VL and Qwen Omni Models
Qwen VL means vision-language. These models accept images or video alongside text and produce text. The branch progressed from image description, text reading, and grounding in Qwen-VL to dynamic image resolution and video understanding in Qwen2-VL. Qwen2.5-VL strengthened document extraction, visual localization, long-video analysis, and computer use. Qwen3-VL added separate Instruct and Thinking behavior for visual tasks.
Qwen Omni covers more modalities and more output types. Qwen2.5-Omni and Qwen3-Omni can process text, images, audio, and video. They can also generate spoken responses instead of returning only text. Omni supports live voice and video conversations. VL remains the clearer label for image, document, and video understanding without full speech output.
Qwen-Image belongs to neither group. It creates and edits images. A VL model explains what appears in an image; an image generation model produces a new image. Qwen VLo briefly joined both roles in a hosted preview before Qwen-Image established a separate open-weight generation line.
Qwen Reasoning Models
QwQ was the first dedicated Qwen reasoning family. QwQ-32B-Preview demonstrated longer internal problem solving in November 2024. The March 2025 QwQ-32B release used reinforcement learning to improve mathematics, coding, tool use, and general reasoning.
QVQ applied extended reasoning to visual evidence. QVQ-Max could study an image or video and reason about diagrams, visual mathematics, code screenshots, and real-world scenes. It was a hosted visual reasoning model rather than a general text-only replacement for QwQ.
Qwen3 absorbed reasoning into the main family through thinking modes and dedicated Thinking variants. QwQ and QVQ remain important historical branches because they show how text and visual reasoning developed, but users no longer need a model with QwQ in its name to access deliberate reasoning in Qwen.
Specialized Qwen Models
Qwen-Math models focus on mathematical problem solving and methods that combine written reasoning with programs or tools. Qwen-Embedding converts content into vectors for semantic search, while Qwen-Reranker scores the relevance of retrieved results. The later VL versions extend those retrieval jobs to images and video.
Qwen-Audio and Qwen2-Audio understand speech, music, and other sound. Qwen3-ASR is a more focused speech-to-text family, while Qwen3-TTS generates speech from text. Qwen3Guard classifies potentially unsafe content. These models solve narrower tasks and should not be treated as successive generations of the main conversational model.
Major Qwen Products
Qwen Studio and Qwen Chat
Qwen’s consumer-facing chat service lets people use hosted models without downloading weights or creating an API integration. It has carried the Qwen Chat name and is now presented within Qwen Studio across web, mobile, and desktop platforms. Available models and features can change independently from open-weight releases.
QVQ-Max, Qwen VLo, and some Max models appeared in Qwen Studio without a matching checkpoint for local use. Availability in Qwen Studio confirms access to a hosted model, not the release of downloadable weights.
Qwen-Agent
Qwen-Agent is an open-source framework for building applications around Qwen models. It provides patterns for function calling, planning, memory, retrieval-augmented generation, code execution, browser assistance, and MCP tools. It is also a backend for parts of Qwen’s hosted chat experience.
Qwen Code
Qwen Code is an open-source command-line coding agent introduced with Qwen3-Coder in July 2025. It can inspect a project, read and edit files, run shell commands, use tools, and work through multi-step development tasks. The tool and model are separate: Qwen Code is the client application, while Qwen3-Coder and later compatible models provide the underlying generation and reasoning. See our Qwen Code CLI guide for installation and everyday use.
Alibaba Cloud Model Studio
Model Studio is Alibaba Cloud’s platform for accessing Qwen and other models through APIs. It supports OpenAI-compatible interfaces, multimodal inputs, application development, evaluation, tuning, and deployment services. Hosted names such as Qwen-Plus, Qwen-Max, and dated API snapshots may not correspond to a downloadable checkpoint with the same specifications.
How Qwen Changed Over Time
From Hosted Model to Open-Weight Family
Tongyi Qianwen began as a hosted Alibaba Cloud model in April 2023. Researchers and developers could download Qwen-7B and Qwen-7B-Chat weights four months later. Qwen-VL, Qwen-14B, Qwen-Agent, Qwen-72B, and Qwen-1.8B then established a family rather than a single chatbot.
Qwen2.5 Brought the Specialist Lines Together
Qwen2 strengthened the shared language foundation, while Qwen2.5 coordinated general, Coder, and Math releases. The combined range offered a clearer choice of model sizes and specialties. Developers could select a model based on task and hardware instead of treating each Qwen release as an isolated experiment.
Qwen VL Moved Beyond Image Recognition
The first Qwen-VL recognized and located content in images. Qwen2-VL added stronger video and resolution handling, while Qwen2.5-VL parsed documents and operated as a visual agent. QVQ and Qwen3-VL added longer visual reasoning. By Qwen3.7-Plus, visual perception had become part of the hosted general agent line.
Reasoning Moved into the Main Model Line
QwQ began as a separate experiment because extended reasoning required different training and response behavior. QwQ-32B followed as a downloadable model for mathematics, coding, and tools. QVQ extended the approach to visual evidence. Qwen3 then combined thinking and direct answers within the primary generation. Reasoning became a mode of Qwen rather than only a specialist model name.
Qwen Code Connected the Models to Software Work
Earlier Qwen Coder models generated and repaired code. Qwen3-Coder was trained for longer interaction with repositories, browsers, tools, and execution feedback. Qwen Code placed those capabilities in a terminal agent. Qwen3.6 and Qwen3.7 later carried the same emphasis on planning and action into the general flagship models.
Qwen Timeline FAQs
When was Qwen first released?
Alibaba Cloud publicly unveiled Tongyi Qianwen on April 11, 2023. The first downloadable Qwen models, Qwen-7B and Qwen-7B-Chat, followed on August 3, 2023.
What does Qwen mean?
Qwen is a shortened form of Qianwen in the Chinese name Tongyi Qianwen. Qwen’s original technical report describes Qianwen as meaning “thousands of prompts.” The name now covers Alibaba’s language, multimodal, coding, reasoning, media, retrieval, and agent model families.
What was the first open Qwen model?
Qwen-7B and Qwen-7B-Chat were the first public open-weight Qwen language models. Alibaba released them through ModelScope and Hugging Face on August 3, 2023.
What is the latest Qwen model?
Qwen3.7 is the latest general generation. Qwen3.7-Max was introduced on May 20, 2026, and Qwen3.7-Plus followed on June 1. A Qwen3.7-Max API snapshot released on June 10 added visual understanding. These Qwen3.7 models are hosted and proprietary. Qwen3.6-27B, released on April 22, 2026, is the latest open-weight general model.
What is the difference between Qwen, Qwen Coder, and Qwen VL?
Qwen is the general foundation model line. Qwen Coder models receive additional code-focused training for programming and software agents. Qwen VL models process images, documents, and video alongside text. Recent general models overlap with both specialist branches, but the names still identify their primary training focus.
Is Qwen a reasoning model?
Some Qwen models are designed specifically for reasoning, including QwQ and QVQ. Qwen3 and later general generations also provide thinking modes or Thinking variants, so reasoning is now part of the main Qwen line as well.
What is the difference between QwQ and Qwen3?
QwQ is a dedicated text reasoning family based on the Qwen2.5 era. Qwen3 is a later general-purpose generation that combines reasoning, direct responses, multilingual language work, coding, and agent capabilities. QwQ established the approach; Qwen3 brought it into the main family.
Is Qwen open source?
Many Qwen models have downloadable weights and open-source code, but the exact license depends on the model. Most Qwen2 and Qwen3 open models use Apache 2.0, while some earlier Qwen and Qwen2.5 sizes used Qwen-specific licenses. Hosted Max and Plus models may be proprietary and available only through Qwen products or APIs. Qwen therefore includes both open-weight and proprietary models.
What are Qwen Studio, Qwen Code, and Qwen-Agent?
Qwen Studio is the user-facing service for chatting with hosted Qwen models. Qwen Code is a terminal coding agent that works with files, commands, and code repositories. Qwen-Agent is a development framework for building tool-using applications with Qwen models.
Who owns and develops Qwen?
Qwen is developed by Alibaba’s Qwen team. The project began under Alibaba Cloud, and its hosted models and APIs remain closely connected to Alibaba Cloud services.
Where can Qwen models be accessed?
Hosted models are available through Qwen Studio and Alibaba Cloud Model Studio. Open-weight releases are commonly published through Hugging Face and ModelScope, with source code and usage instructions in the QwenLM organization on GitHub.
Official Qwen resources: Qwen and Qwen Studio for hosted access; Alibaba Cloud Model Studio for APIs; QwenLM on GitHub, Hugging Face, and ModelScope for code and downloadable models.
Why do some Qwen release dates differ?
A Qwen model may have separate dates for its announcement, model weights, API endpoint, technical report, and repository update. Qwen3, for example, was announced on April 28, 2025, while its public repository records April 29. This is why two sources may show different dates for the same generation.
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