2026-09-02 upgraded snapshot of Qwen3.8 Max with stronger coding, collaborative agents, and multimodal document understanding
Models
Every model in the catalog with source-linked pricing, context limits, provider availability, and published benchmark results.
Qwen vision-language model for visual reasoning, documents, and agent tasks
2.4-trillion-parameter MoE flagship for coding, professional work, multimodal understanding, and long-horizon agentic workflows
Preview Qwen flagship for million-token multimodal reasoning and long-horizon agentic workflows
Lightweight multimodal Qwen model for high-throughput text, image, and video tasks
Multimodal Qwen workhorse for long-context agents, visual inputs, and coding
Qwen frontier model tuned for agent frameworks, coding assistants, and long tasks
Qwen vision-language model for visual reasoning, documents, and agent tasks
Flagship Qwen model for complex reasoning, coding, and agentic workflows
Earlier Qwen multimodal workhorse for million-token agent and document tasks
Qwen vision-language model for visual reasoning, documents, and agent tasks
Qwen vision-language model for visual reasoning, documents, and agent tasks
Flagship Qwen3 model for coding agents, complex reasoning, and tool use
Qwen vision-language model for visual reasoning, documents, and agent tasks
Efficient Qwen model for fast chat, extraction, and high-volume workloads
Qwen coding model for software agents, repository edits, and code reasoning
Hosted Qwen coder for software agents, repo edits, and long-context code
Qwen reasoning model for deliberate problem solving, math, and coding
Qwen omni model for text, vision, audio, and multimodal agent tasks
Efficient Qwen model for fast chat, extraction, and high-volume workloads
Qwen vision-language model for visual reasoning, documents, and agent tasks
Flagship Qwen model for complex reasoning, coding, and agentic workflows
Qwen instruction model for multilingual chat, reasoning, and tool use
Qwen vision-language model for visual reasoning, documents, and agent tasks
Qwen3-VL-8B-Thinking is the reasoning-optimized variant of the Qwen3-VL-8B multimodal model, designed for advanced visual and textual reasoning across complex scenes, documents, and temporal sequences. It integrates enhanced multimodal alignment and...
Qwen3-235B-A22B-Thinking-2507 is a high-performance, open-weight Mixture-of-Experts (MoE) language model optimized for complex reasoning tasks. It activates 22B of its 235B parameters per forward pass and natively supports up to 262,144...
Qwen3-Coder-30B-A3B-Instruct is a 30.5B parameter Mixture-of-Experts (MoE) model with 128 experts (8 active per forward pass), designed for advanced code generation, repository-scale understanding, and agentic tool use. Built on the...
Qwen3-235B-A22B-Instruct-2507 is a multilingual, instruction-tuned mixture-of-experts language model based on the Qwen3-235B architecture, with 22B active parameters per forward pass. It is optimized for general-purpose text generation, including instruction following,...
Qwen3, the latest generation in the Qwen large language model series, features both dense and mixture-of-experts (MoE) architectures to excel in reasoning, multilingual support, and advanced agent tasks. Its unique...
Qwen3-8B is a dense 8.2B parameter causal language model from the Qwen3 series, designed for both reasoning-heavy tasks and efficient dialogue. It supports seamless switching between "thinking" mode for math,...
Qwen3-32B is a dense 32.8B parameter causal language model from the Qwen3 series, optimized for both complex reasoning and efficient dialogue. It supports seamless switching between a "thinking" mode for...
Qwen2.5-Coder is the latest series of Code-Specific Qwen large language models (formerly known as CodeQwen). Qwen2.5-Coder brings the following improvements upon CodeQwen1.5: - Significantly improvements in **code generation**, **code reasoning**...
Qwen2.5 7B is the latest series of Qwen large language models. Qwen2.5 brings the following improvements upon Qwen2: - Significantly more knowledge and has greatly improved capabilities in coding and...
Qwen3-VL-235B-A22B Thinking is a multimodal model that unifies strong text generation with visual understanding across images and video. The Thinking model is optimized for multimodal reasoning in STEM and math....
Qwen2.5-VL is proficient in recognizing common objects such as flowers, birds, fish, and insects. It is also highly capable of analyzing texts, charts, icons, graphics, and layouts within images.
Qwen3-Next-80B-A3B-Instruct is an instruction-tuned chat model in the Qwen3-Next series optimized for fast, stable responses without “thinking” traces. It targets complex tasks across reasoning, code generation, knowledge QA, and multilingual...
Qwen3.8 Max 0902 is an updated snapshot of Qwen3.8 Max from Alibaba's Qwen team. It is a 2.4-trillion-parameter mixture-of-experts model that accepts text, image, and video input and returns text,...
Qwen Plus 0728, based on the Qwen3 foundation model, is a 1 million context hybrid reasoning model with a balanced performance, speed, and cost combination.
Qwen3.5-9B is a multimodal foundation model from the Qwen3.5 family, designed to deliver strong reasoning, coding, and visual understanding in an efficient 9B-parameter architecture. It uses a unified vision-language design...
Qwen3-Coder-480B-A35B-Instruct is a Mixture-of-Experts (MoE) code generation model developed by the Qwen team. It is optimized for agentic coding tasks such as function calling, tool use, and long-context reasoning over...
Qwen3 Coder Plus is Alibaba's proprietary version of the Open Source Qwen3 Coder 480B A35B. It is a powerful coding agent model specializing in autonomous programming via tool calling and...
Qwen3.8 2.4T A95B is an open-weight sparse mixture-of-experts model from Qwen and the open-weight variant of [Qwen3.8 Max](/qwen/qwen3.8-max), with 95 billion active parameters out of 2.4 trillion total. It is...
Qwen3.6 Flash is a fast, efficient language model from Alibaba's Qwen 3.6 series. It supports text, image, and video input with a 1M token context window. Tiered pricing kicks in...
Qwen3.8 Max (0803) is the August 3, 2026 checkpoint of Qwen3.8 Max, the flagship model in Alibaba's Qwen3.8 series and the general-availability successor to the Qwen3.8 Max Preview. It is...
Qwen3.7-Plus is a cost-effective model in Alibaba's Qwen3.7 series. It supports text and image input with text output, building on the series' text capabilities with a comprehensive upgrade to its...
Qwen 3.6 Plus builds on a hybrid architecture that combines efficient linear attention with sparse mixture-of-experts routing, enabling strong scalability and high-performance inference. Compared to the 3.5 series, it delivers...
Qwen3.8 27B is an open-weight dense vision-language model from Qwen. It is suited for coding, professional workflows, research, multimodal interaction, and long-running agent tasks, with flexible thinking that can be...
Qwen3-14B is a dense 14.8B parameter causal language model from the Qwen3 series, designed for both complex reasoning and efficient dialogue. It supports seamless switching between a "thinking" mode for...
Qwen3-Coder-480B-A35B-Instruct is a Mixture-of-Experts (MoE) code generation model developed by the Qwen team. It is optimized for agentic coding tasks such as function calling, tool use, and long-context reasoning over...
Qwen3-235B-A22B is a 235B parameter mixture-of-experts (MoE) model developed by Qwen, activating 22B parameters per forward pass. It supports seamless switching between a "thinking" mode for complex reasoning, math, and...
| Model | Creator | Inputs | Context | Input | Output | Released | Compare |
|---|---|---|---|---|---|---|---|
| Qwen3.8 Max 0902alibaba/qwen3.8-max-0902 | 1M | $1.71 | $5.14 | 2026-09-02 | |||
| Qwen3.8 Flashalibaba/qwen3.8-flash | 1M | $0.15 | $0.47 | 2026-08-26 | |||
| Qwen3.8 Maxalibaba/qwen3.8-max | 1M | $2 | $6 | 2026-08-03 | |||
| Qwen3.8 Max Previewalibaba/qwen3.8-max-preview | 1M | $2 | $6 | 2026-07-19 | |||
| Qwen3.7 Flashalibaba/qwen3.7-flash | 1M | $0.028 | $0.113 | 2026-07-15 | |||
| Qwen3.7 Plusalibaba/qwen3.7-plus | 1M | $0.5 | $3 | 2026-06-02 | |||
| Qwen3.7 Maxalibaba/qwen3.7-max | 1M | $2.5 | $7.5 | 2026-05-21 | |||
| Qwen3.6 Flashalibaba/qwen3.6-flash | 1M | $0.188 | $1.125 | 2026-04-27 | |||
| Qwen3.6 Max Previewalibaba/qwen3.6-max-preview | 262.144K | $1.3 | $7.8 | 2026-04-20 | |||
| Qwen3.6 Plusalibaba/qwen3.6-plus | 1M | $0.5 | $3 | 2026-04-02 | |||
| Qwen3.5 Flashalibaba/qwen3.5-flash | 1M | $0.029 | $0.287 | 2026-02-23 | |||
| Qwen3.5 Plusalibaba/qwen3.5-plus | 1M | $0.4 | $2.4 | 2026-02-16 | |||
| Qwen3 Maxalibaba/qwen3-max | 262.144K | $1.2 | $6 | 2025-09-23 | |||
| Qwen3-VL Plusalibaba/qwen3-vl-plus | 262.144K | $0.2 | $1.6 | 2025-09-23 | |||
| Qwen Flashalibaba/qwen-flash | 1M | $0.05 | $0.4 | 2025-07-28 | |||
| Qwen3 Coder Flashalibaba/qwen3-coder-flash | 1M | $0.3 | $1.5 | 2025-07-28 | |||
| Qwen3 Coder Plusalibaba/qwen3-coder-plus | 1.04858M | $1 | $5 | 2025-07-23 | |||
| QwQ Plusalibaba/qwq-plus | 131.072K | $0.8 | $2.4 | 2025-03-05 | |||
| Qwen-Omni Turboalibaba/qwen-omni-turbo | 32.768K | $0.07 | $0.27 | 2025-01-19 | |||
| Qwen Turboalibaba/qwen-turbo | 1M | $0.05 | $0.2 | 2024-11-01 | |||
| Qwen-VL Maxalibaba/qwen-vl-max | 131.072K | $0.8 | $3.2 | 2024-04-08 | |||
| Qwen Maxalibaba/qwen-max | 32.768K | $1.6 | $6.4 | 2024-04-03 | |||
| Qwen Plusalibaba/qwen-plus | 1M | $0.4 | $1.2 | 2024-01-25 | |||
| Qwen-VL Plusalibaba/qwen-vl-plus | 131.072K | $0.21 | $0.63 | 2024-01-25 | |||
| Qwen: Qwen3 VL 8B Thinkingqwen/qwen3-vl-8b-thinking | 131.072K | $0.18 | $2.1 | — | |||
| Qwen: Qwen3 235B A22B Thinking 2507qwen/qwen3-235b-a22b-thinking-2507 | 131.072K | $0.23 | $2.3 | — | |||
| Qwen: Qwen3 Coder 30B A3B Instructqwen/qwen3-coder-30b-a3b-instruct | 262.144K | $0.07 | $0.28 | — | |||
| Qwen: Qwen3 235B A22B Instruct 2507qwen/qwen3-235b-a22b-2507 | 262.144K | $0.22 | $0.88 | — | |||
| Qwen: Qwen3 30B A3Bqwen/qwen3-30b-a3b | 40.96K | $0.12 | $0.5 | — | |||
| Qwen: Qwen3 8Bqwen/qwen3-8b | 131.072K | $0.117 | $0.455 | — | |||
| Qwen: Qwen3 32Bqwen/qwen3-32b | 40.96K | $0.08 | $0.28 | — | |||
| Qwen2.5 Coder 32B Instructqwen/qwen-2.5-coder-32b-instruct | 32.768K | $0.66 | $1 | — | |||
| Qwen: Qwen2.5 7B Instructqwen/qwen-2.5-7b-instruct | 32.768K | $0.1 | $0.2 | — | |||
| Qwen: Qwen3 VL 235B A22B Thinkingqwen/qwen3-vl-235b-a22b-thinking | 131.072K | $0.4 | $4 | — | |||
| Qwen: Qwen2.5 VL 72B Instructqwen/qwen2.5-vl-72b-instruct | 128K | $0.8 | $1 | — | |||
| Qwen: Qwen3 Next 80B A3B Instruct (free)qwen/qwen3-next-80b-a3b-instruct:free | 262.144K | Free | Free | — | |||
| Qwen: Qwen3.8 Max (0902)qwen/qwen3.8-max-0902 | 1M | $2 | $6 | — | |||
| Qwen: Qwen Plus 0728 (thinking)qwen/qwen-plus-2025-07-28:thinking | 1M | $0.26 | $0.78 | — | |||
| Qwen: Qwen3.5-9B (batch)qwen/qwen3.5-9b:batch | 262.144K | $0.17 | $0.25 | — | |||
| Qwen: Qwen3 Coder 480B A35B (free)qwen/qwen3-coder:free | 262K | Free | Free | — | |||
| Qwen: Qwen3 Coder Plusqwen/qwen3-coder-plus | 1M | $0.65 | $3.25 | — | |||
| Qwen: Qwen3.8 2.4T A95B (batch)qwen/qwen3.8-2.4t-a95b:batch | 1.01M | $2 | $6 | — | |||
| Qwen: Qwen3.6 Flashqwen/qwen3.6-flash | 1M | $0.188 | $1.125 | — | |||
| Qwen: Qwen3.8 Max (0803)qwen/qwen3.8-max | 1M | $2 | $6 | — | |||
| Qwen: Qwen3.7 Plusqwen/qwen3.7-plus | 1M | $0.32 | $1.28 | — | |||
| Qwen: Qwen3.6 Plusqwen/qwen3.6-plus | 1M | $0.325 | $1.95 | — | |||
| Qwen: Qwen3.8 27Bqwen/qwen3.8-27b | 1M | $0.42 | $3 | — | |||
| Qwen: Qwen3 14Bqwen/qwen3-14b | 131.072K | $0.227 | $0.91 | — | |||
| Qwen: Qwen3 Coder 480B A35Bqwen/qwen3-coder | 262.144K | $0.3 | $1 | — | |||
| Qwen: Qwen3 235B A22Bqwen/qwen3-235b-a22b | 131.072K | $0.455 | $1.82 | — |