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 vision-language model for visual reasoning, documents, and agent tasks
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
Qwen vision-language model for visual reasoning, documents, and agent tasks
Qwen omni model for text, vision, audio, and multimodal agent tasks
Qwen vision-language model for visual reasoning, documents, and agent tasks
Qwen vision-language model for visual reasoning, documents, and agent tasks
The Qwen3.5 series 397B-A17B native vision-language model is built on a hybrid architecture that integrates a linear attention mechanism with a sparse mixture-of-experts model, achieving higher inference efficiency. It delivers...
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...
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 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,...
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...
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...
No provider description is available for this model yet.
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...
Qwen3.6 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...
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-VL-235B-A22B Instruct is an open-weight multimodal model that unifies strong text generation with visual understanding across images and video. The Instruct model targets general vision-language use (VQA, document parsing, chart/table...
Qwen3.8 Flash is a multimodal reasoning model from Alibaba. It is suited for coding assistance, agentic workflows, visual understanding, document and codebase analysis, desktop interaction, chart analysis, and long-video analysis.
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....
Qwen3-VL-32B-Instruct is a large-scale multimodal vision-language model designed for high-precision understanding and reasoning across text, images, and video. With 32 billion parameters, it combines deep visual perception with advanced text...
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...
Qwen3.7 Flash is a vision-language reasoning model from Alibaba. It is suited for multimodal agents, visual coding, search, and computer interaction, with strengths in object recognition, spatial understanding, and real-world...
Qwen3-VL-8B-Instruct is a multimodal vision-language model from the Qwen3-VL series, built for high-fidelity understanding and reasoning across text, images, and video. It features improved multimodal fusion with Interleaved-MRoPE for long-horizon...
Qwen3.6 27B is a dense 27-billion-parameter language model from the Qwen Team at Alibaba, released in April 2026. It features hybrid multimodal capabilities — accepting text, image, and video inputs...
Qwen3.6-35B-A3B is an open-weight multimodal model from Alibaba Cloud with 35 billion total parameters and 3 billion active parameters per token. It uses a hybrid sparse mixture-of-experts architecture combining Gated...
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...
The Qwen3.5 27B native vision-language Dense model incorporates a linear attention mechanism, delivering fast response times while balancing inference speed and performance. Its overall capabilities are comparable to those of...
The Qwen3.5 122B-A10B native vision-language model is built on a hybrid architecture that integrates a linear attention mechanism with a sparse mixture-of-experts model, achieving higher inference efficiency. In terms of...
The Qwen3.5 Series 35B-A3B is a native vision-language model designed with a hybrid architecture that integrates linear attention mechanisms and a sparse mixture-of-experts model, achieving higher inference efficiency. Its overall...
The Qwen3.5 native vision-language series Plus models are built on a hybrid architecture that integrates linear attention mechanisms with sparse mixture-of-experts models, achieving higher inference efficiency. In a variety of...
Qwen3-VL-30B-A3B-Instruct is a multimodal model that unifies strong text generation with visual understanding for images and videos. Its Instruct variant optimizes instruction-following for general multimodal tasks. It excels in perception...
Qwen3-VL-30B-A3B-Thinking is a multimodal model that unifies strong text generation with visual understanding for images and videos. Its Thinking variant enhances reasoning in STEM, math, and complex tasks. It excels...
Qwen3.5 Plus (April 2026) is a large-scale multimodal language model from Alibaba. It accepts text, image, and video input and produces text output, with a 1M token context window. This...
The Qwen3.5 native vision-language Flash models are built on a hybrid architecture that integrates a linear attention mechanism with a sparse mixture-of-experts model, achieving higher inference efficiency. Compared to the...
| 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 | |||
| Qwen3.6 Flashalibaba/qwen3.6-flash | 1M | $0.188 | $1.125 | 2026-04-27 | |||
| 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-VL Plusalibaba/qwen3-vl-plus | 262.144K | $0.2 | $1.6 | 2025-09-23 | |||
| Qwen-Omni Turboalibaba/qwen-omni-turbo | 32.768K | $0.07 | $0.27 | 2025-01-19 | |||
| Qwen-VL Maxalibaba/qwen-vl-max | 131.072K | $0.8 | $3.2 | 2024-04-08 | |||
| Qwen-VL Plusalibaba/qwen-vl-plus | 131.072K | $0.21 | $0.63 | 2024-01-25 | |||
| Qwen: Qwen3.5 397B A17Bqwen/qwen3.5-397b-a17b | 262.144K | $0.55 | $3.5 | — | |||
| Qwen: Qwen3 VL 8B Thinkingqwen/qwen3-vl-8b-thinking | 131.072K | $0.18 | $2.1 | — | |||
| Qwen: Qwen3.6 Plusqwen/qwen3.6-plus | 1M | $0.325 | $1.95 | — | |||
| Qwen: Qwen3.8 Max (0902)qwen/qwen3.8-max-0902 | 1M | $2 | $6 | — | |||
| Qwen: Qwen3.7 Plusqwen/qwen3.7-plus | 1M | $0.32 | $1.28 | — | |||
| Qwen: Qwen3.5-9B (batch)qwen/qwen3.5-9b:batch | 262.144K | $0.17 | $0.25 | — | |||
| Qwen/Qwen3.8-Flash-NextQwen/Qwen3.8-Flash-Next | Not documented | — | — | — | |||
| Qwen: Qwen3.8 Max (0803)qwen/qwen3.8-max | 1M | $2 | $6 | — | |||
| Qwen: Qwen3.6 Flashqwen/qwen3.6-flash | 1M | $0.188 | $1.125 | — | |||
| Qwen: Qwen2.5 VL 72B Instructqwen/qwen2.5-vl-72b-instruct | 128K | $0.8 | $1 | — | |||
| Qwen: Qwen3 VL 235B A22B Instructqwen/qwen3-vl-235b-a22b-instruct | 131.072K | $0.21 | $1.9 | — | |||
| Qwen: Qwen3.8 Flashqwen/qwen3.8-flash | 1M | $0.15 | $0.47 | — | |||
| Qwen: Qwen3 VL 235B A22B Thinkingqwen/qwen3-vl-235b-a22b-thinking | 131.072K | $0.4 | $4 | — | |||
| Qwen: Qwen3 VL 32B Instructqwen/qwen3-vl-32b-instruct | 131.072K | $0.104 | $0.416 | — | |||
| Qwen: Qwen3.8 27Bqwen/qwen3.8-27b | 1M | $0.42 | $3 | — | |||
| Qwen: Qwen3.7 Flashqwen/qwen3.7-flash | 1M | $0.03 | $0.13 | — | |||
| Qwen: Qwen3 VL 8B Instructqwen/qwen3-vl-8b-instruct | 131.072K | $0.117 | $0.455 | — | |||
| Qwen: Qwen3.6 27Bqwen/qwen3.6-27b | 262.144K | $0.3 | $2 | — | |||
| Qwen: Qwen3.6 35B A3Bqwen/qwen3.6-35b-a3b | 262.144K | $0.1 | $0.9 | — | |||
| Qwen: Qwen3.5-9Bqwen/qwen3.5-9b | 262.144K | $0.1 | $0.15 | — | |||
| Qwen: Qwen3.5-27Bqwen/qwen3.5-27b | 262.144K | $0.195 | $1.56 | — | |||
| Qwen: Qwen3.5-122B-A10Bqwen/qwen3.5-122b-a10b | 262.144K | $0.26 | $2.08 | — | |||
| Qwen: Qwen3.5-35B-A3Bqwen/qwen3.5-35b-a3b | 256K | $0.312 | $1.25 | — | |||
| Qwen: Qwen3.5 Plus 2026-02-15qwen/qwen3.5-plus-02-15 | 1M | $0.26 | $1.56 | — | |||
| Qwen: Qwen3 VL 30B A3B Instructqwen/qwen3-vl-30b-a3b-instruct | 262.144K | $0.15 | $0.6 | — | |||
| Qwen: Qwen3 VL 30B A3B Thinkingqwen/qwen3-vl-30b-a3b-thinking | 131.072K | $0.2 | $2.4 | — | |||
| Qwen: Qwen3.5 Plus 2026-04-20qwen/qwen3.5-plus-20260420 | 1M | $0.3 | $1.8 | — | |||
| Qwen: Qwen3.5-Flashqwen/qwen3.5-flash-02-23 | 1M | $0.065 | $0.26 | — |