11 models
Ranked by Coding Index
71.8

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/qwen3.8-max-0902 1M context $2/M input $6/M output
68.9

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...

qwen/qwen3.8-max 1M context $2/M input $6/M output
68.1

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...

qwen/qwen3.8-27b 1M context $0.42/M input $3/M output
54.5

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...

qwen/qwen3.6-plus 1M context $0.325/M input $1.95/M output
53.7

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...

qwen/qwen3.6-27b 262.144K context $0.3/M input $2/M output
48.2

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...

qwen/qwen3.5-397b-a17b 262.144K context $0.55/M input $3.5/M output
45.7

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...

qwen/qwen3.5-122b-a10b 262.144K context $0.26/M input $2.08/M output
41.9

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...

qwen/qwen3.6-35b-a3b 262.144K context $0.1/M input $0.9/M output
37.0

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...

qwen/qwen3.5-35b-a3b 256K context $0.312/M input $1.25/M output
28.7

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...

qwen/qwen3.5-9b:batch 262.144K context $0.17/M input $0.25/M output
28.7

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...

qwen/qwen3.5-9b 262.144K context $0.1/M input $0.15/M output