AI Models

Qwen: Qwen2.5 VL 72B Instruct

qwen/qwen2.5-vl-72b-instruct

Vision

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.

Input

13 208/M so'm

$1.04

Output

16 510/M so'm

$1.30

data_array 131K context

Qwen: Qwen3 VL 235B A22B Instruct

qwen/qwen3-vl-235b-a22b-instruct

Vision

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...

Input

3 302/M so'm

$0.26

Output

14 529/M so'm

$1.14

data_array 262K context

Qwen: Qwen3 VL 30B A3B Instruct

qwen/qwen3-vl-30b-a3b-instruct

Vision

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...

Input

2 146/M so'm

$0.17

Output

8 585/M so'm

$0.68

data_array 262K context

Qwen: Qwen3.5 397B A17B

qwen/qwen3.5-397b-a17b

Vision

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...

Input

6 356/M so'm

$0.50

Output

40 450/M so'm

$3.19

data_array 256K context

Qwen: Qwen3.5 Plus 2026-02-15

qwen/qwen3.5-plus-02-15

Vision

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...

Input

4 293/M so'm

$0.34

Output

25 756/M so'm

$2.03

data_array 1,000K context

Qwen: Qwen3.5 Plus 2026-04-20

qwen/qwen3.5-plus-20260420

Vision

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...

Input

4 953/M so'm

$0.39

Output

29 718/M so'm

$2.34

data_array 1,000K context

Qwen: Qwen3.5-122B-A10B

qwen/qwen3.5-122b-a10b

Vision

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...

Input

4 293/M so'm

$0.34

Output

34 341/M so'm

$2.70

data_array 262K context

Qwen: Qwen3.5-27B

qwen/qwen3.5-27b

Vision

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...

Input

3 219/M so'm

$0.25

Output

25 756/M so'm

$2.03

data_array 262K context

Qwen: Qwen3.5-35B-A3B

qwen/qwen3.5-35b-a3b

Vision

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...

Input

2 311/M so'm

$0.18

Output

16 510/M so'm

$1.30

data_array 262K context

Qwen: Qwen3.5-Flash

qwen/qwen3.5-flash-02-23

Vision

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...

Input

1 073/M so'm

$0.08

Output

4 293/M so'm

$0.34

data_array 1,000K context

Qwen: Qwen3.6 27B

qwen/qwen3.6-27b

Vision

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...

Input

4 763/M so'm

$0.38

Output

52 337/M so'm

$4.12

data_array 262K context

Qwen: Qwen3.6 35B A3B

qwen/qwen3.6-35b-a3b

Vision

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...

Input

2 311/M so'm

$0.18

Output

16 510/M so'm

$1.30

data_array 262K context

Qwen: Qwen3.6 Flash

qwen/qwen3.6-flash

Vision

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...

Input

3 096/M so'm

$0.24

Output

18 574/M so'm

$1.46

data_array 1,000K context

Qwen: Qwen3.6 Plus

qwen/qwen3.6-plus

Vision

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...

Input

5 366/M so'm

$0.42

Output

32 195/M so'm

$2.54

data_array 1,000K context

Qwen: Qwen3.7 Plus

qwen/qwen3.7-plus

Vision

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...

Input

5 283/M so'm

$0.42

Output

21 133/M so'm

$1.66

data_array 1,000K context