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Models

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GPT-5 Codex

Openai

GPT-5 Codex

-

Input tokens/M

-

Output tokens/M

-

Context Length

Kimi-K2

Moonshot

Kimi-K2

$4

Input tokens/M

$16

Output tokens/M

256

Context Length

Doubao-Seed-1.6

Bytedance

Doubao-Seed-1.6

$0.8

Input tokens/M

$2

Output tokens/M

256

Context Length

qwen-deep-research

Alibaba

qwen-deep-research

$54

Input tokens/M

$163

Output tokens/M

1k

Context Length

Doubao-Seed-1.6-vision

Bytedance

Doubao-Seed-1.6-vision

$0.8

Input tokens/M

$8

Output tokens/M

256

Context Length

Hunyuan-T1-20250822

Tencent

Hunyuan-T1-20250822

$1

Input tokens/M

$4

Output tokens/M

32

Context Length

Hunyuan-T1-latest

Tencent

Hunyuan-T1-latest

$1

Input tokens/M

$4

Output tokens/M

32

Context Length

DeepSeek-V3.1

Deepseek

DeepSeek-V3.1

$4

Input tokens/M

$12

Output tokens/M

128

Context Length

gpt-oss-20b

Openai

gpt-oss-20b

$0.4

Input tokens/M

-

Output tokens/M

128

Context Length

Doubao-Seed-1.6-thinking

Bytedance

Doubao-Seed-1.6-thinking

$0.8

Input tokens/M

$8

Output tokens/M

256

Context Length

GLM-4.5

Chatglm

GLM-4.5

$2

Input tokens/M

$8

Output tokens/M

128

Context Length

GLM-4.5-X

Chatglm

GLM-4.5-X

$8

Input tokens/M

$16

Output tokens/M

128

Context Length

DeepSeek-R1

Deepseek

DeepSeek-R1

$4

Input tokens/M

$16

Output tokens/M

32

Context Length

Spark X1

Iflytek

Spark X1

$2

Input tokens/M

-

Output tokens/M

-

Context Length

Doubao-1.5-thinking-pro

Bytedance

Doubao-1.5-thinking-pro

$4

Input tokens/M

$16

Output tokens/M

128

Context Length

Doubao-1.5-UI-TARS

Bytedance

Doubao-1.5-UI-TARS

$3.5

Input tokens/M

$12

Output tokens/M

128

Context Length

DeepSeek-V3

Deepseek

DeepSeek-V3

$2

Input tokens/M

$8

Output tokens/M

32

Context Length

ERNIE X1 Turbo

Baidu

ERNIE X1 Turbo

$1

Input tokens/M

$4

Output tokens/M

64

Context Length

Doubao-1.5-thinking-vision-pro

Bytedance

Doubao-1.5-thinking-vision-pro

$3

Input tokens/M

$9

Output tokens/M

128

Context Length

qwen-plus

Alibaba

qwen-plus

$0.8

Input tokens/M

$0.2

Output tokens/M

128

Context Length

AASIST3

MTUCI

A

AASIST3 is an enhanced version based on the AASIST architecture, specifically designed for voice deep forgery detection. This model integrates Kolmogorov - Arnold Networks (KAN), combines self - supervised learning features and additional regularization techniques, which can effectively improve the performance and robustness of voice deep forgery detection.

Audio ProcessingSafetensorsSafetensorsEnglish
MTUCI
821
1

Llava 7b 1.5 Rfrd

sparklexfantasy

L

This is a multi-modal forgery representation learning model focused on image-text to text processing, used to detect video content generated by diffusion models, and identify deepfake content through multi-modal feature learning.

MultimodalTransformersTransformers
sparklexfantasy
115
1

CoDE

aimagelab

C

A Vision Transformer model for detecting deepfake images, achieving high-precision forgery detection through contrastive learning and global-local similarity analysis.

Computer VisionTransformersTransformers
aimagelab
515
2
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