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Key Breakthrough in Computing Power Enhancement: Peking University and DeepSeek Jointly Open-Source Large Model Inference Framework DSpark

Peking University and DeepSeek jointly open-source the DSpark large model inference acceleration framework, providing a breakthrough solution to high concurrency latency and computing power waste caused by the need for full computing power for each token during autoregressive generation.

13.6k 3 hours ago
Key Breakthrough in Computing Power Enhancement: Peking University and DeepSeek Jointly Open-Source Large Model Inference Framework DSpark

Models

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Spark X1

Iflytek

Spark X1

$2

Input tokens/M

-

Output tokens/M

-

Context Length

Spark Medical Large Model - Lite

Iflytek

Spark Medical Large Model - Lite

$2

Input tokens/M

-

Output tokens/M

8

Context Length

Spark Tiny

Iflytek

Spark Tiny

$2

Input tokens/M

-

Output tokens/M

8

Context Length

Spark Max

Iflytek

Spark Max

$8

Input tokens/M

-

Output tokens/M

8

Context Length

Spark Mini Instruct

Iflytek

Spark Mini Instruct

$2

Input tokens/M

-

Output tokens/M

8

Context Length

Spark Lite Patch

Iflytek

Spark Lite Patch

$2

Input tokens/M

-

Output tokens/M

8

Context Length

Spark Mini

Iflytek

Spark Mini

$2

Input tokens/M

-

Output tokens/M

8

Context Length

kimi-latest-32k

Moonshot

kimi-latest-32k

$5

Input tokens/M

$20

Output tokens/M

32

Context Length

kimi-latest-8k

Moonshot

kimi-latest-8k

$2

Input tokens/M

$10

Output tokens/M

8

Context Length

kimi-thinking-preview

Moonshot

kimi-thinking-preview

$200

Input tokens/M

$200

Output tokens/M

131

Context Length

kimi-k2-0711-preview

Moonshot

kimi-k2-0711-preview

$1

Input tokens/M

$16

Output tokens/M

131

Context Length

moonshot-v1-8k

Moonshot

moonshot-v1-8k

$2

Input tokens/M

$10

Output tokens/M

8

Context Length

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