Deepseek V3

Deepseek V3

DeepSeek-V3 is a large language model developed by the Chinese company DeepSeek. It adopts the MoE architecture, with 37 billion active parameters and a total of 671 billion parameters. It focuses on mathematics, programming, and Chinese language tasks, and its performance is comparable to that of top models such as GPT-4o.

DeepSeek-V3 is a large language model developed by the Chinese company DeepSeek. It adopts the MoE architecture, with 37 billion active parameters and a total of 671 billion parameters. It focuses on mathematics, programming, and Chinese language tasks, and its performance is comparable to that of top models such as GPT-4o.

Intelligence(Relatively Strong)

Speed(Relatively Slow)

Input Supported Modalities

No

Is Reasoning Model

128,000

Context Window

8,000

Maximum Output Tokens

-

Knowledge Cutoff

Pricing

￥1.94 /M tokens

Input

￥7.92 /M tokens

Output

￥4.93 /M tokens

Blended Price

Quick Simple Comparison

DeepSeek-V3

￥0.27

Basic Parameters

GPT-4.1 Technical Parameters

Parameter Count

Not Announced

Context Length

128.00k tokens

Training Data Cutoff

Open Source Category

Open Source

Multimodal Support

Text Only

Throughput

14.80k

Release Date

2024-12-26

Response Speed

87.5 tokens/s

Benchmark Scores

Below is the performance of claude-monet in various standard benchmark tests. These tests evaluate the model's capabilities in different tasks and domains.

Intelligence Index

Large Language Model Intelligence Level

8000

Large Language Model Intelligence Level

Coding Index

Indicator of AI model performance on coding tasks

8260

Indicator of AI model performance on coding tasks

Math Index

Capability indicator in solving mathematical problems, mathematical reasoning, or performing math-related tasks

-

Capability indicator in solving mathematical problems, mathematical reasoning, or performing math-related tasks

MMLU Pro

Massive Multitask Multimodal Understanding - Testing understanding of text, images, audio, and video

81.2

Massive Multitask Multimodal Understanding - Testing understanding of text, images, audio, and video

GPQA

Graduate Physics Questions Assessment - Testing advanced physics knowledge with diamond science-level questions

68.4

Graduate Physics Questions Assessment - Testing advanced physics knowledge with diamond science-level questions

HLE

The model's comprehensive average score on the Hugging Face Open LLM Leaderboard

-

The model's comprehensive average score on the Hugging Face Open LLM Leaderboard

LiveCodeBench

Specific evaluation focused on assessing large language models' ability in real-world code writing and solving programming competition problems

49.2

Specific evaluation focused on assessing large language models' ability in real-world code writing and solving programming competition problems

SciCode

The model's capability in code generation for scientific computing or specific scientific domains

-

The model's capability in code generation for scientific computing or specific scientific domains

HumanEval

Score achieved by the AI model on the specific HumanEval benchmark test set

82.6

Score achieved by the AI model on the specific HumanEval benchmark test set

Math 500 Score

Score on the first 500 larger, more well-known mathematical benchmark tests

90.2

Score on the first 500 larger, more well-known mathematical benchmark tests

AIME Score

An indicator measuring an AI model's ability to solve high-difficulty mathematical competition problems (specifically AIME level)

59.4

An indicator measuring an AI model's ability to solve high-difficulty mathematical competition problems (specifically AIME level)

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