DataLearner logoDataLearnerAI
Latest AI Insights
Model Evaluations
Model Directory
Model Comparison
Resource Center
Tool Directory

加载中...

DataLearner logoDataLearner AI

A knowledge platform focused on LLM benchmarking, datasets, and practical instruction with continuously updated capability maps.

产品

  • Leaderboards
  • 模型对比
  • Datasets

资源

  • Tutorials
  • Editorial
  • Tool directory

关于

  • 关于我们
  • 隐私政策
  • 数据收集方法
  • 联系我们

© 2026 DataLearner AI. DataLearner curates industry data and case studies so researchers, enterprises, and developers can rely on trustworthy intelligence.

隐私政策服务条款
Page navigation
目录
Model catalogDeepSeek-V3
DE

DeepSeek-V3

DeepSeek-V3

Release date: 2024-12-26更新于: 2025-03-21 11:14:411,300
Live demoGitHubHugging FaceCompare
Parameters
6810.0亿
Context length
128K
Chinese support
Supported
Reasoning ability

Data sourced primarily from official releases (GitHub, Hugging Face, papers), then benchmark leaderboards, then third-party evaluators. Learn about our data methodology

DeepSeek-V3

Model basics

Reasoning traces
Not supported
Context length
128K tokens
Max output length
No data
Model type
聊天大模型
Release date
2024-12-26
Model file size
687.9 GB
MoE architecture
No
Total params / Active params
6810.0B / N/A
Knowledge cutoff
No data
Inference modes
No mode data
DeepSeek-V3

Open source & experience

Code license
MIT License
Weights license
DEEPSEEK LICENSE AGREEMENT- 免费商用授权
GitHub repo
https://github.com/deepseek-ai/DeepSeek-V3
Hugging Face
https://huggingface.co/deepseek-ai/DeepSeek-V3
Live demo
No live demo
DeepSeek-V3

Official resources

Paper
Introducing DeepSeek-V3
DataLearnerAI blog
开源大模型的新里程碑:DeepSeek AI开源6510亿参数的DeepSeek V3模型,评测结果显著好于4050亿参数的Llama3.1 405B,比肩Sonnet 3.5的开源模型
DeepSeek-V3

API details

API speed
No data
No public API pricing yet.
DeepSeek-V3

Benchmark Results

No benchmark data to show.
DeepSeek-V3

Publisher

DeepSeek-AI
DeepSeek-AI
View publisher details
DeepSeek-V3

Model Overview

DeepSeek AI开源的大语言模型,是其开源的第三代大语言模型。DeepSeek V3是一个混合专家架构的模型(Mixture-of-Experts),总参数量6810亿,每次推理会激活其中370亿的参数。DeepSeek V3模型在14.8万亿tokens上完成训练,花费了278.8万个H800小时训练完成,其各项评测结果都十分优异。


本版本是经过后训练(Post Training)之后的版本。

DataLearner 官方微信

欢迎关注 DataLearner 官方微信,获得最新 AI 技术推送

DataLearner 官方微信二维码