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DeepSeek V3 Depth Guide

685B MoE Architecture and R1 Logic Model fully parsed

Total argument volume
685B
Activate Parameters
37B
Training costs
$5.57M
Open Source
MIT
Recent developments: 2025 AI Top of the Year
# The world is so full of shit # DeepSeek V3 Officially Update (2025.12) has been fully pacified in multiple programming benchmark tests Sonnet。 With its extreme MoE architecture optimization, DeepSeek is rewriting the global large model competition pattern.
2025.12.26
The latest version of DeepSeek V3 was released, and programming and logic capabilities were significantly enhanced.
2025.01
DeepSeek-R1 reasoning model published, COT (Cot) Power versus Shoulder OpenAI o1.
2024.12
DeepSeek V3 first edition released, 685B parameter MoE architecture shocked industry.
Core technology: Why is DeepSeek so strong?
• Mixed expert structure (MoE)
Provides in-depth knowledge through the total 685B parameter volume, but only 37B is activated per reasoning Parameters, which greatly increase the speed of response and reduce costs.
♪ The myth of the math ♪
The top performance was achieved at a training cost of $5.576 million only, approximately 1/10 of the cost of training in the same level abroad.
💻 Programming专精
The code generation, the Devug and system architecture depth optimization are currently the most popular domestic model developed.
MIT loose open source
The most liberal MIT agreements are used to support commercial and privatization deployment at the enterprise level without any restrictions.
🚀 DeepSeek 2025 Model Family barrel
DeepSeek-V3
General-purpose flagship
685B Total parameters
128K Context
¥1/M Enter price
DeepSeek-R1
Logical reasoning
Shoulder o1 The ability to reason.
CoT Thinking chain.
¥4/M Enter price

DeepSeek V3: 2025 National Production AI A year of transformation of the world

If 2024 is the year of the outbreak of the Generable AI, 2025 is the year of the "DeepSeek" The year. As a deep-seated demand from the Hangzhou Fantasia, DeepSeek passed DeepSeek-V3 and DeepSeek-R1 The release showed the world the top of the Chinese AI team in the design of the architecture for the use of efficiency and modelling.

1. 685B MoE Structure: Large and uncompromising art

DeepSeek-V3 uses complex hybrid specialist (Mixture-of-Experts, MoE) structures. Traditional dense models (e.g., GPT-4 needs to run all parameters in reasoning, while V3 has 68.5 billion total parameters but is handling specific Token When, only 370 of them will be activated. Billions of parameters. This design not only allows models to learn from extremely large and sophisticated knowledge points, but also achieves at the reasoning end a low delay comparable to that of medium models. For business applications, this means lower. Token cost and faster response experience.

2. R1 Model: Let AI learn to think

Follow V3 release DeepSeek-R1 Models, marking the official entry of the National Production AI into the "the age of reasoning." R1 Models have introduced large-scale intensive learning and Chain-of-Thought (the thought chain) technology. Unlike the normal model, R1- In-depth thinking is first undertaken in answering complex mathematical, logical or programming questions. This "rethinking back" pattern, it's in the The performance of the AIME and MATH topics in the competition is equal to OpenAI o1-preview.

3. Validity: $5.57 million miracle

In AI circles, DeepSeek is the most exciting thing to do than its extremely high-powered conversion ratio. According to official technical reports, V3 The entire pre-training process of the model cost only about 557.6. (c) Ten million dollars for electricity and computing rental costs. In contrast, the cost of training in a foreign homo-performance model is often in the billions. This "small-big" technology path proves how algorithmic innovation is. AI Central position in competition.

4. Open-source power: the far-reaching implications of the MIT agreement

DeepSeek chose the most thorough open source path - MIT Protocol 。 This means that anyone can download the model weights free of charge, fine-tuning or even commercial profits, and that additional authorization costs do not have to be met, as in some “false open source” models. This move has greatly facilitated the process. The spread of the corporate level privatization in 2025, and many enterprises that are extremely sensitive to data security have begun to shift to a DeepSeek-based approach to the development of a new business environment. The Self-Research Programme.

5. Summary: How do developers capture the DeepSeek dividend?

As a developer, it's the best time to access DeepSeek ecology. You can pass API Fast integration of its flagship capacity can also be attempted locally for vertical fine-tuning of the Coder or Chat versions. DeepSeek It's not just a model, it's more an efficient, open, practical AI technology route.