The following is a detailed introduction, technical differences, and applicable population analysis of different DeepSeek models:
1. DeepSeek core model classification
DeepSeek’s models are mainly divided into three categories: * * general dialogue models * *, * * code generation models * *, and * * embedding models * *, each of which contains versions of different scales to meet diverse needs.
2. Model Explanation and Comparison
* * 2.1 Universal Dialogue Model**
-Model Name:
-Deepseek Chat Lite (Lightweight Version)
-Deepseek Chat (Standard Version)
-Deepseek Chat pro (Enhanced Version)
-* * Technical Features * : – * Parameter Scale * : Lite（7B）、 Standard (13b), Pro (30B+) – * Training data * : multilingual text (mainly in Chinese and English), encyclopedias, books, high-quality dialogue data – * Response speed * : Lite>Standard>Pro (speed is inversely proportional to model size) – * Core Competencies * : -Natural dialogue, knowledge Q&A, copywriting, multiple rounds of contextual understanding -The Pro version supports complex logical reasoning, such as mathematical calculations and event analysis – * Applicable scenarios * : -Lite version: Mobile application, real-time customer service (cost sensitive scenarios) – * Standard Version * : Intelligent Assistant, Educational Q&A (Balancing Performance and Cost) – * Pro version * : Enterprise level knowledge base, advanced data analysis (requiring high-precision scenarios) – * Target users * *:
-Start up companies (Lite), SaaS platforms (Standard), financial/healthcare enterprises (Pro)
* * 2.2 Code Generation Model**
-Model Name:
deepseek-coder-7bdeepseek-coder-33b
-Deepseek coder-33B instruction (instruction optimized version)
-* * Technical Features * : – * Supported languages * : Python, Java, C++, and over 20 other programming languages – * Code completion * : Automatically generate code snippets based on context -Debugging ability: Identify syntax errors and provide repair suggestions (only 33B+) – * Core Competencies * : -Code generation/completion, annotation writing, cross language translation, automated testing scripts -The- structversion supports complex instructions (such as’ implementing a sortable table with React ‘) – * Applicable scenarios * : -7B version: IDE plugin, simple script generation (low latency requirement) – * Version 33B * : Full stack development, legacy code migration (high complexity tasks) – * 33B instruction * : Educational programming, technical document generation (requires natural language interaction) – * Target users * *:
-Developer (individual/team), technical education platform, DevOps engineer
2.3 Embedding Models**
-Model Name:
-Deepseed embeddings small (256 dimensions)
-Deepseed embeddings large (1024 dimensions)
-* * Technical Features * : – * Semantic Understanding * : The Large version supports long text (up to 8192 tokens) – * Multilingual alignment * : The same semantic is close in vector space distance in languages such as Chinese/English/Japanese -Search Optimization: Fine tuning for RAG (Search Enhanced Generation) – * Core Competencies * : -Text vectorization, similarity calculation, large-scale semantic search -Support clustering analysis (such as user comment sentiment grouping) – * Applicable scenarios * : – * Small version * : Real time recommendation system (e-commerce product matching) – * Large version * : Legal document retrieval, academic paper plagiarism check – * Target users * *:
-Data scientist, recommendation system engineer, knowledge management platform
3. Model selection decision tree
Quickly match models based on requirements:
- * * Target area * *:
-Dialogue/Copywriting → Deepseek Chat Series
-Programming → Deepseek Coder Series
-Semantic analysis → deepseed embeddings` - * * Resource Limitations * *:
-Low computing power/latency sensitive → Lite/7B version
-High precision requirements → Pro/33B version - * * Budget considerations * *:
-Free quota → Priority trial of Small/Lite version
-Enterprise level → Contact sales to customize billing plan (such as monthly subscription based on Token)
4. Performance Comparison Table
| Model | Input unit price ($/1k tokens) | Output unit price ($/1k tokens) | Maximum Token length | Number of requests processed per second |
|---|---|---|---|---|
| deepseek-chat-lite | 0.0012 | 0.0018 | 4096 | 15 |
| deepseek-chat-pro | 0.0035 | 0.0050 | 8192 | 5 |
| deepseek-coder-7b | 0.0020 | 0.0030 | 4096 | 12 |
| deepseek-coder-33b | 0.0045 | 0.0065 | 8192 | 8 |
| Embeddings small | 0.0001 (fixed/time) | – | 512 | 50 |
| Embeddings large | 0.0003 (fixed/time) | – | 8192 | 20 |
5. Advanced features and limitations
-* * Fine tuning in the field * : -Only the enterprise version supports uploading private data to train exclusive models (requires signing an NDA) -Supporting industries: Medical (ICD-10 coding assistance), Legal (contract review) – * Usage restrictions * *:
-The free version cannot access the Pro model
-The code model prohibits the generation of malicious software (API keys will be banned if content censorship is triggered)
6. Latest News (Updated in 2024)
-Deepseek coder-7b: Added support for low code platforms (such as converting Figma designs into frontend code)
-Deepseek Chat Multimodal: Internal testing of image understanding ability (whitelist application required)
Suggest visiting the DeepSeek Model Center（ https://platform.deepseek.com/models ）Get real-time updates or dynamically query model parameters through the model_cards API endpoint.