DeepSeek-Coder
DeepSeek-Coder is a series of code-specialized large language models developed by DeepSeek, designed to support software development tasks. The models are pre-trained on large-scale code corpora covering multiple mainstream programming languages, and support code generation, completion (including Fill-in-the-Middle), code comprehension, and bug repair. The series is applicable to programming assistance and automated code generation scenarios.
Core Facts
Alibaba Cloud's Qwen2.5-Coder series is optimized specifically for coding scenarios and has reached internationally leading levels on multiple code generation benchmarks.
DeepSeek-Coder employs a Fill-in-the-Middle (FIM) training strategy, making it well-suited for code completion scenarios.
DeepSeek-Coder is pre-trained on a mixed corpus of code and natural language exceeding 2 trillion tokens and supports more than 80 programming languages.
Timeline (last 90 days)
Models optimized for role-playing cannot match the coding capabilities of dedicated coding models such as the Qwen-Coder and DeepSeek-Coder series.
7B-class code models (such as Qwen2.5-Coder 7B and DeepSeek-Coder) can understand common HTML/CSS/JavaScript requirements and generate basic component code
Developers can use tools such as Ollama and LM Studio to run open-source code models (such as DeepSeek Coder and Code Llama) locally as a backup solution; their capability ceiling is below that of top cloud-based models but they are fully controllable.
Code large models such as DeepSeek Coder, CodeLlama, and StarCoder all follow a technical path similar to that of Codex
Alibaba Cloud's Qwen2.5-Coder series is optimized specifically for coding scenarios and has reached internationally leading levels on multiple code generation benchmarks.
All Facts (12)
Alibaba Cloud's Qwen2.5-Coder series is optimized specifically for coding scenarios and has reached internationally leading levels on multiple code generation benchmarks.
80%VerifiedDeepSeek-Coder employs a Fill-in-the-Middle (FIM) training strategy, making it well-suited for code completion scenarios.
80%VerifiedDeepSeek-Coder is pre-trained on a mixed corpus of code and natural language exceeding 2 trillion tokens and supports more than 80 programming languages.
80%VerifiedPass rates of code generation models on benchmarks such as HumanEval jumped from 60% to over 90% between 2024 and 2025
80%VerifiedThe open-source version of DeepSeek-Coder includes multiple parameter scales such as 1.3B, 6.7B, and 33B.
70%UnverifiedDeepSeek-Coder具备16K甚至更长的上下文窗口
80%Unverified可以用Ollama等工具在本地部署开源编程模型（如CodeLlama、DeepSeek-Coder），需要至少16GB显存
75%UnverifiedDeepSeek-Coder在多项编程基准测试中达到国际领先水平
70%UnverifiedDevelopers can use tools such as Ollama and LM Studio to run open-source code models (such as DeepSeek Coder and Code Llama) locally as a backup solution; their capability ceiling is below that of top cloud-based models but they are fully controllable.
60%UnverifiedCode large models such as DeepSeek Coder, CodeLlama, and StarCoder all follow a technical path similar to that of Codex
60%UnverifiedModels optimized for role-playing cannot match the coding capabilities of dedicated coding models such as the Qwen-Coder and DeepSeek-Coder series.
50%Unverified7B-class code models (such as Qwen2.5-Coder 7B and DeepSeek-Coder) can understand common HTML/CSS/JavaScript requirements and generate basic component code
50%