DeepSeek Coder

What is DeepSeek Coder?

DeepSeek Coder is an open-source language model (LLM) specialized in software engineering and programming tasks. Developed by the AI research company DeepSeek, the model stands out for its outstanding efficiency and performance, widely considered one of the best open-source code models in the world. It was trained on more than 2 trillion tokens containing actual GitHub repositories across over 80 different programming languages, achieving competitive results compared to closed proprietary models like GPT-4.

How it works

DeepSeek Coder can be downloaded from public repositories (such as Hugging Face) or consumed through cloud API keys. It works by integrating with code editors via AI extensions. The model is proficient in generating code from natural language prompts, inline code completion (smart autocomplete via Fill-in-the-Middle), finding bugs, and suggesting refactoring for performance optimization.

Key features

• Different Parameter Sizes: Availability of models ranging from 1.3B parameters (light enough to run locally on a laptop) up to 33B and large-scale MoE (Mixture of Experts) models.
• 16k to 128k Token Context Window: Ability to absorb long code blocks and dependencies from multiple files at the same time.
• Fill-in-the-Middle (FIM): Extraordinary performance in autocompleting code within existing files, predicting correct imports and variable declarations.
• Extraordinarily Low API Cost: One of the cheapest commercial AI APIs in the world, costing a tiny fraction compared to OpenAI or Anthropic APIs.

Available integrations

As an open-source foundation model, DeepSeek Coder is widely integrated into the development tool ecosystem:

• Code editors and IDEs: Cursor Editor, VS Code (with extensions), JetBrains.
• Assistant extensions: Continue.dev, Llama.coder, Tabby.
• Local model executors: Ollama, LM Studio, vLLM.

Who it is for

• Software Developers and DevOps looking for an advanced and low-cost code copilot for their daily work.
• Technology Companies needing to deploy and customize proprietary programming models on internal private servers.
• Students and computer enthusiasts interested in running and experiencing offline code copilots for free.

Pricing

Pros and cons

Pros:

• Excellent performance in programming logic and automated testing, beating larger closed models in development benchmarks.
• Free to run on local computers with common consumer graphics cards (1.3B and 7B versions).
• Stable API with ultra-low response latency.

Cons:

• Advanced training documentation is focused on English and Mandarin, although the model generates code in other languages without difficulties.
• Larger versions of the model (MoE / 33B) require significant hardware resources if hosted locally.

Alternatives to DeepSeek Coder

Prominent competing models focused on software development are: Codestral (from Mistral AI), CodeLlama (from Meta), StarCoder 2, and Qwen2-Coder.