DeepSeek + Codeium Dual AI Setup - Complete Integration Guide

Most AI coding setups are either useless autocomplete toys or overhyped garbage that tries to replace your brain. Running DeepSeek and Codeium together hits the sweet spot - each tool does what it's actually good at without stepping on the other.

What Each Tool Actually Does

DeepSeek R1 is great when you need to think through complex problems. It's slower than a Windows update for simple questions, but when you're debugging a race condition or designing an API, it actually reasons through the problem instead of just pattern matching. The thinking mode isn't marketing BS - you can see it work through the problem step by step.

Codeium just autocompletes your code fast. That's it. Supports 70+ languages and the suggestions are usually right. It's not trying to be your AI pair programmer - it just fills in the boring stuff so you can focus on the hard problems.

How They Work Together (Without Fighting)

The setup is pretty straightforward - Codeium runs in the background doing autocompletion while you use DeepSeek for the hard stuff. They don't really conflict because they're doing completely different things.

Codeium handles the fast, frequent stuff - completing function calls, importing modules, writing boilerplate. DeepSeek gets called in when you need to actually think - debugging complex issues, reviewing architecture decisions, or figuring out why your code is running like shit.

Don't ask DeepSeek to autocomplete your imports - it'll spend 30 seconds 'thinking' about whether you want React or ReactDOM. Don't expect Codeium to debug your promise hell - it'll happily suggest more broken async code.

What You Actually Get

Using both beats the hell out of relying on just one tool, but don't expect miracles. The real benefit is that you stop context-switching between "writing code" mode and "thinking about code" mode.

Codeium keeps your typing flow going, so you're not constantly stopping to remember method names or import syntax. DeepSeek handles the times when you need to step back and actually think through a problem properly.

The API bills will make you cry though. If you use R1 for everything, expect $100+ monthly bills. I burned through $45 in a week when I first set this up and kept asking R1 stupid questions like 'what does this error mean' instead of just googling it.

Real Workflow That Actually Works

Here's how I use them day-to-day: Codeium runs constantly and just handles the autocomplete stuff. When I hit a problem that makes me stop and think, that's when I bring in DeepSeek.

Use Codeium for:

• Function completions and imports
• Boilerplate code generation
• Method signatures you can never remember
• Converting between similar patterns

Use DeepSeek for:

• "Why is this async function deadlocking?"
• "How should I architect this data pipeline?"
• "What's the best way to handle error propagation here?"
• Code reviews when you need a second opinion

The context sharing between them isn't perfect, but it's good enough. Just keep your project structure clean and both tools will understand what you're working on.

Ready to actually set this up? The implementation varies significantly between different IDEs, so let me walk through what actually works in practice.

Setting up DeepSeek and Codeium will make you question your career choices and you'll definitely want to rage quit at least twice, but it's worth it. Here's what actually works and what breaks in Cursor, Windsurf, and VS Code - based on actually doing this setup multiple times.

Prerequisites and API Setup

Get your API keys first - you'll need them. Go to DeepSeek's platform, register, and grab your keys. Current pricing is around $0.55 per million input tokens and $2.19 per million output tokens - yeah, it's pricier than the old promotional rates.

Codeium provides a generous free tier for individual developers, supporting unlimited autocompletions across 70+ programming languages. For team environments, Codeium's professional plans start at $12 per user per month, offering enhanced context awareness and priority support.

Cursor: Actually Pretty Easy

Cursor is the least painful option for this setup. Go to Settings > Models and add DeepSeek as a custom provider. Use https://api.deepseek.com/v1 as the endpoint and paste your API key.

What actually works:

• Set Codeium for tab completion (the autocomplete stuff)
• Use DeepSeek R1 for the chat (Cmd+L or Ctrl+L)
• Cmd+K for quick edits usually works with whatever model you have set

Here's what will definitely break:

• When DeepSeek's API shits the bed (not if, when), restart Cursor. Nobody knows why this black magic works but it does.
• The first API call sometimes times out - just try again.
• @codebase with DeepSeek R1 can be slow but gives good context for large projects.

The smart routing mostly works. Just remember that R1 is slow for simple questions - use V3 for quick stuff, R1 when you need it to actually think.

Windsurf: More Setup, But Works Well

Windsurf's setup is trickier but worth it if you like their flow-focused approach. You'll need to use Windsurf's built-in Cascade AI plus external connections for DeepSeek.

Install an AI client extension that can connect to OpenRouter or direct APIs. Either route works - OpenRouter makes it easier if you don't mind the middleman, or go direct to DeepSeek's API if you want to save a few cents.

What works well:

• Windsurf's native AI for quick suggestions and edits
• Codeium extension handles autocomplete
• DeepSeek R1 through the chat when you need serious thinking

Takes more fiddling to get right, but once it's working the experience is solid. You can route different tasks to different models based on what you're doing.

VS Code: More Work But More Control

VS Code takes more setup but gives you the most flexibility. Install the DeepSeek extension and Codeium extensions from the marketplace.

The soul-crushing reality:

• You'll need 2-3 extensions minimum and they sometimes conflict
• Codeium extension works great for autocomplete
• DeepSeek extension gives you a chat sidebar
• Continue extension is worth setting up if you want local models

Local setup with Ollama (if you want privacy):

## Install Ollama first
ollama pull deepseek-coder:6.7b
ollama pull deepseek-r1

Then configure Continue to use these. Takes 30 minutes if everything works, 2 hours if you hit the usual Docker/networking issues.

Ways this will definitely fuck you over:

• Extension conflicts are common - disable one if autocomplete breaks
• DeepSeek extension sometimes can't find the API - check your key again
• Continue + Ollama setup breaks if you update Docker or change networks

What actually works:

• Sometimes Codeium autocomplete just stops working for no reason - toggle it off and on
• DeepSeek R1 is slow as hell - I've waited 45 seconds for it to explain a simple function
• The @codebase feature works great until your project gets big, then it times out

Real setup times:

• Cursor setup: 10 minutes if you're lucky, 2 hours if the API decides to have a bad day
• VS Code setup: Plan for an afternoon. Seriously. I've lost entire weekends to extension conflicts

Now that you know the setup process, let me break down how these IDEs actually compare in real-world usage for this dual AI setup.