Free AI Coding - Claude Opus, DeepSeek, KMI via GitHub Codespaces + Kilo Code

📌 Quick Summary: Run advanced AI models like Claude Opus 4.7, KMI 2.6, DeepSeek V4 Pro completely free using GitHub Codespaces + Kilo Code extension and NVIDIA NIM API. No expensive GPU, no token worries. Build full‑stack applications in minutes. Step‑by‑step setup for beginners – works on any laptop with just a browser.

🚀 Free AI Coding: Claude Opus, DeepSeek, KMI via GitHub Codespaces + Kilo Code (2026)

Hey everyone! Welcome back to PakAlerts. Today I'm going to show you something that will completely change how you code – especially if you're tired of token limits and slow local models.

Have you ever been in the middle of building an advanced project, and suddenly your tokens run out? Or you wanted to use Claude Opus or the latest DeepSeek model, but they're locked behind expensive subscriptions? Not anymore.

In this guide, I'll walk you through a setup that lets you run Claude Opus 4.7, KMI 2.6, DeepSeek V4 Pro, and many other top models for free – using GitHub Codespaces (a cloud development environment) and the Kilo Code extension (a VS Code extension that connects to multiple AI providers). We'll also build a full‑stack shopping web app live, so you can see exactly how powerful this setup is.

Follow every step carefully – if you skip something, the setup might not work. Let's get started!

💡 What you'll learn: How to create a GitHub repository, launch Codespaces, install the Kilo Code extension, connect NVIDIA NIM API, add multiple free models, and build a full‑stack shopping app – all without writing a single line of code yourself!

🧰 Prerequisites – What You Need

• A free GitHub account (sign up at github.com).
• A web browser (Chrome, Edge, Firefox – anything works).
• A free NVIDIA account (to get API keys).
• No powerful PC needed – everything runs in the cloud.

📁 Step 1: Create a GitHub Repository

First, we need a place to store our code. GitHub Codespaces will use this repository to spin up a cloud development environment.

1. Go to github.com and log in.
2. Click the "+" icon in the top right, then select "New repository".
3. Give your repository a name – for example, "my-ai-project".
4. Scroll down and click "Create repository".
5. On the next page, click "README.md" then click "Commit changes" (this just creates a starting file).
6. Now click the "Code" button. You'll see a dropdown. Select "Codespaces" tab, then click "Create codespace on main".

Wait about 1‑2 minutes for your Codespace to be ready. It will open a full VS Code in your browser, with a terminal and file explorer. This is your cloud development environment – it's completely free for up to 60 hours per month (more than enough for learning and building).

📦 Step 2: Install the Kilo Code Extension

Kilo Code is a VS Code extension that lets you connect to multiple AI models – including free ones from NVIDIA, OpenRouter, etc.

1. In your Codespace, look at the left sidebar. Click the "Extensions" icon (four squares).
2. In the search bar, type "kilo code".
3. The first result is "Kilo Code" – click the "Install" button.
4. A popup may appear asking you to "Trust Publisher". Click "Trust Publisher".
5. After installation, you'll see a new Kilo Code icon on the left sidebar (looks like a little robot or chat bubble). Click it.

If you don't see the icon, close any unnecessary tabs (click the three dots on a tab and choose "Close All"). The Kilo Code interface should now be visible.

🔑 Step 3: Get Your NVIDIA NIM API Key

NVIDIA provides free API access to many powerful models. You don't need a credit card.

1. Open a new browser tab and go to build.nvidia.com/models.
2. Sign in with your NVIDIA account (create one if you don't have it – it's free).
3. Once logged in, click on "Explore" or "API Keys" from the menu.
4. Click "Generate API Key". Give it a name (e.g., "my-key") and set expiration to "Never Expire".
5. Copy the generated API key. Save it somewhere safe – you'll need it shortly.
6. Also note the Base URL for NVIDIA NIM. It's usually https://integrate.api.nvidia.com/v1.

⚙️ Step 4: Add a Custom Provider in Kilo Code

Now we'll connect Kilo Code to NVIDIA NIM by creating a custom provider.

1. Back in your Codespace, click the Kilo Code icon on the left sidebar.
2. Look for a Settings icon (gear) – click it. Kilo Code settings will open.
3. In the settings, click on "Providers" (or "Model Providers").
4. Scroll down to the bottom where it says "Custom Provider". Click "Connect".
5. Fill in the following:
   • Provider ID: give it a name, e.g., "nvidia-nim" (use lowercase, no spaces).
   • Display Name: "NVIDIA NIM" (or whatever you prefer).
   • Base URL: paste the NVIDIA base URL: https://integrate.api.nvidia.com/v1
   • API Key: paste your NVIDIA API key.
6. Now we need to add Model IDs – the names of the models we want to use. For example:
   • For KMI 2.6 – go back to NVIDIA models page, search for "KMI 2.6", click it, copy the model name from the URL or from the "View Code" section (usually something like moonchute/kmi-2.6 or nvidia/kmi-2.6).
   • Paste that Model ID into the Kilo Code custom provider settings.
   • Add a display name like "KMI 2.6".
7. Repeat for DeepSeek V4 Pro and Claude Opus 4.7 (if available via NVIDIA – check the models page). For Claude Opus, you may need to use a different provider like OpenRouter, but many models are directly available from NVIDIA's free endpoint.
8. Click "Submit" or "Save".

Wait a few seconds. You should see your custom provider listed as "Connected". That means Kilo Code can now talk to NVIDIA's free models.

🧪 Step 5: Test the Model – First Message

Let's verify that everything works.

1. Click the Kilo Code icon to open the chat interface.
2. At the top, there is a dropdown to select which model to use. Choose KMI 2.6 (or the first model you added).
3. Type a test message: "Hi" and press Send.
4. If it asks you to sign in or authorize, click "Open Browser" and authorize (this happens only once).
5. After a few seconds, you should get a reply. Congratulations – you're now using a top‑tier AI model for free!

Repeat the same for DeepSeek V4 Pro and other models to ensure they work.

🛠️ Step 6: Add More Models (Optional)

You can add multiple models to Kilo Code – all using the same NVIDIA NIM provider. Just go back to the custom provider settings and add more Model IDs. Popular free models on NVIDIA NIM include:

• DeepSeek V4 Pro – excellent for complex reasoning and code generation.
• KMI 2.6 (Kimi) – great for long context and coding.
• GLM 5.1 – powerful general purpose model.
• Qwen 2.5 – fast and efficient.
• MiniMax – comparable to Claude Sonnet.

To find the exact Model ID for each, go to the NVIDIA models page, click on the model, and copy the string that appears after /v1/ or from the "View Code" section.

💻 Step 7: Build a Full‑Stack Shopping App – Live Demo

Now let's put this setup to work. I'll ask Kilo Code (using the free AI model) to build a complete shopping web app.

Prompt used:

Create a full functional web app using HTML, CSS and JavaScript in the same page. It should be mobile as well as desktop friendly. Also it should use local storage to store data. You are going to create a shopping web app.

Within a few minutes, the AI generated over 14,000 lines of code – a complete shopping application with product listings, cart, wishlist, orders page, and checkout. It even included local storage persistence and a responsive design.

What the app included:

• Product grid with images, prices, and "Add to Cart" buttons.
• Cart page with quantity updates and total calculation.
• Wishlist functionality.
• Checkout form with address, email, and order placement.
• Orders page showing past orders.
• Mobile‑friendly layout using CSS grid/flexbox.
• A floating chat robot (assistant) that could answer questions.

When I requested the link to preview it locally, the AI started a simple HTTP server and provided a localhost URL. I clicked "Open in Browser", and the fully functional shopping app was live. The only minor issue was a missing product image placeholder – easily fixable.

This proves that these free models are capable of building production‑level applications. You don't need to spend money on expensive APIs or local GPUs.

📱 Mobile Responsiveness – It Works!

I tested the same app on a mobile view (by resizing the browser). The layout adjusted perfectly – two‑column grid, readable fonts, touch‑friendly buttons, and a working menu icon. The AI built it with responsive design in mind without even being explicitly told.

Build Android AI Assistant - No Coding! Claude AI + Android Studio (Natural Voice)

❓ Frequently Asked Questions

Q1: Is GitHub Codespaces really free?
A: Yes, GitHub offers 60 free core hours per month. That's enough for about 60 hours of coding. For learning and building projects, it's plenty.

Q2: Do I need to install anything on my computer?
A: No. Everything runs in your browser. You only need a GitHub account and an NVIDIA account. Your local machine doesn't need any special software.

Q3: Are there any hidden costs with NVIDIA NIM?
A: NVIDIA offers a generous free tier with 40 requests per minute – no daily limit. For normal development work, you'll never hit that. It's truly free.

Q4: Can I use this setup for commercial projects?
A: Yes. The code you generate is yours. NVIDIA's terms allow commercial use as long as you don't resell the API itself.

Q5: What if I want to run this on my local VS Code instead of Codespaces?
A: You can! Just install the Kilo Code extension in your local VS Code, follow the same custom provider steps, and use your NVIDIA API key. It works identically.

Q6: How long will the NVIDIA free models be available?
A: No one knows. NVIDIA hasn't announced an end date. Use it while it's available. I'll update this article if anything changes.

Q7: I'm stuck. How can I get help?
A: Leave a comment below this article (on our website). I personally reply to every query. You can also join our WhatsApp channel for quick community support.

Q8: Can I use other providers like OpenRouter or DeepSeek Direct API?
A: Yes, Kilo Code supports multiple providers. You can add them as separate custom providers. The process is almost identical – just use their base URL and API key.

🎯 My advice: This setup is a game changer for students, freelancers, and developers who want to build real applications without burning money on API calls. Don't just watch – try it yourself. Create a GitHub repo, launch Codespaces, install Kilo Code, add your NVIDIA key, and start building. The only limit is your imagination.

📚 Next Steps – What to Learn Next

• Explore more free models on the NVIDIA NIM platform – there are dozens available.
• Learn how to use Kilo Code's advanced features like context management, file editing, and diff reviewing.
• Build your own full‑stack application – a blog, a portfolio, a small e‑commerce site.
• Share your projects with the community – tag us on social media or join our WhatsApp channel to show what you've built.

📢 Liked this guide? If it helped you, please share it with a friend who's also into AI coding. And don't forget to subscribe to our newsletter for more free AI coding tutorials (link below).

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🔗 Resources: GitHub (github.com), NVIDIA NIM models (build.nvidia.com/models), Kilo Code extension (search in VS Code extensions). All commands and model IDs are mentioned above – copy them directly.

⚠️ Disclaimer: This setup uses free tiers of third‑party services. Availability may change. Always respect API terms of service. The code you generate is yours.