Can You Supercharge AI Coding Workflow by Running OpenAI’s gpt-oss Models in VS Code? Discover the Surprising Truth!

Is Downloading OpenAI’s gpt-oss:20 and gpt-oss:120 with Ollama the Best Way to Boost Private AI Performance? Here’s the Honest Review!

OpenAI’s first open-weight language models, gpt-oss:20b and gpt-oss:120b, make it possible to run highly capable AI on your own computers. Here’s a simple, advisor-style overview of using these models with Ollama and GitHub Copilot in VS Code.

What are open-weight models?

OpenAI released gpt-oss:20b (about 21 billion parameters) and gpt-oss:120b (about 117 billion parameters) on August 5, 2025.

These models are “open-weight” instead of “open-source.” This means you get the trained model’s weights, but not the full code or training data. You can fine-tune the model for your needs, but you can’t see all details of how it was trained.

They’re released under the Apache 2.0 license, making them free for research, business, and tinkering.

Open-weight vs. open-source: What’s the real difference?

Open-weight models let anyone use, inspect, and adapt the weights. But true open source also means sharing the training data and how the model was built.

The EU AI Act now requires model makers to describe what data was used. OpenAI shares summaries, but not all details.

Some companies (like DeepSeek) go further and release both their code and training process.

Performance Benchmarks

gpt-oss:120b is nearly as strong as OpenAI’s o4-mini on deep reasoning and coding tests.

gpt-oss:20b, though much smaller, is close in ability to o3-mini, and often beats other open models.

Both models perform well on math, coding, general knowledge, and specialized tasks, even with fewer computing resources compared to earlier giants.

Hardware requirements

gpt-oss:20b runs on devices with 16GB RAM or VRAM (works on higher-end laptops and desktops).

gpt-oss:120b needs at least 60–80GB VRAM—most users will need access to a cloud server or specialized workstation.

Both models are memory-efficient thanks to techniques like Mixture-of-Experts (MoE), which activates only some parts of the network for each answer, and “quantization,” which shrinks the space the model requires.

How to Install and Use with Ollama

Ollama is a tool for downloading and running large AI models locally.

Steps:

1. Install the latest Ollama from the official website (older versions won’t support these models).
2. On Mac, use the DMG installer, and on Windows, use the setup executable.
3. Open a command window. Run ollama pull gpt-oss:20b to download. The model is about 14GB—give it some time.
4. To start using the model, run ollama run gpt-oss:20b.
5. Models in Ollama are stored in ~/.ollama/models/ (Mac) or C:\Users\<UserName>\OllamaModels\ (Windows).
6. If you prefer, try Ollama’s graphical interface.

If you see errors about Ollama version, update to the latest release.

Ollama Turbo Mode

Turbo Mode lets you run bigger models (including gpt-oss:120b) in the cloud, using Ollama’s high-performance servers.

Ollama Turbo is $20 per month. There’s also a free tier with 10,000 tokens (roughly 7,000 words) every week.

Turbo gives you fast, almost instant AI responses and saves your computer’s resources.

Integrating gpt-oss with GitHub Copilot in VS Code

Local models mean you control your data—code stays on your machine, which improves privacy.

After starting Ollama and pulling the model, open VS Code:

1. Open Copilot’s Model Picker.
2. Click “Manage Models.”
3. Select “Ollama” and pick your downloaded model.

You can use gpt-oss:20b in “Ask” mode. “Agent” mode may freeze if your RAM is tight or due to an incompatibility.

Possible Issues and Workarounds

gpt-oss:20b runs on high-RAM laptops but may slow down if you run many other apps at the same time. Closing other apps helps.

gpt-oss:120b almost always requires cloud Turbo mode due to its size.

If startup or runtime is slow, check you have the right hardware and software versions.

Benefits and Drawbacks

Positive:

• Run state-of-the-art AI with strong reasoning privately.
• Models are easy to download, fine-tune, and inspect.
• More affordable and open than past offerings.

Limitations:

• Not fully open-source—training recipes and raw data are unavailable.
• Performance jumps between model sizes are smaller than expected. Even huge models show only minor improvement, showing limits to scaling.
• Safety measures are strong, but anyone can fine-tune local models; extra caution is advised.

gpt-oss:20b is a friendly, privacy-focused AI tool for developers and learners. It’s simple to set up with Ollama and VS Code Copilot, especially for those who value running AI on their own machines. If you need high speed or the largest available model, Turbo mode is worth considering, though it’s not strictly local.

The release makes advanced AI much more accessible. If privacy, freedom, and hands-on use matter to you, OpenAI’s gpt-oss models are a happy upgrade for your AI projects.