In this categoryLocal AI · 24
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- How to Install Ollama on Windows
- How to Run Llama 3 Locally with Ollama
- How to Pick the Right Local AI Model for Your Hardware
- Best GGUF Models to Run by VRAM Tier (8GB, 12GB, 16GB, 24GB, 48GB)
- Run LLMs in Your Browser With WebGPU: No Install, No Server (WebLLM)
- How to Use Ollama as a Drop-In OpenAI API
- GGUF vs MLX vs NVFP4: Local AI Quantization Formats Explained
gpt-oss-20b vs gpt-oss-120b: Which Open Model Should You Run?
OpenAI shipped two open-weight models. One runs on a laptop, the other needs a serious GPU. Here is exactly how they differ and which one fits your hardware and use case.
When OpenAI released gpt-oss, it shipped two sizes: gpt-oss-20b and gpt-oss-120b. Both are Apache 2.0, both are mixture-of-experts, and both run locally — but the hardware they demand and the quality they deliver are very different. This guide breaks down the practical differences so you pick the right one the first time instead of downloading 65 GB you cannot run.
The specs side by side
| gpt-oss-20b | gpt-oss-120b | |
|---|---|---|
| Total parameters | 20.9B | 117B |
| Active per token | 3.6B | 5.1B |
| Memory needed | ~16 GB | ~60–80 GB |
| Download size | ~13 GB | ~65 GB |
| Context window | 128K | 128K |
| License | Apache 2.0 | Apache 2.0 |
| Runs on | 16 GB laptop / GPU / Mac | 80 GB GPU or 64 GB+ unified Mac |
| Ollama tag | gpt-oss:20b | gpt-oss:120b |
Choose gpt-oss-20b if…
- You have a 16 GB laptop, a 16 GB GPU, or an Apple Silicon Mac with 16–24 GB of unified memory.
- You want fast, responsive everyday use: chat, coding help, summarization, drafting.
- You are running it alongside other apps and cannot dedicate the whole machine to one model.
- You are just getting started with local AI and want the lowest-friction path.
Choose gpt-oss-120b if…
- You have an 80 GB datacenter GPU (H100/A100), a multi-GPU rig, or a Mac with 64 GB+ unified memory (M-series Pro/Max/Ultra).
- You need the strongest reasoning and coding quality an open OpenAI model can give, and you are willing to trade speed and hardware cost for it.
- You are building a shared inference server for a team rather than a personal assistant.
How to run whichever you pick
Both install the same way through Ollama — the only thing that changes is the tag. For the full step-by-step (install, first chat, reasoning control, and the OpenAI-compatible API), follow our guide on running gpt-oss-20b locally with Ollama; swap in gpt-oss:120b if your hardware can handle it.
Local models run better with more VRAM. CompareRTX GPUs on Amazonbefore you upgrade.(affiliate link. We may earn a commission at no extra cost. Disclosure)
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