The most efficient approach for a local installation is leveraging Docker containers.
Please adhere to the deployment steps listed below.
The engine will automatically fetch large dependencies in the background.
The installer will automatically analyze your hardware and select the optimal configuration.
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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