gpt-oss-120b
A 117B (MoE) reasoning model whose MXFP4 weights fit a single 80GB GPU. View on Hugging Face.
What gpt-oss-120b is
gpt-oss-120b is a 117B-parameter mixture-of-experts language model published by OpenAI on Hugging Face, one of two open-weight gpt-oss models built for reasoning, agentic tasks and developer use. Its MoE weights are post-trained in MXFP4 precision, which the model card says is what lets a 117B-parameter model run on a single 80GB GPU (NVIDIA H100 or AMD MI300X). It supports configurable reasoning effort (low, medium, high), function calling, web browsing and Python code execution, and is released under Apache 2.0.
License note: fully permissive, no gating and no usage restrictions. Facts on this page are sourced from gpt-oss-120b's Hugging Face model card, not benchmarked by Aquanode.
What it's used for
- Reasoning and chain-of-thought tasks
- Agentic tool use and function calling
- Web browsing and code-execution agents
Deploy gpt-oss-120b
Needs 1× A100 at its published (MXFP4) precision. Aquanode doesn't run a hosted inference API for gpt-oss-120b. Spin up a GPU pod sized for it below and install your own inference stack (vLLM, SGLang, TGI, llama.cpp, Ollama, or whatever you prefer) on it.
Set up a podCheapest current fit at gpt-oss-120b's published (MXFP4) precision: 1× A100, at $0.851/hr per GPU ($0.851/hr total).
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