Model release

gpt-oss-120b

gpt-oss-120b is an open-weight model release in the gpt-oss family from OpenAI1 2, version gpt-oss-120b, released Aug 2025. Its weights can be downloaded by the public2 under the Apache License 2.03 1.

gpt-oss-120b is the larger gpt-oss model: a 36-layer mixture-of-experts transformer with 116.8B total and about 5.1B active parameters per token, using 128 experts with the top 4 selected per token. It is text-only, supports context up to 131,072 tokens, and ships with its MoE weights quantized to MXFP4.1

Model hub: Hugging Face model card (external site: huggingface.co)
Repository: gpt-oss repository (external site: github.com)
Paper: Model card (arXiv) (external site: arxiv.org)
License: LICENSE (Apache 2.0) (external site: huggingface.co)

Last reviewedSep 29, 2026Entry updated Sep 29, 2026Documented release Aug 2025

Availability and license

Overall availability

Public

Downloadable from Hugging Face without gating.2

Availability fact review: not separately recorded

Availability is separate from permission: read the license before using or redistributing.

Apache License 2.0 (external site: huggingface.co)3 1
Applies to: Weights · SPDX Apache-2.0 · on the rubric’s OSI-approved software-license list · fact-level rights review not recorded
Plain-language guide to the Apache License 2.0
Apache License 2.0 (external site: github.com)6
Applies to: Code · SPDX Apache-2.0 · on the rubric’s OSI-approved software-license list · fact-level rights review not recorded
Plain-language guide to the Apache License 2.0

The model card says the models are available under Apache 2.0 and OpenAI's gpt-oss usage policy. The USAGE_POLICY file shipped with the weights is a short statement asking users to comply with all applicable law; it adds no further listed restrictions.1 4

Component reuse rights

A readable or downloadable component is not automatically reusable. These indicators concern recorded license evidence, not system certification.

weights: Unknown — no complete fact-level rights review
code: Unknown — no complete fact-level rights review
data: Unknown — no complete fact-level rights review
documentation: Unknown — no complete fact-level rights review

No complete system-rights review is recorded for this release.

Model-disclosure tier

Computed from the checklist below using USASI rubric v0.2. An editorial category, not a certification.

Open-weight

The model parameters for this release can be downloaded by the public. License terms may still restrict use, redistribution, or commercial use.

How tiers are computed

Public materials checklist

Items for a model under USASI rubric v0.2. Unknown means unassessed or insufficient evidence.

Public materials checklist for gpt-oss-120b
Item	Status	Notes and evidence
WeightsCan the general public download the model parameters for this release?	Public	MXFP4-quantized MoE weights plus an original-format checkpoint are in the Hugging Face repository.2
Inference codeIs code for running the model published?	Public	The GitHub repository has reference PyTorch, Triton, and Metal implementations, tools, and a Responses API server.5
Training codeIs the code used to train the model published?	Unknown	The official repository covers inference, tools, and evaluation; no training code was found.
Training-data informationDoes the information cover provenance, scope, acquisition, selection, labeling, processing, and where data or alternatives can be obtained? Access alone does not establish completeness.	Unknown	Not assessed.
Training-data accessCan the training data be obtained? This is independent of information completeness and reuse rights; original unshareable data need not be downloadable.	Unknown	Not assessed.
Complete training pipelineIs the complete base-training and preprocessing pipeline published, including configuration? Fine-tuning code or an inference SDK alone is insufficient.	Unknown	Not assessed.
Legacy data assessment (v0.1)Historical assessment combining download access and disclosure. Preserved for traceability; excluded from the v0.2 tier calculation. See the new separate assessments above.	Partial	The model card describes a text-only dataset of trillions of tokens focused on STEM, coding, and general knowledge, filtered for hazardous biosecurity content, with a June 2024 knowledge cutoff. The data itself is not released.1
Training recipeAre the training configuration and procedure documented in enough detail to follow?	Partial	The model card documents architecture, tokenizer, training compute (2.1 million H100-hours), and post-training with chain-of-thought reinforcement learning at a high level, not in reproducible detail.1
Evaluation materialsPublic = evaluation code or prompts that let others re-run the evaluations are published. Partial = results only.	Public	The model card reports benchmark and safety results; the repository includes evaluation code adapted from simple-evals for running GPQA and HealthBench.1 7

What it is useful for

Presented for production, general-purpose, and high-reasoning use cases, including tool use, function calling, and fine-tuning on a single H100 node.2

Run and use notes

Documented facts only. No hardware or performance claims are made without a cited source and stated assumptions.

The model card documents running the model with Transformers, vLLM, Ollama, and LM Studio, and OpenAI's repository provides reference PyTorch, Triton, and Metal implementations.2 5
OpenAI states that with its MoE weights in MXFP4 precision (4.25 bits per parameter), gpt-oss-120b fits on a single 80GB GPU such as an NVIDIA H100 or AMD MI300X; the model card lists the checkpoint size as 60.8 GiB.1 2
The model must be prompted with OpenAI's harmony response format; the model card says it will not work correctly otherwise.2

Organization context

OpenAI

Provenance and derivatives

Catalog records that name this entry in their provenance:

gpt-oss-safeguard-120b

Other releases in the gpt-oss family

gpt-oss-20bModel-disclosure tier (USASI rubric v0.2): Open-weight

gpt-oss family overview

What this catalog does not know

Unknown means the sources reviewed for this record do not document it. It is not evidence that something does not exist.

Training code: unknown.
Training-data information: unknown.
Training-data access: unknown.
Complete training pipeline: unknown.

Have a primary source? How to report a correction.

U.S. eligibility

Project eligibility rests on documented governing or maintaining entities, not on contributors.

Eligible · basis: U.S. headquarters

Developed and published by OpenAI. Its operating company, OpenAI Group PBC, lists its address in San Francisco, California, in a February 2026 SEC-filed agreement.1 8

Assessed Sep 29, 2026

Sources

1.
gpt-oss-120b & gpt-oss-20b Model Card (external site: cdn.openai.com)
OpenAI · Model card · published Aug 5, 2025 · accessed Sep 29, 2026
2.
openai/gpt-oss-120b (external site: huggingface.co)
OpenAI (Hugging Face) · Model card · accessed Sep 29, 2026
3.
openai/gpt-oss-120b LICENSE (external site: huggingface.co)
OpenAI (Hugging Face) · License · accessed Sep 29, 2026
4.
openai/gpt-oss-120b USAGE_POLICY (external site: huggingface.co)
OpenAI (Hugging Face) · License · accessed Sep 29, 2026
5.
openai/gpt-oss (GitHub repository) (external site: github.com)
OpenAI · Repository · accessed Sep 29, 2026
6.
openai/gpt-oss LICENSE (external site: raw.githubusercontent.com)
OpenAI · License · accessed Sep 29, 2026
7.
gpt_oss.evals README (external site: raw.githubusercontent.com)
OpenAI · Repository · accessed Sep 29, 2026
8.
Exhibit 10.1: Equity commitment letter agreement between OpenAI Group PBC and Amazon (external site: sec.gov)
U.S. Securities and Exchange Commission (Amazon.com, Inc. filing) · Filing · published Feb 27, 2026 · accessed Sep 29, 2026

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This listing is not an endorsement, a safety assessment, or a federal approval.

Cite this page

APA style

USASI. (2026, September 29). gpt-oss-120b. United States of America Superintelligence. https://unitedstatesofamericasuperintelligence.com/open/gpt-oss-120b/

BibTeX

@misc{usasi_gpt_oss_120b,
  author = {{USASI}},
  title = {gpt-oss-120b},
  year = {2026},
  month = sep,
  howpublished = {\url{https://unitedstatesofamericasuperintelligence.com/open/gpt-oss-120b/}},
  note = {United States of America Superintelligence. Last updated 2026-09-29}
}

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