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LatestOpenAIgpt-oss-120b
OpenAIReasoning

OpenAI Releases Its First Open-Source MoE Model

The new 117-billion-parameter `gpt-oss-120b` is a Mixture-of-Experts model focused on reasoning, released under a permissive Apache 2.0 license.

Aug 4, 2025
Major releaseApache 2.0
gpt-oss-20b

In a significant strategy shift, OpenAI has released gpt-oss-120b, its first-ever open-weight foundation model. The move places the historically closed-source company in direct competition with established open-source players like Meta and Mistral AI, signaling a new phase in the development of freely available AI.

The new model is a Mixture-of-Experts (MoE) architecture with a total of approximately 117 billion parameters. MoE models are designed for efficiency, activating only a fraction of their total parameters for any given task, which can lead to faster inference times and lower computational costs. According to the release notes, the model uses the MXFP4 data format and supports a generous 131,072-token context window.

OpenAI is releasing the model under the business-friendly Apache 2.0 license. This permissive approach allows for broad use, including commercial applications, which will likely accelerate its adoption among developers and researchers. The company highlights the model's strong performance on agentic and complex reasoning tasks, positioning it as a powerful tool for building sophisticated applications.

This release could reshape the open-source AI ecosystem by providing a new, high-quality baseline for development. Researchers and developers can now directly inspect, build upon, and fine-tune a model from the creators of the GPT series. All model weights and supporting files are available for download from the official Hugging Face repository.

Sources

  • openai/gpt-oss-120b

    Hugging Face

    Visit
OlderNVIDIA Releases Canary 1B v2 Multilingual Speech ModelNVIDIA · Speech → Text · last yearNewerOpenAI Releases 21B Open-Weight MoE ModelOpenAI · Reasoning · last year

Get the model

Hugging Face

Specs

Parameters117B · MoE
Active params3.6B active
Context window131K tokens
Size119 GB
PrecisionINT8
ArchitectureGptOssForCausalLM
LicenseAPACHE-2.0
Downloads2.5M
Likes5.5K

Can you run it?

Needs a workstation GPU (96 GB) as published.

  • MXFP4 4-bit (as published)

    80 GB GPU (A100 / H100) · 128 GB Mac Studio

    71.8 GB
Your machine
GGUF builds
  • Mixture-of-experts: all 117B parameters must be resident even though only 3.6B are active per token — active count affects speed, not memory.
  • Published weights are already quantized (MXFP4 4-bit); smaller builds are not assumed.
  • KV cache sized for 8,192 tokens of context; longer prompts need proportionally more.

Based on Hugging Face weights metadata. Assumes an 8K context and ~1 GB runtime overhead; actual needs vary. How we estimate


Modalities

Text / LLMReasoning
2 versions — view changelog

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