gpt-oss
OpenAI's Apache-2.0 open-weight reasoning models at 120B and 20B, its first open release since GPT-2.
About
gpt-oss is OpenAI's first open-weight release since GPT-2: two Apache-2.0 mixture-of-experts reasoning models shipped in August 2025. gpt-oss-120b has 117B total and 5.1B active parameters and fits a single 80 GB GPU such as an H100 or MI300X, while gpt-oss-20b (21B total, 3.6B active) runs within 16 GB of memory on consumer hardware. MoE weights are natively quantized to MXFP4 with everything else in BF16, and the models expose configurable reasoning effort at low, medium, or high, plus function calling, structured outputs, and built-in browsing and Python tools. They require the harmony response format to work correctly, and the repository provides educational PyTorch, Triton, and Metal reference implementations along with the tool code, while support landed quickly in Ollama, LM Studio, vLLM, and llama.cpp. Apache-2.0 licensing means no copyleft or usage restrictions for commercial deployment. With over 20k GitHub stars and a dedicated OpenAI cookbook section, gpt-oss rapidly became a default choice for local reasoning and agent experiments.
Reviews (0)
Leave a Review
No reviews yet. Be the first to review!
Details
- Category
- Large Language Models (LLMs)
- Price
- Free
- Platform
- Local/Desktop
- Difficulty
- Easy (2/5)
- License
- Apache-2.0
- Minimum VRAM
- 16 GB
- Added
- Jul 29, 2026
Related Tools
Lightweight open-weight LLM by Google available in 1B to 27B sizes.
Open-source code LLM family by IBM for enterprise code generation.
Open-weight LLM by Meta in 8B and 70B sizes with strong general capabilities.
High-performance open-weight MoE LLM with 671B total parameters.
Hybrid SSM-Transformer model by AI21 Labs combining Mamba with attention layers.
Open-weight code LLM trained on 2 trillion tokens of code and natural language.