LLM local
ramalama
RamaLama is an open-source developer tool that simplifies the local serving of AI models from any source and facilitates their use for inference in productio…
★ 3,1 mil estrelasMIT
Ver o guia →// local-llm · openai/gpt-oss
GPT-OSS
GPT-OSS é um projeto de LLM local de código aberto de openai (openai/gpt-oss no GitHub). Tem 20.511 estrelas no GitHub e 2.190 forks, é publicado sob a licença Apache-2.0 e foi atualizado pela última vez no GitHub em 29 de outubro de 2026.
GPT-OSS — OpenAI open-weight language models: gpt-oss-120b for production reasoning and gpt-oss-20b for local use, Apache-2.0
★ 20,5 mil estrelas⑂ 2,2 mil forksApache-2.0atualizado out 2026
▦ visual: o README deste projeto não inclui nenhuma captura incorporável,
então aqui vai um marcador. O guia abaixo está completo mesmo assim.
então aqui vai um marcador. O guia abaixo está completo mesmo assim.
// dados do projeto
Dados do projeto
- Repositório
- openai/gpt-oss
- Estrelas no GitHub
- 20.511
- Forks
- 2.190
- Licença
- Apache-2.0
- Última atualização no GitHub
- 29 de outubro de 2026
- Categoria
- LLM local
- Tipo de ficha
- Guia de instalação completo
- Site oficial
- OpenAI open models
// como funciona
Como funciona
- Pick the model that fits your hardware
Choose gpt-oss-120b for production-grade reasoning on a single 80GB GPU, or gpt-oss-20b for lower latency and local or specialised use within 16GB of memory.
- Install a serving route
Use the Transformers library, vLLM, or the reference gpt-oss package from the repository — all three routes are documented in the README.
- Use the harmony format
Send prompts in the harmony response format, via the Transformers chat template or the openai-harmony package; using the models without it will not work correctly.
// recursos
Por que as pessoas gostam tanto
Two genuinely open-weight OpenAI models
A 120b production model and a 20b local model, both Apache-2.0, with weights on Hugging Face.
MXFP4 quantisation built in
Post-training MXFP4 quantisation of the mixture-of-experts weights is what lets the 120b model run on one 80GB GPU and the 20b model in 16GB.
High-reasoning design
The 120b model is positioned for general-purpose, high-reasoning use cases; the 20b model trades size for latency and local deployment.
Standard serving routes
Transformers, vLLM and the reference package are all documented, so the models drop into existing inference stacks.
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// execute você mesmo
Execute você mesmo
- Install the reference package
The repository reference implementation from PyPI.
pip install gpt-oss - Run with Transformers
The README route: the Transformers pipeline with the harmony chat template applied automatically.
https://cookbook.openai.com/articles/gpt-oss/run-transformers - Serve with vLLM
The README serving route for the smaller model.
vllm serve openai/gpt-oss-20b
// casos de uso
O que você pode criar
- Running an open-weight OpenAI model locally or on a single GPU server
- High-reasoning chat, coding and agent workloads with the 120b model
- Low-latency local or specialised deployments with the 20b model
- Studying open-weight mixture-of-experts models and MXFP4 quantisation
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// perguntas frequentes
Perguntas frequentes
Who makes GPT-OSS?
OpenAI, as its open-weight model family (gpt-oss-120b and gpt-oss-20b).
Is GPT-OSS free?
Yes — Apache-2.0 licensed open weights. You still pay for your own hardware or hosting.
What hardware do I need?
gpt-oss-120b fits a single 80GB GPU (H100 or MI300X class); gpt-oss-20b runs within 16GB of memory.
What is the harmony format?
The response format both models were trained with. The README is explicit: use it (via the Transformers chat template or the openai-harmony package) or the models will not work correctly.
How do I get started?
Pick a model for your hardware, install via Transformers, vLLM or the gpt-oss package, and serve it with the harmony format.
// continue explorando
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Baixe o GPT-OSS
Grátis e aberto: pegue o código-fonte, dê uma estrela no repositório e comece a criar.