diff --git a/docs/inference-providers/_toctree.yml b/docs/inference-providers/_toctree.yml
index e6f4684d1..23a7c71f7 100644
--- a/docs/inference-providers/_toctree.yml
+++ b/docs/inference-providers/_toctree.yml
@@ -53,7 +53,7 @@
- local: guides/function-calling
title: Function Calling
- local: guides/gpt-oss
- title: How to use OpenAI's GPT OSS
+ title: How to use OpenAI gpt-oss
- title: API Reference
diff --git a/docs/inference-providers/guides/gpt-oss.md b/docs/inference-providers/guides/gpt-oss.md
index c7ad1447f..6ce17da60 100644
--- a/docs/inference-providers/guides/gpt-oss.md
+++ b/docs/inference-providers/guides/gpt-oss.md
@@ -1,10 +1,10 @@
-# How to use OpenAI's GPT OSS
+# How to use OpenAI gpt-oss
-This guide walks you through using OpenAI's latest GPT OSS models with Hugging Face Inference Providers. GPT OSS is an open-weights family built for strong reasoning, agentic workflows and versatile developer use cases, and it comes in two sizes: a one with 120B parameters ([gpt-oss-120b](https://hf.co/openai/gpt-oss-120b)), and a smaller one with 20B parameters ([gpt-oss-20b](https://hf.co/openai/gpt-oss-120b)).
+This guide walks you through using OpenAI's latest gpt-oss models with Hugging Face Inference Providers which powers the official OpenAI playground ([gpt-oss.com](https://gpt-oss.com)). gpt-oss is an open-weights family built for strong reasoning, agentic workflows and versatile developer use cases, and it comes in two sizes: a one with 120B parameters [gpt-oss-120b](https://hf.co/openai/gpt-oss-120b), and a smaller one with 20B parameters ([gpt-oss-20b](https://hf.co/openai/gpt-oss-120b)).
Both models are supported on Inference Providers and can be accessed through either the OpenAI-compatible [Chat Completions API](https://platform.openai.com/docs/api-reference/chat/completions), or the more advanced [Responses API](https://platform.openai.com/docs/api-reference/responses).
@@ -39,7 +39,7 @@ npm install openai
## Chat Completion
-Getting started with GPT OSS models on Inference Providers is simple and straightforward. The OpenAI-compatible Chat Completions API supports features like tool calling, structured outputs, streaming, and reasoning effort controls.
+Getting started with gpt-oss models on Inference Providers is simple and straightforward. The OpenAI-compatible Chat Completions API supports features like tool calling, structured outputs, streaming, and reasoning effort controls.
Here's a basic example using [gpt-oss-120b](https://hf.co/openai/gpt-oss-120b) through the fast Cerebras provider:
@@ -282,7 +282,7 @@ console.log(parsedOutput);
-With just a few lines of code, you can start using GPT OSS models with Hugging Face Inference Providers, fully OpenAI API-compatible, easy to integrate, and ready out of the box!
+With just a few lines of code, you can start using gpt-oss models with Hugging Face Inference Providers, fully OpenAI API-compatible, easy to integrate, and ready out of the box!
## Responses API
@@ -566,5 +566,5 @@ response.output.forEach((item, index) => {
-That's it! With the Responses API on Inference Providers, you get fine-grained control over powerful open-weight models like GPT OSS, including streaming, tool calling, and remote MCP, making it ideal for building reliable, agent-driven applications.
+That's it! With the Responses API on Inference Providers, you get fine-grained control over powerful open-weight models like gpt-oss, including streaming, tool calling, and remote MCP, making it ideal for building reliable, agent-driven applications.