Add Japanese and English versions of gpt-oss deployment doc.

2026-03-26 13:18:34 +07:00 · 2025-08-13 12:20:41 +08:00
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+---
+title: " gpt-oss Local Deployment with Ollama and Dify "
+---
+# I. Introduction
+
+The gpt-oss series is an open-source model first released by OpenAI in August 2025.
+
+> gpt-oss:20b (fits systems with ~16 GB memory)
+>
+> gpt-oss:120b (designed for ≥ 60 GB memory)
+
+You can run it locally with Ollama. No cloud calls. Data stays on your machine, which helps with privacy and latency.
+
+Dify is an open-source platform for building AI Agents and Workflows. This guide shows how to run gpt-oss with Ollama and plug it into Dify for a private, high-performance setup.
+
+* * *
+
+# II. Environment Setup
+
+## Step 1: Run gpt-oss with Ollama
+
+1.  Install Ollama
+    
+
+[Download](https://ollama.com/) and install for macOS, Windows, or Linux. If anything is unclear, see the [official docs](https://docs.dify.ai/en/development/models-integration/ollama#integrate-local-models-deployed-by-ollama).
+
+  
+
+2.  Pull a model
+    
+
+```Bash
+# Recommended for most dev machines
+ollama pull gpt-oss:20b
+
+# For large GPUs or multi-GPU hosts
+ollama pull gpt-oss:120b
+```
+
+Both models are pre‑quantized in **MXFP4** , suitable for local deployment.
+
+  
+
+3.  Start Ollama
+    
+
+The default endpoint is http://localhost:11434.
+
+## Step 2: Install Dify locally
+
+See the [Dify docs](https://docs.dify.ai/en/getting-started/install-self-hosted/readme) for full instructions. Or follow the quick tutorial below.
+
+### Prerequisites
+
+Install [Docker](https://www.docker.com/products/docker-desktop/) and make sure Docker Engine is running.
+
+![1](https://raw.githubusercontent.com/NanSike/image-host/main/images/1.png)
+
+
+
+### Install steps
+
+```Bash
+git clone https://github.com/langgenius/Dify.git
+cd Dify/docker
+cp .env.example .env
+docker compose up -d
+```
+
+![2](https://raw.githubusercontent.com/NanSike/image-host/main/images/2.png)
+
+Open your local Dify instance and complete the initial setup.
+
+![3](https://raw.githubusercontent.com/NanSike/image-host/main/images/3.png)
+
+# III. Add the model and test chat
+
+1.  In **Settings → Model Providers → Ollama** , click **Add Ollama model type** .
+    
+
+![4](https://raw.githubusercontent.com/NanSike/image-host/main/images/4.png)  
+
+2.  Set **Base URL** to `http://localhost:11434`, select **Model name** `gpt-oss:20b`, and fill in the required fields.
+    
+
+![5](https://raw.githubusercontent.com/NanSike/image-host/main/images/5.png)
+
+  
+
+3.  Create a blank template
+    
+
+![6](https://raw.githubusercontent.com/NanSike/image-host/main/images/6.png)
+
+  
+
+4.  Select the app or workflow type you want to build.
+    
+
+![7](https://raw.githubusercontent.com/NanSike/image-host/main/images/7.png)
+
+* * *
+
+# IV. Verification and Usage
+
+*   On Dify’s **model testing** page, send a prompt and check that the response looks correct.
+    
+*   In a workflow, add an **LLM** node, select `gpt-oss:20b`, and connect the nodes end to end.
+    
+
+![8](https://raw.githubusercontent.com/NanSike/image-host/main/images/8.png)
+
+![9](https://raw.githubusercontent.com/NanSike/image-host/main/images/9.png)
+
+* * *
+
+# V. Appendix — FAQ and tips
+
+**Model Pull Is Slow**
+
+*   *Configure a Docker proxy or use an image mirror to speed up downloads.*
+    
+
+**Insufficient GPU Memory**
+
+*   *Use* *`gpt-oss:20b`*. You can enable CPU offloading, but responses will be slower.*
+
+**Port Access Issues**
+
+*   *Check firewall rules, port bindings, and Docker network settings to ensure connectivity.*