$ -weight: 500;">curl -fsSL https://ollama.com/-weight: 500;">install.sh | sh
-weight: 500;">curl -fsSL https://ollama.com/-weight: 500;">install.sh | sh
-weight: 500;">curl -fsSL https://ollama.com/-weight: 500;">install.sh | sh
const r = await fetch("http://localhost:11434/v1/chat/completions", { method: "POST", body: JSON.stringify({ model: "qwen2.5-coder:7b", messages: [{ role: "user", content: "Hello" }], stream: true, }),
});
const r = await fetch("http://localhost:11434/v1/chat/completions", { method: "POST", body: JSON.stringify({ model: "qwen2.5-coder:7b", messages: [{ role: "user", content: "Hello" }], stream: true, }),
});
const r = await fetch("http://localhost:11434/v1/chat/completions", { method: "POST", body: JSON.stringify({ model: "qwen2.5-coder:7b", messages: [{ role: "user", content: "Hello" }], stream: true, }),
}); - Ollama — best for developers who want a CLI and an HTTP API. The default for engineers.
- LM Studio — best for non-developers and researchers who want a polished GUI.
- Jan — best if open-source-everything matters and you want a ChatGPT-like UI you fully own. - You write code that calls local LLMs (90 percent of developers).
- You want a single binary on a server, not a desktop app.
- You're integrating with VS Code's Continue extension, LangChain, llama_index, or any OpenAI-compatible SDK.
- You care about idle RAM. - You want to chat with local models without writing code.
- You need to test exotic models that aren't in Ollama's registry.
- You like a polished UI for managing model files.
- You're doing model research and need fine-grained control over quantisation. - "Fully open-source, every dependency" is a hard requirement.
- You want a ChatGPT-style chat UI that's yours forever, regardless of what OpenAI does.
- You're building for users who want a desktop AI assistant they own, not a developer tool.
