El Bruno

⚠️ This blog post was created with the help of AI tools. Yes, I used a bit of magic from language models to organize my thoughts and automate the boring parts, but the geeky fun and the 🤖 in C# are 100% mine.

The Microsoft Bing Search team just dropped something big:

👉 https://blogs.bing.com/search/April-2026/Microsoft-Open-Sources-Industry-Leading-Embedding-Model

They’ve open-sourced a new set of high-quality embedding models, designed to be competitive with state-of-the-art approaches — and ready to run in modern AI workflows.

And here’s the fun part 👇

You can already use these models from C#/.NET.

🤖 From Announcement to .NET in Minutes

I integrated these new models into a C# library:

👉 https://www.nuget.org/packages/ElBruno.LocalEmbeddings.Harrier

Now you can:

• Run embeddings locally
• Use Bing’s open models
• Plug into your .NET apps

🌍 A Personal Take: Multilingual FTW

Harrier shines with multilingual support.

You can embed content like:

• “Hello world!”
• “Hola mundo!”

…and still get meaningful semantic relationships — out of the box.

Perfect for global-ready AI apps 🌎

🧩 .NET + AI Ecosystem

You can combine this with:

• Foundry Local or Ollama for local AI
• Microsoft Foundry for cloud
• Microsoft Agent Framework for agents

🛠️ Getting Started

👉 https://www.nuget.org/packages/ElBruno.LocalEmbeddings.Harrier

using ElBruno.LocalEmbeddings.Harrier;

await using var generator = await HarrierEmbeddingGenerator.CreateAsync();

var embeddings = await generator.GenerateAsync(["Hello world!", "Hola mundo!"]);
Console.WriteLine($"Dimensions: {embeddings[0].Vector.Length}"); // 640

Samples:

👉 https://github.com/elbruno/elbruno.localembeddings/tree/main/samples/HarrierConsoleApp
👉 https://github.com/elbruno/elbruno.localembeddings/tree/main/samples/HarrierMultilingualSample