🧠 MagenticBrain Is Now Supported in ElBruno.LocalLLMs

⚠️ 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.

TL;DR

KnownModels.MagenticBrain is now ready for local .NET usage with ElBruno.LocalLLMs.
ONNX package is available at:
- https://huggingface.co/elbruno/MagenticBrain-onnx
Original model source:
- https://huggingface.co/microsoft/MagenticBrain
This support is designed to power end-to-end agentic app experiences such as:
- https://github.com/elbruno/ElBruno.MagenticUI

Why this model is important (and what it is designed for)

MagenticBrain is not just another general-purpose chat model. It is designed for agent orchestration: planning multi-step tasks, selecting tools, chaining tool calls across rounds, and deciding when to terminate with a final answer.

That design matters because many app scenarios need more than one prompt/one response:

file + web research workflows
iterative tool usage with state between turns
“do the task, then submit result” orchestration patterns

In short, MagenticBrain is built for agentic execution loops, which is why it is a strong fit for .NET + LocalChatClient + MagenticUI experiences.

When Microsoft Research introduced MagenticLite, MagenticBrain, and Fara1.5, they framed a practical path for local agentic workflows:

Official post:
- https://www.microsoft.com/en-us/research/blog/magenticlite-magenticbrain-fara1-5-an-agentic-experience-optimized-for-small-models/

For this repo, this post marks the concrete implementation milestone: MagenticBrain is now a first-class supported model in ElBruno.LocalLLMs.

Why this matters for MagenticUI scenarios

The target is a clean .NET workflow where orchestration and model inference stay in the same stack:

Use KnownModels.MagenticBrain in LocalChatClient.
Keep tool-calling and multi-round logic in C#.
Reuse the same model path for local multi-agent UX in MagenticUI-style applications.

This is exactly the scenario behind:

https://github.com/elbruno/ElBruno.MagenticUI

Basic usage: MagenticBrain in C#

1. Install

dotnet add package ElBruno.LocalLLMs --version 0.20.4

2. Create a local MagenticBrain client

			
using ElBruno.LocalLLMs;
using Microsoft.Extensions.AI;
var options = new LocalLLMsOptions
{
    Model = KnownModels.MagenticBrain,
    EnsureModelDownloaded = true,
    Temperature = 0.7f,
    MaxSequenceLength = 32768
};
using var client = await LocalChatClient.CreateAsync(options);

		

3. Use it in an agentic loop with tools

			
var response = await client.GetResponseAsync(
[
    new ChatMessage(ChatRole.System, "You are an agentic assistant. Use tools and call submit when done."),
    new ChatMessage(ChatRole.User, "List project files and summarize README.")
],
new ChatOptions
{
    Tools = tools
});

		

Repo samples you can run now

src/samples/MagenticBrainAgent
- OmniAgent-style round loop, tool calls, and submit stop-signal.
src/samples/MagenticUIServer
- Local multi-agent web sample with SignalR + React UI.
docs/magentic-ui-dotnet.md
- Architecture and setup details for MagenticUI .NET flow.