FireConnect Open Models from MS Foundry to GH Copilot, or any other AI Coding Harness

#githubcopilot #llm #fireworks #tutorial

❓ Impressed by the latest open-source model benchmarks and eager to use those models in GitHub Copilot?

❓ Using several AI coding tools and tired of configuring bring-your-own-key (BYOK) access separately in each one?

🔥 FireConnect is an open-source CLI that connects agentic coding tools to open-source model families such as Llama, Qwen, DeepSeek, Kimi, and GLM.

💡 A reminder about native GH Copilot models

At the time of writing, GitHub Copilot already supports 30 models, including open models such as Kimi K3.

FireConnect becomes useful when you want:

Faster access to an expanding range of models
One configuration pattern across coding tools (GitHub Copilot, Claude Code, Cursor)
Install once, sign in once, then flip any supported harness on or off without hand-editing config files

What is Fireworks and FireConnect?

💡 Fireworks AI is a high-performance inference and fine-tuning platform focused on open-source models such as Llama, Qwen, DeepSeek, Kimi, and GLM.

💡 Microsoft announced Fireworks AI as an official first-party inference provider inside Foundry in March 2026.

💡 FireConnect is the bridge between your AI coding harness and the model ecosystem, letting you plug in models your tool does not natively offer without changing how you work.

🤔 Wait, aren't open models already available on Foundry?

Yes, Microsoft Foundry already offers a rich catalog of models, including open source models sold directly by Azure. Fireworks provides an alternative inference path for many of those models at a quicker pace. Fireworks brings its own rapidly evolving catalog backed by an optimized inference platform that's directly integrated into Foundry.

Some examples:

Model	Direct from Azure	Via Fireworks on Foundry
Kimi K3	❌ No	✅ Yes
GLM 5.2	❌ No	✅ Yes
Kimi K2.7 Code	✅ Yes	✅ Yes
DeepSeek V4 Pro	✅ Yes	✅ Yes

🤔 Looks like just another way of Bring Your Own Key (BYOK), do I really need FireConnect ?

If you only need a custom model for GH Copilot CLI or GH Copilot inside VS Code, BYOK is more than enough and works great!

FireConnect becomes much more interesting when you use multiple AI coding harnesses—such as GitHub Copilot, Cursor, Claude Code, Codex, or others—and want a more consistent way to connect and route them to models available through Fireworks AI. Instead of configuring every harness independently against different model-provider interfaces, FireConnect provides a common integration layer across supported tools.

FireConnect will fit in perfectly when you need a single control plane across multiple AI coding tools such as GH Copilot, Cursor, Claude Code and others.

When to Use Which Approach?

Use-Case Built-in providers and Extensions Custom Endpoint with FireConnect

Use a single model in VS Code chat ✅ Just add your key and go Works, but overkill for this

Use the same Fireworks models across Copilot, Cline, Continue, etc. ❌ Set up each tool separately ✅ One setup — toggle harnesses on/off

Get Fireworks latency and routing out of the box ❌ Generic endpoint, you're on your own ✅ Built for Fireworks, tuned for their infrastructure

Get your whole team on the same model config ❌ Everyone sets it up manually ✅ Shared config that anyone can reproduce

Use-Case	Built-in providers and Extensions	Custom Endpoint with FireConnect
Use a single model in VS Code chat	✅ Just add your key and go	Works, but overkill for this
Use the same Fireworks models across Copilot, Cline, Continue, etc.	❌ Set up each tool separately	✅ One setup — toggle harnesses on/off
Get Fireworks latency and routing out of the box	❌ Generic endpoint, you're on your own	✅ Built for Fireworks, tuned for their infrastructure
Get your whole team on the same model config	❌ Everyone sets it up manually	✅ Shared config that anyone can reproduce

Warning

FireConnect provides technical integration between Claude Code and Fireworks models through an Anthropic-compatible endpoint. But, this is not an Anthropic-endorsed configuration, and Anthropic does not provide support for routing Claude Code to non-Claude models through third-party gateways.

So maybe as a fun fact we can say:

Claude Code can technically be configured to go outside the Claude family to make most out of open weighted models, but Anthropic currently doesn't like this 😁

How to Get Started

Prerequisites

An active Azure subscription with the Fireworks integration enabled. See the Fireworks on Foundry setup guide.
A Microsoft Foundry project and a deployment of your preferred open-weight model from the Fireworks model catalog.

Step 1: Set Up the Foundry Resource and Project

Before running the Azure CLI commands, create a local .env file in the repository root. These variables are used by the commands below.


RESOURCE_GROUP=my-fireconnect-rg

AZURE_REGION=eastus

FOUNDRY_RESOURCE_NAME=my-fireconnect-foundry

PROJECT_NAME=my-fireconnect-project

MODEL_NAME=FW-GLM-5.2

BASE_URL=https://<your-resource-name>.services.ai.azure.com/

AZURE_API_KEY=your_key


# Load the variables into your current Bash session.

set -a

source .env

set +a

# create the resource group

az group create \\

  --name "$RESOURCE_GROUP" \\

  --location "$AZURE_REGION"

# Create the Microsoft Foundry resource.

az cognitiveservices account create \\

  --name "$FOUNDRY_RESOURCE_NAME" \\

  --resource-group "$RESOURCE_GROUP" \\

  --location "$AZURE_REGION" \\

  --kind AIServices \\

  --sku S0 \\

  --custom-domain "$FOUNDRY_RESOURCE_NAME" \\

  --yes

# Create the Microsoft Foundry project.

az cognitiveservices account project create \\

  --project-name "$PROJECT_NAME" \\

  --name "$FOUNDRY_RESOURCE_NAME" \\

  --resource-group "$RESOURCE_GROUP" \\

  --location "$AZURE_REGION"

Step 2: Deploy a Fireworks Model on Foundry

Model benchmarks evolve frequently. For this example, I’ll use GLM-5.2 from Z.ai, which ranked among the strongest open-weight coding models in recent evaluations. See the GLM-5.2 benchmark analysis.


# Inspect the model format.

MODEL_NAME="FW-GLM-5.2"

MODEL_INFO=$(az cognitiveservices account list-models \\

  --name "$FOUNDRY_RESOURCE_NAME" \\

  --resource-group "$RESOURCE_GROUP" \\

  | jq --arg MODEL "$MODEL_NAME" '.[] | select(.name == $MODEL)')

echo "$MODEL_INFO"

# Deploy the model.

az cognitiveservices account deployment create \\

  --resource-group "$RESOURCE_GROUP" \\

  --name "$FOUNDRY_RESOURCE_NAME" \\

  --deployment-name "$MODEL_NAME" \\

  --model-format "Fireworks" \\

  --model-name "$MODEL_NAME" \\

  --model-version "1" \\

  --sku-name "DataZoneStandard" \\

  --sku-capacity 100

Step 3: Install, Upgrade, and Configure FireConnect

Install FireConnect, then configure its global VS Code settings:


# Install FireConnect.

curl -fsSL https://raw\.githubusercontent.com/fw-ai/fireconnect/main/install.sh | bash

fireconnect upgrade

# Configure the global FireConnect settings.

fireconnect configure \\

  --provider azure \\

  --base-url "$BASE_URL" \\

  --api-key "$AZURE_API_KEY"

fireconnect vscode on --model FW-GLM-5.2

fireconnect vscode status

Start or restart VS Code, open Copilot Chat, and pick a Fireworks model from the model picker.

For one-off routing without changing the global configuration, pass your Foundry model with --model (for example, FW-GLM-5.2), not a Fireworks serverless short ID.


fireconnect vscode on \\

  --azure \\

  --base-url "$BASE_URL" \\

  --model FW-GLM-5.2

To disable or uninstall FireConnect:


# Disable FireConnect for VS Code.

fireconnect vscode off

# Uninstall FireConnect for VS Code.

fireconnect uninstall

🔐 BYOK in Depth

BYOK IN DEPTH

Bring your own key (BYOK) allows you to use Copilot with models of your choice: local or hosted by an external provider. GitHub Copilot supports BYOK at two levels:

Feature	Enterprise BYOK	Local BYOK
Who configures it	Enterprise / Org owner	Individual developer
Where keys live	Server-side (GitHub)	Client-side only
Copilot license needed?	Yes	No
Works offline / air-gapped?	❌ No	✅ Yes

Local BYOK works across multiple surfaces:

VS Code	JetBrains IDEs	Xcode	Copilot CLI	GitHub Copilot App	Copilot SDK
✅ GA	✅ Public preview	✅ Public preview	✅ Supported	✅ Supported	✅ Supported

BYOK to GH Copilot in VS Code and FireConnect

VS Code offers different ways to add language models:

Provider option	What it means
Built-in providers	The provider is already listed (Azure, Anthropic, Gemini, OpenAI, and others)
Extensions	A marketplace extension provides the model (e.g., AI Toolkit for local models)
Custom endpoint	You have a self-hosted or enterprise endpoint that speaks Chat Completions, Responses, or Messages API