OEM Bundling Framework — Pre-Configuration for Hardware SKUs

Date: 2026-04-01 Status: Planning Target Milestone: v0.24.0 Priority: P1 — drives OEM adoption of GAIA on Ryzen AI devices Related Issues:

#648 — OEM bundling framework: pre-configuration for hardware SKUs

#649 — Cost savings telemetry: show users what they save by running locally

#644 — Model Manager UI: download, switch, and update models from the desktop app

#615 — App Store and Distribution Channel Packaging

Related Plans:

desktop-installer — NSIS desktop installer + bundled Lemonade MSI

agent-hub — Agent registry and marketplace

Agent UI — Phases A-D overview

1. Overview

AMD’s Ryzen AI 400-series is shipping across six major OEM partners: Acer, ASUS, Dell, HP, GIGABYTE, and Lenovo. Each partner ships devices with different memory configurations, NPU capabilities, and target audiences. The OEM bundling framework gives these partners a standardized way to pre-configure GAIA so that end users experience zero-touch deployment: plug in the device, and a private AI agent works immediately with no setup required. The first showcase device is the AMD Agent Computer (Halo Box), powered by Ryzen AI MAX+ 395 with 128GB unified memory.

2. OEM Configuration Manifest

Each OEM provides a YAML manifest placed at a well-known path during factory image creation. GAIA checks for this manifest before running its standard first-boot flow. Invalid manifests fall back to the standard gaia init flow with a warning. Required fields: schema_version, oem.name, hardware.sku, models.default.

# oem-config.yaml -- OEM Bundling Manifest for GAIA
schema_version: "1.0"

oem:
  name: "ASUS"
  display_name: "ASUS AI Suite"
  support_url: "https://support.asus.com/ai"

hardware:
  sku: "ASUS-ProArt-PX13-HX370"
  processor: "AMD Ryzen AI 9 HX 370"
  npu_tops: 50
  gpu_compute_units: 12
  ram_gb: 32

models:
  default: "Qwen3.5-35B-A3B-GGUF"
  preinstalled:
    - id: "Qwen3-0.6B-GGUF"
      size_gb: 0.4
      purpose: "lightweight-chat"
    - id: "Qwen3.5-35B-A3B-GGUF"
      size_gb: 18.0
      purpose: "agent-reasoning"
    - id: "nomic-embed-text-v1.5-GGUF"
      size_gb: 0.3
      purpose: "rag-embedding"

skills:
  bundle: "consumer"    # consumer | developer | enterprise | creative
  enabled: ["chat", "rag", "talk", "summarize"]

settings:
  temperature: 0.7
  ctx_size: 32768
  first_run:
    skip_model_download: true
    skip_hardware_detection: true

3. Hardware Profiles

The framework maps hardware SKUs to model recommendations. OEMs select from predefined profiles or define custom ones in their manifest.

Profile Tier	Representative SKU	NPU TOPS	GPU CUs	RAM	Max Model Size	Recommended Default Model
Halo Max+	Ryzen AI MAX+ 395 (Agent Computer)	50	40	128 GB	~200B (FP4)	Qwen3.5-35B
Halo	Ryzen AI MAX 390	50	32	64 GB	~70B (FP4)	Qwen3.5-35B
High	Ryzen AI 9 HX 370	50	12	32 GB	~30B (Q4)	Qwen3.5-35B
Mid	Ryzen AI 7 340	39	8	16 GB	~7B (Q4)	Qwen3-8B-GGUF
Entry	Ryzen AI 5 320	16	4	16 GB	~4B (Q4)	Qwen3-4B-Instruct-GGUF

GAIA validates that a model fits the hardware at boot time. If the default model exceeds available memory (RAM minus ~4 GB OS overhead, with 15% model overhead for KV cache), GAIA falls back to the next smaller preinstalled model.

4. Pre-Installed Model Packages

OEMs bundle models onto the factory image or a companion USB drive. Three predefined tiers cover common deployment scenarios.

Tier	Models Included	Total Disk	Target Audience
Minimal	Qwen3-0.6B-GGUF	~400 MB	Entry-level devices, demo units
Standard	Qwen3-0.6B + Qwen3.5-35B + nomic-embed-text-v1.5	~19 GB	Consumer laptops (32+ GB RAM)
Full	Standard + Qwen3-VL-4B + Qwen3-8B	~25 GB	Developer and Halo-class devices

Pre-installed models are placed at C:\AMD\GAIA\models\ and symlinked into the user’s ~/.gaia/models/ directory on first boot.

5. OEM Skill Bundles

Skill bundles define which GAIA capabilities are enabled out of the box. OEMs pick a predefined bundle (consumer, developer, enterprise, creative) or define a custom list in the manifest. Skills not in the active bundle are hidden from the UI but remain installed — users can enable additional skills from the Model Manager UI (#644) at any time.

6. Distribution Channels

Channel	Package Format	Auto-Update	Target
Windows Store	MSIX	Via Store	Consumer retail
Pre-installed image	Embedded in OEM Windows image	Via GAIA update channel	Factory install
USB provisioning	ZIP + PowerShell bootstrap	Manual / `gaia update`	IT deployment
Enterprise MDM	MSI + Group Policy template	Via MDM policy	Fleet management
winget	winget manifest	Via winget upgrade	Developer self-install

7. Cost Savings Telemetry

A key benefit of local AI is cost savings versus cloud APIs. The telemetry module (#649) tracks tokens generated and processed locally, then calculates equivalent cloud API costs using published pricing (OpenAI, Anthropic, Google). All data is stored locally in SQLite — nothing leaves the device unless the user explicitly opts into anonymous aggregate reporting. The Agent UI displays a savings summary card showing monthly and lifetime savings.

8. Phased Rollout

Phase 1 (v0.24.0): Ship the Agent Computer (Halo Box) with a production-ready reference OEM config, manifest schema v1.0, bootstrap loader in gaia init, cost savings telemetry v1, and Model Manager UI v1.
Phase 2 (v0.25.0): Provide OEM partners with a toolkit — gaia oem validate and gaia oem preview CLI commands, OEM integration guide, model packaging tools, and an automated test suite for manifest loading.
Phase 3 (v0.26.0+): Ship GAIA on all six OEM partner devices through standard distribution channels (Microsoft Store, MDM, winget), with enterprise fleet management tooling and a partner certification program.

9. GitHub Issue Cross-References

Issue	Title	Relevance
#648	OEM bundling framework	Primary issue — this plan is the design document
#649	Cost savings telemetry	Savings calculator and dashboard
#644	Model Manager UI	Hardware-aware model recommendations
#615	App Store and Distribution Channel Packaging	MSIX, winget, Store distribution
#597	Setup wizard	First-boot flow that OEM manifest can skip or customize
#612	Agent registry	Skill bundles map to registered agents
#643	System tray	OEM branding in tray icon and tooltip
#634	Always-on agent (heartbeat)	Enterprise fleet health monitoring
#474	MCP auto-install	Enterprise MCP server provisioning via manifest

What's Next

Agent UI

Ecosystem

Infrastructure

Agents

OEM Bundling

OEM Bundling Framework — Pre-Configuration for Hardware SKUs

1. Overview

2. OEM Configuration Manifest

3. Hardware Profiles

4. Pre-Installed Model Packages

5. OEM Skill Bundles

6. Distribution Channels

7. Cost Savings Telemetry

8. Phased Rollout

9. GitHub Issue Cross-References

​OEM Bundling Framework — Pre-Configuration for Hardware SKUs

​1. Overview

​2. OEM Configuration Manifest

​3. Hardware Profiles

​4. Pre-Installed Model Packages

​5. OEM Skill Bundles

​6. Distribution Channels

​7. Cost Savings Telemetry

​8. Phased Rollout

​9. GitHub Issue Cross-References

OEM Bundling Framework — Pre-Configuration for Hardware SKUs

1. Overview

2. OEM Configuration Manifest

3. Hardware Profiles

4. Pre-Installed Model Packages

5. OEM Skill Bundles

6. Distribution Channels

7. Cost Savings Telemetry

8. Phased Rollout

9. GitHub Issue Cross-References