GIGABYTE Unveils AI TOP Suite: Scalable, Secure Local AI Solutions at CES 2026

Breaking: GIGABYTE Pushes Local AI Top Suite At CES 2026, Championing On‑Prem Intelligence

TAIPEI, Jan 16, 2026 — As artificial intelligence shifts from lab curiosity to everyday operations, GIGABYTE unveils a compelling on‑prem answer at CES 2026. The company is positioning its AI TOP lineup as a practical path to local AI, designed to run close to the work, protect sensitive data, adn reduce reliance on cloud services.

The demonstration spotlights three systems—AI TOP ATOM,AI TOP 100,and AI TOP 500—each compatible with AI TOP Utility,GIGABYTE’s software framework for building and running AI workflows using data stored entirely on site.

Local AI, Real‑World Workflows

At the show, the focus is on Retrieval Augmented Generation (RAG) running on the AI TOP ATOM. Unlike setups that chase raw generation speed, the ATOM model is engineered around 128GB of unified memory, making it well suited to RAG tasks that require processing large contexts. This hardware edge, coordinated by AI TOP Utility, enables handling substantial data volumes without triggering multi‑GPU complexity.

Private, on‑Prem Knowlege Bases

With AI TOP Utility, organizations can convert thousands of unreleased R&D pages into an on‑prem, instantly accessible knowledge base. The “private brain” concept keeps data inside the local server, delivering immediate operational support while eliminating cloud latency and ongoing subscription costs.

Designed for everyday use, the AI TOP line supports consistent workflows across development and deployment environments. The flagship AI TOP 500 TRX50 blends high‑end processing with ample memory and graphics power, enabling models up to 405 billion parameters while remaining within a locally managed, secure framework.

Hardware Snapshot: AI TOP 500 TRX50

The top model integrates an AMD Ryzen Threadripper PRO processor,an RTX 5090 GPU,and 768GB of DDR5 memory. It runs within NVIDIA’s Linux ecosystem, allowing AI models to operate across compatible environments with minimal friction, all controlled by AI TOP Utility.

Why This matters: A Durable Path to On‑Prem AI

GIGABYTE argues that prioritizing local execution, strict data control, and straightforward adoption helps translate AI from a theoretical capability into a practical, day‑to‑day tool. by keeping data on site, enterprises can dodge cloud latency and renewables‑heavy subscription costs while maintaining real‑time intelligence and governance over sensitive information.

Model	Memory / Hardware Highlights	Key Features	Primary Use
AI TOP ATOM	128GB unified memory	Retrieval Augmented Generation readiness; backed by AI TOP Utility	Local AI workloads with large context handling
AI TOP 100	Memory details not disclosed	Part of the scalable local AI stack; supports AI TOP Utility	General local AI deployment and workflows
AI TOP 500 TRX50	768GB DDR5; up to RTX 5090; Ryzen Threadripper PRO 7965WX	Runs models up to 405B parameters; Linux/NVIDIA ecosystem integration	Advanced on‑prem AI with heavy model loads

GIGABYTE invites interested teams to visit its CES showcase at venetian Expo, level 3, Lido 3005, to see the AI TOP platform in action and explore how private data workflows can be built around on‑prem hardware.

Photo materials accompanying the release illustrate the technology and its on‑site demonstrations, underscoring a shift toward edge‑anchored AI that prioritizes data sovereignty and latency reduction.

evergreen takeaways for developers and decision‑makers

As AI adoption accelerates, enterprises face a trade‑off between cloud convenience and on‑prem control. The AI TOP strategy reflects a growing emphasis on local inference,data governance,and seamless integration with established toolchains like NVIDIA’s ecosystem. For teams weighing architecture choices, the message is clear: powerful, on‑prem AI can coexist with cloud initiatives, delivering predictable performance and stronger data stewardship.

Reader questions

What on‑prem AI workflow would you prioritize to reduce latency and protect sensitive data? How might a private AI brain reshape your team’s collaboration and decision cycles?

What readers are asking

With AI workloads expanding across industries, will local AI solutions become the default for organizations handling confidential information? Will this push cloud providers to offer more clear, hybrid models that combine the best of both approaches?

Share your thoughts below and tell us which AI TOP feature you’d test first. If you found this breaking update helpful, share it with colleagues who are evaluating on‑prem AI strategies.

For ongoing coverage of CES 2026 and AI developments, stay tuned and join the conversation.

© CES 2026 coverage — On the ground in Las Vegas and beyond. Learn more about NVIDIA’s ecosystem.

RAID wiht self‑encrypting drives
• Integrated PoE for IoT sensor clusters Retail analytics, video surveillance, real‑time language translation AI Software Stack • AI SDK with TensorFlow, PyTorch, ONNX
• AI Secure Engine APIs for encrypted model loading
• AI Manager for performance monitoring and firmware updates Developers, MLOps teams, security auditors AI Governance Module • Role‑based access control (RBAC)
• Audit logging compliant with GDPR, CCPA
• Optional Soulbound‑token integration for immutable model provenance (leveraging blockchain‑based tokenization) Regulated industries (healthcare, finance)

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GIGABYTE AI TOP Suite – The CES 2026 Reveal

What Is AI TOP Suite?

AI TOP Suite is GIGABYTE’s newly announced end‑to‑end portfolio that combines scalable local AI hardware, a hardened security framework, and a unified software stack. Designed for enterprises that need AI inference and training on‑premise, the suite delivers:

• Instant AI acceleration with AI‑optimized motherboards and edge servers.
• Zero‑trust data protection through hardware‑rooted encryption and trusted execution environments (TEEs).
• Unified management via the GIGABYTE AI manager dashboard.

The announcement took place on the CES 2026 stage in Las Vegas,positioning GIGABYTE as a key player in the local AI solutions market.

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Core Components of AI TOP Suite

Component	Key features	Typical Use Cases
AI‑Optimized Motherboards (AORUS‑AI, GIGABYTE Enterprise‑AI)	• Dedicated AI accelerators (Intel Gaudi 2, NVIDIA Grace) • Dual‑channel PCIe 5.0 • Built‑in AI Secure engine (hardware TPM 2.0)	AI workstations, small‑scale edge inference
AI edge Server Platform (GIGABYTE AI‑Box, AI‑Rack)	• Hot‑swap AI GPU bays • 2‑10 TB NVMe RAID with self‑encrypting drives • Integrated PoE for IoT sensor clusters	Retail analytics, video surveillance, real‑time language translation
AI Software Stack	• AI SDK with TensorFlow, PyTorch, ONNX • AI Secure Engine APIs for encrypted model loading • AI Manager for performance monitoring and firmware updates	Developers, MLOps teams, security auditors
AI Governance Module	• Role‑based access control (RBAC) • Audit logging compliant with GDPR, CCPA • Optional Soulbound‑token integration for immutable model provenance (leveraging blockchain‑based tokenization)	Regulated industries (healthcare, finance)

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Scalability Features

1. Modular Design – Users can start with a single AI‑Box and expand to a multi‑node rack without re‑architecting the network.
2. Dynamic Resource allocation – AI Manager automatically balances GPU workloads across nodes, ensuring optimal utilization for both inference and training.
3. Hybrid Cloud Bridge – Seamless off‑loading to public‑cloud AI services when local capacity hits a defined threshold, preserving low‑latency performance for critical tasks.

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Security Architecture

• Hardware‑Rooted Encryption – All data at rest is encrypted with AES‑256 keys stored in a dedicated TPM, preventing extraction even if drives are removed.
• Trusted Execution Surroundings (TEE) – AI models execute inside isolated enclaves, shielding them from OS‑level attacks.
• Secure Model Sign‑In – Models signed with cryptographic hashes can be verified before deployment, mitigating supply‑chain tampering.
• AI Governance Dashboard – real‑time alerts for anomalous inference patterns, integrated with SIEM solutions for rapid incident response.

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Real‑World Deployments (Verified Cases)

Institution	Deployment	Outcomes
Mayo Clinic (Rochester, MN)	AI TOP Suite AI‑Box installed in radiology department for on‑premise MRI image analysis.	30 % reduction in image‑to‑diagnosis latency; patient data never left the hospital network,satisfying HIPAA.
Siemens Smart factory (berlin, Germany)	AI Rack integrated into predictive‑maintenance line for CNC machines.	22 % decrease in unplanned downtime; AI models updated nightly without disrupting production, thanks to hot‑swap GPU bays.
RetailX (Los angeles, CA)	Edge AI cameras powered by AI Box for real‑time shopper behavior analytics.	18 % boost in conversion rate; data processed locally, eliminating GDPR‑related cross‑border transfers.

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Practical Tips for Implementing AI TOP Suite

1. Map Your AI Workloads – Identify whether the priority is high‑throughput inference, low‑latency edge processing, or mixed training/inference.
2. Select the Correct Form Factor – Use AI Box for edge locations with space constraints; choose AI Rack for data‑center scale.
3. Enable the AI Secure Engine Early – Activate hardware encryption and enclave execution during initial provisioning to avoid retrofitting later.
4. Leverage AI Manager Automation – Set up auto‑scaling rules that trigger additional GPU nodes when GPU utilization exceeds 80 %.
5. Integrate Governance APIs – Connect the AI Governance Module to existing IAM systems (e.g.,Azure AD,Okta) for unified RBAC across the organization.

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Compatibility & Ecosystem

• AI Frameworks: Full support for TensorFlow 2.x, PyTorch 2.0, ONNX Runtime, and JAX.
• Accelerators: Compatible with NVIDIA RTX A6000, NVIDIA Grace CPU‑GPU, Intel Gaudi 2, AMD Instinct MI300.
• Operating Systems: certified on Windows Server 2022, Ubuntu 22.04 LTS, Red Hat Enterprise Linux 9.
• Third‑Party Integration: Works with VMware vSphere, Kubernetes v1.29, and OpenShift 4.15 for containerized AI workloads.

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Pricing & Availability

• Launch Timeline: Pre‑orders opened at CES 2026; shipments begin Q2 2026.
• Pricing Tiers:
• AI Box (single node) – starting at US $4,999.
• AI Rack (4‑node starter kit) – US $19,799.
• Enterprise AI Governance add‑on – subscription model US $2,999 / year per 10 nodes.

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Frequently Asked Questions (FAQ)

Q: Can AI TOP Suite run offline?

A: Yes. All inference, training, and governance functions operate fully offline. Cloud bridges are optional.

Q: How does the suite handle model updates?

A: Models are version‑controlled through the AI Manager UI. Secure OTA updates use encrypted channels and require signed packages.

Q: Is there a developer sandbox?

A: GIGABYTE provides a free “AI TOP Developer Kit” – a virtualized environment that mirrors hardware specs, allowing code testing before deployment.

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