Return of the SLI: Lenovo's new workstation PC supports up to two RTX 5060 Ti GPUs for AI inference - but I'm more interested in the secretive 1TB AI Fusion Card

• Lenovo ThinkCentre X Tower’s 1TB AI Fusion Card enables local post-training for massive models
• Dual RTX 5060 Ti cards provide 32GB VRAM for extended context lengths
• Intel Core Ultra 9 CPU and 256GB memory prevent preprocessing bottlenecks

At CES 2026, Lenovo unveiled the ThinkCentre X Tower, its newest workstation-class desktop designed for AI inference and data-intensive computing.

The device supports either a single high-end Nvidia GeForce RTX 5090 with 32GB of memory or a dual RTX 5060 Ti configuration.

It marks a return to an SLI-style multi-GPU approach, a setup that became viable around 2010 when driver support improved and dual-card scaling reached 60 to 80% in real applications.

Dual GPUs return for modern inference workloads

Rather than focusing on raw frame rates, the dual RTX 5060 Ti setup emphasizes memory capacity by combining 32GB of GDDR7 VRAM across both cards.

This capacity allows large language models to run locally with extended context lengths that exceed what many single-card systems can sustain.

However, configuring dual RTX 5060 Ti cards requires careful system planning, including sufficient PCIe slots, strong airflow, and a capable power supply.

The ThinkCentre X Tower uses an Intel Core Ultra 9 processor and supports up to 4x 64GB DDR5 6400 UDIMM memory.

This design prevents CPU-side preprocessing and memory-intensive tasks from becoming immediate bottlenecks during inference operations.

Expansion options remain extensive, with multiple PCIe slots, up to 3x 2TB M.2 PCIe 2280 SSD storage bays, and legacy connectivity options.

The system also includes 1x Thunderbolt 4, 1x USB-C, 6x USB-A, 2x Ethernet, 1x HDMI 2.1, 1x DisplayPort 1.4a, audio in and out, and optional PS/2 or COM ports.

In practical tests, the dual-GPU configuration pushes Mixture-of-Experts models such as Qwen3-MoE 30B beyond 100K tokens.

It sustains around 131K tokens reliably, while dense models such as Qwen3 32B reach up to 45K tokens.

FlashAttention improves responsiveness and reduces swapping during large-context inference tasks.

Optimized runtimes such as ExLlamaV3 and TabbyAPI help close performance gaps, making the system feel more responsive even at 32K to 44K context lengths.

However, stability under sustained inference loads stands out as the primary advantage rather than outright throughput leadership.

Token generation performance also remains constrained by bandwidth limitations, particularly as context sizes expand.

Beyond GPU selection, Lenovo includes support for a 1TB AI Fusion Card, which remains one of the less clearly defined elements of the system.

This component enables local post-training and fine-tuning for models reaching up to 70 billion parameters.

Cooling for these workloads relies on a biomimetic fan design within a 34-liter chassis, which supports high airflow for dual GPU configurations.

Lenovo also bundles support for a Sensor Hub assistant that integrates cameras, microphones, radar, and environmental sensors.

The system processes data locally to adjust performance characteristics, privacy behavior, and power efficiency in real time.

Although such adaptive systems promise efficiency gains, their real-world value will likely depend on software maturity and user control transparency.

Security features include DTPM 2.0, ThinkShield, a Kensington Security Slot, an optional chassis intrusion switch, E-lock, and a Smart cable lock.

At over 20kg, the ThinkCentre X Tower prioritizes modularity and airflow over physical convenience.

The dual RTX 5060 Ti setup is most compelling for users who need large context windows and model flexibility.

The device starts at $1,500 and will be available in March 2026, while the Sensor Hub costs an additional $99 and will become available in June 2026.

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