Acer Veriton VGN100-UD11 — DGX Spark AI Workstation (NVIDIA GB10 Grace Blackwell)
$6,499.00
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Acer Veriton VGN100-UD11 — DGX Spark AI Workstation (NVIDIA GB10 Grace Blackwell)
$6,499.00
The Acer Veriton VGN100-UD11 (marketed in North America as the Veriton GN100) is Acer’s entry into the NVIDIA GB10 Grace Blackwell “personal AI supercomputer” category, the same platform underpinning NVIDIA’s own DGX Spark. It packs that platform into a workstation weighing under three pounds, with Acer’s own management software on top. It suits ML engineers and small AI teams who want DGX Spark-class local compute with Acer’s build quality, monitoring tools and support channel behind it.
Who it's for
- ML engineers running and quantizing models in the 70B–200B parameter class on their own desk
- Small AI teams that want live visibility into GPU temperature, memory pressure and inference throughput
- Developers who want to move work to a DGX Spark, a DGX cluster or DGX Cloud without modification
Key features
- NVIDIA GB10 Grace Blackwell Superchip: a 20-core Arm CPU (10x Cortex-X925 performance cores + 10x Cortex-A725 efficiency cores) fused to an integrated Blackwell GB20B GPU with 5th Gen Tensor Cores and 4th Gen RT Cores, rated for up to 1 petaFLOP of FP4 AI performance.
- 128GB unified LPDDR5x memory at 273GB/s: coherent memory shared between CPU and GPU (8533MT/s effective), so large models load and run without the VRAM ceiling of discrete-GPU workstations.
- Up to 4TB self-encrypting NVMe SSD: the top configuration ships with a 4TB Gen5-class NVMe drive; a lower-storage SKU is also available.
- ConnectX-7 Smart NIC + 10GbE: dual 200Gb/s QSFP ports for clustering multiple units to pool memory, plus a dedicated 10 Gigabit Ethernet RJ-45 port for everyday networking.
- Acer Sense Pro management software: a dashboard layered on top of NVIDIA DGX OS with real-time CPU, GPU, memory and thermal monitoring, hardware tuning, inference benchmarking (tokens-per-second and time-to-first-token charts) and self-diagnostics.
- Full NVIDIA DGX OS + AI stack: ships on Ubuntu 24.04 LTS for Arm with NVIDIA DGX OS, PyTorch, Jupyter and Ollama pre-installed, plus NVIDIA Sync support for remote management over the network.
- Portable footprint: 5.9 x 5.9 x 2 inches and roughly 1.2kg (2.65 lbs), powered from a 240W external adapter, with 4x USB-C ports (3x USB-C 3.2 Gen2x2 at 20Gbps carrying DisplayPort 2.1, plus 1x USB-C PD-in) and HDMI 2.1 for multi-monitor visualization.
- Wireless and physical security: Wi-Fi 7, Bluetooth 5.4 and a Kensington lock slot for units deployed outside a locked server room.
Specifications
| Spec | Detail |
|---|---|
| Model | Veriton VGN100-UD11 (Veriton GN100 AI Mini Workstation) |
| Superchip | NVIDIA GB10 Grace Blackwell |
| CPU | 20-core Arm (10x Cortex-X925 + 10x Cortex-A725) |
| GPU | NVIDIA Blackwell GB20B, 5th Gen Tensor Cores, 4th Gen RT Cores |
| AI Performance | Up to 1 petaFLOP (FP4, with sparsity) |
| Memory | 128GB LPDDR5x unified memory, 8533MT/s, 273GB/s bandwidth |
| Storage | Up to 4TB self-encrypting NVMe SSD (lower-capacity SKUs available) |
| Networking | NVIDIA ConnectX-7 Smart NIC (dual 200Gb/s QSFP), 10 Gigabit Ethernet (RJ-45) |
| Wireless | Wi-Fi 7, Bluetooth 5.4 |
| Ports | 3x USB-C 3.2 Gen2x2 (20Gbps) with DisplayPort 2.1, 1x USB-C PD-in, HDMI 2.1 |
| Security | Self-encrypting SSD, Kensington lock slot |
| Software | NVIDIA DGX OS (Ubuntu 24.04 LTS Arm), Acer Sense Pro dashboard, NVIDIA Sync, PyTorch, Jupyter, Ollama pre-installed |
| Power Supply | 240W external adapter |
| Dimensions | 5.9 x 5.9 x 2 inches (150 x 150 x 50.5mm) |
| Weight | Approx. 1.2kg (2.65 lbs) |
| Clustering | Multi-unit clustering via ConnectX-7 for pooled memory on larger model classes |
Good to know
- The 1 petaFLOP figure is a peak FP4-with-sparsity number. Real dense-precision throughput on a given model will be lower.
- This is a fine-tuning, quantization and inference machine, not a from-scratch foundation-model trainer. That workload still belongs on a cluster.
- Acer’s original launch materials cited two linked units for models up to roughly 405B parameters. Later materials reference larger multi-unit clusters for bigger model classes.
- It runs the identical NVIDIA DGX OS and CUDA stack as other GB10-class devices.
The silicon, memory design and DGX OS stack are the same across every GB10 system, so choose this one for Acer’s management tooling and its established enterprise support and warranty structure rather than for raw performance.