The NVIDIA GB10 Superchip and the NVIDIA GB300 are both powerful AI-focused processors, but they serve different purposes and have distinct memory bandwidth capabilities.
NVIDIA GB10 Superchip
The GB10 Superchip, used in devices like the NVIDIA DGX Spark and ASUS Ascent GX10, features a unified coherent memory system with 128 GB of 256-bit LPDDR5x memory. This configuration provides a memory bandwidth of 273 GB/s[1][4]. The GB10 utilizes NVIDIA NVLink-C2C interconnect technology, which offers a CPU+GPU-coherent memory model with five times the bandwidth of PCIe 5.0[1][7]. This architecture is optimized for compact, high-performance AI applications, supporting up to 200 billion parameter models with efficient data processing and real-time inferencing[4][7].
NVIDIA GB300
In contrast, the NVIDIA GB300 is designed for high-end AI computing and data center applications. It boasts a significantly higher memory capacity and bandwidth, featuring 288 GB of HBM3e memory with an impressive bandwidth of up to 8 TB/s[2][3][9]. This substantial increase in memory bandwidth is crucial for handling large datasets and complex AI models, enabling faster processing and reduced latency in real-time AI operations[9]. The GB300 also incorporates advanced networking capabilities, such as the ConnectX-8 NIC, which doubles the bandwidth compared to its predecessor, supporting larger batch sizes and extended sequence lengths[3][9].
Comparison
While the GB10 Superchip offers a robust memory bandwidth suitable for local AI development and smaller-scale AI models, the GB300 is designed for much larger-scale AI workloads and data center environments. The GB300's memory bandwidth is significantly higher, making it more suitable for applications requiring massive data processing and high-speed data transfer. In summary, the GB300 provides a much higher memory bandwidth compared to the GB10, reflecting its focus on large-scale AI computing and data center applications.
Citations:
[1] https://www.cnx-software.com/2025/03/19/nvidia-dgx-spark-a-desktop-ai-supercomputer-powered-by-nvidia-gb10-20-core-armv9-soc-with-1000-tops-of-ai-performance/
[2] https://siliconangle.com/2024/12/26/leaks-reveal-beefed-specifications-nvidias-next-gen-gb300-ai-server/
[3] https://longportapp.com/en/news/223389830
[4] https://meta-quantum.today/?p=3460
[5] https://www.nvidia.com/en-us/data-center/gb300-nvl72/
[6] https://www.theregister.com/AMP/2025/03/18/gtc_frame_nvidias_budget_blackwell/
[7] https://www.techpowerup.com/334249/asus-unveils-new-ascent-gx10-mini-pc-powered-nvidia-gb10-grace-blackwell-superchip
[8] https://www.techpowerup.com/330154/nvidia-gb300-blackwell-ultra-will-feature-288-gb-hbm3e-memory-1400-w-tdp
[9] https://drrobertcastellano.substack.com/p/nvidia-gb300-redefining-ai-computing
[10] https://semianalysis.com/2024/12/25/nvidias-christmas-present-gb300-b300-reasoning-inference-amazon-memory-supply-chain/