What’s Nvidia’s 2024‑2025 AI Chip Roadmap? A Deep Dive into GPUs, CPUs, and Interconnects

Nvidia's AI Layout

Nvidia announced at its 2023 investor meeting a new GPU development blueprint that shortens the update cycle to one year. The plan foresees the H200 and B100 GPUs in 2024 and the X100 GPU in 2025, all built on a "One Architecture" unified design that supports training and inference on both data‑center and edge devices, across x86 and ARM platforms.

The roadmap emphasizes a tighter integration of training and inference functions, with a particular focus on inference workloads. Nvidia aims to serve ultra‑large data‑center training tasks as well as enterprise‑level edge computing, positioning its solutions for both massive cloud deployments and specialized on‑premise use cases.

Grace CPU and SuperChip Strategy

Nvidia’s Grace CPU will evolve in sync with its GPUs, forming next‑generation SuperChips that combine CPU and GPU capabilities. While GPU performance is expected to double roughly every year (≈2.5× growth), CPU evolution follows a slower two‑year Moore‑like cadence, reflecting cost sensitivity and different market dynamics.

Interconnect Evolution

Nvidia will continue to leverage NVLink‑C2C and NVSwitch in its future AI chip architectures. The GH200, GB200 and GX200 SuperChips will be built using NVLink‑C2C, and pairs of these chips can be linked back‑to‑back (e.g., GH200NVL, GB200NVL, GX200NVL) to create super‑node modules. These super‑nodes can be scaled with InfiniBand or Ethernet to form larger AI clusters.

Switch Chip Roadmap

The company maintains two open‑network tracks: InfiniBand for AI factories and Ethernet for AIGC cloud services. Expected milestones include a 800 Gbit/s (51.2 Tbit/s capacity) Spectrum‑4 switch in 2024 and a 1.6 Tbit/s (102.4 Tbit/s capacity) Spectrum‑5 switch in 2025, both based on 224 Gbit/s SerDes technology. No explicit plans for NVLink 5.0 or NVSwitch 4.0 were disclosed.

SmartNIC and DPU Development

SmartNICs (ConnectX‑8) and BlueField‑4 DPUs target an 800 Gbit/s rate to complement the upcoming 1.6 Tbit/s Quantum and Spectrum‑X chips. NVLink provides up to 900 GB/s (3.6 Tbps) bidirectional bandwidth, far exceeding traditional PCIe‑to‑Ethernet paths, which are roughly a 1:9 bandwidth ratio.

Competitive Landscape

Nvidia faces increasing pressure from Google, Meta, AMD, Microsoft, and Amazon, all advancing both hardware and software to challenge Nvidia’s dominance. In response, Nvidia pursues an aggressive, multi‑pronged strategy that includes annual GPU updates, HBM3E memory, PCIe 6.0/7.0, and advanced interconnects.

First‑Principles Analysis

The analysis deliberately excludes supply‑chain control tactics and unpredictable black‑swans (e.g., geopolitical conflicts) to focus on physical and technological constraints. It evaluates possible paths using conditional reasoning ("if A then X; if B then Y") for the next two to three years.

NVLink Evolution

Since its 2014 debut, NVLink has progressed through four generations: 20 G (1.0), 25 G (2.0), 50 G (3.0), and 100 G (4.0). The roadmap projects a 200 G NVLink 5.0 by 2024. Early generations targeted intra‑board and intra‑chassis communication, while later versions aim at inter‑device scaling, aligning more closely with Ethernet frequency points to reuse existing ecosystem components.

Acquisitions and Ecosystem Integration

Nvidia acquired Mellanox in 2020, gaining InfiniBand, Ethernet, SmartNIC, DPU, and LinkX interconnect technologies. This enables both a traditional network stack (InfiniBand/Ethernet) and a proprietary bus‑domain network (NVLink) for scaling GPU compute.

ARM Acquisition Attempt and Grace SuperChip

The attempted ARM acquisition in 2020 was halted in 2022, but Nvidia later released the Grace CPU SuperChip in March 2022, making it a company that offers CPU, GPU, and DPU products.

Industry Comparison

AMD focuses on CPU and GPU chiplets with Infinity Fabric, lacking a SuperChip concept, while Broadcom emphasizes network solutions (Jericho3‑AI+Ramon DDC, Tomahawk, Trident). Other players like Cerebras and Tesla Dojo pursue wafer‑scale custom hardware.

Overall, Nvidia’s strategy builds a comprehensive AI ecosystem across three pillars—system/network, hardware, and software—creating a deep technical moat that is difficult for competitors to replicate.