In Oracle Cloud Infrastructure (OCI), "Shapes" are the blueprints that define the physical and virtual resources of your server. As of 2026, OCI has shifted toward a highly specialized lineup, specifically targeting AI, massive databases, and high-frequency computing.

Here is the current landscape of OCI compute shapes:

1. Standard Shapes (General Purpose)

These are the "workhorses" of OCI. They offer a balanced ratio of CPU, memory, and network resources. Most Standard shapes are Flexible, meaning you can drag a slider to pick your exact core and RAM count.

• AMD Series (E-Series):

  • E6 (Latest): Powered by 5th Gen AMD EPYC processors. It offers roughly double the performance-per-dollar compared to the previous generation.

  • E5: Based on 4th Gen AMD EPYC (Genoa), widely used for standard enterprise apps.

• Arm Series (A-Series):

  • A2 & A4 (Current): Powered by AmpereOne® processors. These are designed for high-density, cloud-native workloads and offer the lowest cost-per-core in the cloud.

  • A1: The original Arm shape, still available and famous for being part of the Always Free tier.

• Intel Series (X-Series):

  • Standard3: Based on 3rd Gen Intel Xeon (Ice Lake). Used primarily for workloads that require specific Intel instruction sets (like AVX-512).

2. Dense I/O Shapes (Storage Heavy)

These are designed for workloads that need extreme speed for local data access, such as massive NoSQL databases (Cassandra, MongoDB) or Big Data analytics (Hadoop).

• Key Feature: They include locally attached NVMe SSDs, which provide millions of IOPS with sub-millisecond latency.

• Current Models: Available in E5 (AMD) and X9 (Intel) generations.

3. GPU Shapes (AI & Graphics)

OCI has become a primary destination for AI companies due to its massive Superclusters of GPUs. These are almost exclusively rented as Bare Metal to ensure no virtualization overhead.

• NVIDIA Blackwell (B200 / GB200): The top-tier hardware for training trillion-parameter LLMs.

• NVIDIA Hopper (H200 / H100): The mainstream choice for AI training and large-scale inference.

• AMD Instinct (MI300X / MI355X): A high-memory bandwidth alternative (192GB+ VRAM) often used for high-performance AI inference at a competitive price point.

• L40S & A10: Smaller GPUs used for AI inference, 3D rendering, and video transcoding.

4. HPC & Optimized Shapes (High Frequency)

These shapes are built for scientific simulations (CFD, weather modeling) or financial modeling that requires raw single-core speed.

• HPC Shapes: Feature high-frequency processors (often 3.0GHz+ base clock) and RDMA Cluster Networking. This allows multiple servers to communicate at 100-3200 Gbps with microsecond latency, effectively acting as one giant supercomputer.

• Optimized Shapes: A "flexible" version of HPC hardware, allowing you to scale cores while maintaining a high memory-to-CPU ratio for memory-bound simulations.

Comparison Summary