ecs.i2gne.16xlarge is a ecs.i2gne family (64 vCPUs, 256 GiB RAM, 7679 GB ssd storage) server offered by Alibaba Cloud with 64 vCPUs, 256 GiB of memory and 7.68 TB of storage. The pricing starts at 3.6 USD per hour.
A dedicated 64-core server featuring 7679 GB of local SSD storage and 20 Gbps network bandwidth for storage-intensive database workloads.
Storage & DatabaseGeneral Purpose
Alibaba Cloud ecs.i2gne.16xlarge is a storage-optimized server instance utilizing the KVM hypervisor and x86_64 architecture. It is equipped with 64 dedicated physical cores on an Intel Xeon 8163 processor running at 2.5 GHz, alongside 256 GB of RAM, establishing a 4.0 GB memory-to-core ratio. The instance features a substantial local storage allocation of 7679 GB of SSD capacity and a baseline network bandwidth of 20 Gbps. With no GPU accelerators present, the hardware configuration is tailored for high-capacity local data processing. The dedicated CPU allocation with a single thread per core ensures predictable compute performance. This server is suited for database hosting, data warehousing, and storage-intensive enterprise workloads requiring large local storage volumes and consistent processing power.
Economics
Average Price per Region
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Workload Profiles
Precomputed compound score for Cache Intensive workloads. A weighted average (geometric mean) of benchmark scores compared to their medians: score = ∏ (x_i / m_i)^(w_i / Σw). The score of 1.0 represents a synthetic baseline server with the median performance of each component benchmark; 0.5 means roughly half the performance; and 2.0 means twice the performance of that reference profile. Component weights: 50% Redis RPS (pipeline=1, SET), 20% Redis RPS (pipeline=16, SET), 10% PassMark Memory Mark (composite), 10% Memory bandwidth (read, 16 MB ~ L3), 10% PassMark single-thread CPU. Rationale for component selection: In-memory key-value store workload, mixing direct Redis performance metrics with memory speed and latency benchmarks, and single-core CPU performance profiles.
Precomputed compound score for CI/CD Build workloads. A weighted average (geometric mean) of benchmark scores compared to their medians: score = ∏ (x_i / m_i)^(w_i / Σw). The score of 1.0 represents a synthetic baseline server with the median performance of each component benchmark; 0.5 means roughly half the performance; and 2.0 means twice the performance of that reference profile. Component weights: 50% Geekbench Clang compilation (multi-core), 10% Geekbench Clang compilation (single-core), 20% stress-ng div16 best-N cores, 5% PassMark integer math, 5% PassMark compression, 5% Brotli compression (multi-core, level 0), 5% PassMark string sorting. Rationale for component selection: Build performance is mainly driven by multi-core compilation throughput, but also bundles single-core compilation speed and general CPU performance, multi-core compression and text/scripting processing.
Precomputed compound score for Compute Heavy Applications workloads. A weighted average (geometric mean) of benchmark scores compared to their medians: score = ∏ (x_i / m_i)^(w_i / Σw). The score of 1.0 represents a synthetic baseline server with the median performance of each component benchmark; 0.5 means roughly half the performance; and 2.0 means twice the performance of that reference profile. Component weights: 15% stress-ng div16 best-N cores, 10% stress-ng div16 single core, 20% PassMark CPU Mark (composite), 10% Memory bandwidth (read, 64 MB), 15% PassMark floating point, 15% PassMark AVX/SSE/FMA (SIMD), 10% PassMark integer math, 5% PassMark physics simulation. Rationale for component selection: Number-crunching workload augmenting raw CPU performance stressing, general CPU performance benchmarks, memory bandwidth, and pure math computation speed like floating point, integer, SIMD (AVX/SSE/FMA) operations.
Precomputed compound score for Data Analysis workloads. A weighted average (geometric mean) of benchmark scores compared to their medians: score = ∏ (x_i / m_i)^(w_i / Σw). The score of 1.0 represents a synthetic baseline server with the median performance of each component benchmark; 0.5 means roughly half the performance; and 2.0 means twice the performance of that reference profile. Component weights: 70% PassMark CPU Mark (composite), 10% Gzip compression (single-core, level 5), 10% Memory bandwidth (read, 64 MB), 10% PassMark Memory Mark (composite). Rationale for component selection: Data analysis and ETL workloads are memory-bandwidth-bound and CPU-throughput-driven. The profile combines general CPU performance and memory bandwidth/latency as the primary drivers, supplemented by single-core compression speed as a proxy for serialisation-heavy ETL tasks.
Precomputed compound score for LLM Inference workloads. A weighted average (geometric mean) of benchmark scores compared to their medians: score = ∏ (x_i / m_i)^(w_i / Σw). The score of 1.0 represents a synthetic baseline server with the median performance of each component benchmark; 0.5 means roughly half the performance; and 2.0 means twice the performance of that reference profile. Component weights: 15% LLM text generation (SmolLM-135M, 128 tok), 15% LLM prompt processing (SmolLM-135M, 512 tok), 15% LLM text generation (Llama 7B, 128 tok), 15% LLM prompt processing (Llama 7B, 512 tok), 15% LLM text generation (Llama-3.3 70B, 128 tok), 15% LLM prompt processing (Llama-3.3 70B, 512 tok), 5% Memory bandwidth (read, 256 MB), 2% PassMark AVX/SSE/FMA (SIMD), 2% PassMark floating point. Rationale for component selection: VRAM and memory-bandwidth-bound LLM inference workload, using direct LLM speed benchmarks at three model sizes, and supplementing with raw memory bandwidth and SIMD performance benchmarks.
Precomputed compound score for Web Server workloads. A weighted average (geometric mean) of benchmark scores compared to their medians: score = ∏ (x_i / m_i)^(w_i / Σw). The score of 1.0 represents a synthetic baseline server with the median performance of each component benchmark; 0.5 means roughly half the performance; and 2.0 means twice the performance of that reference profile. Component weights: 30% Static web RPS (1 KiB, 8 conn/vCPU), 20% Static web RPS (64 KiB, 8 conn/vCPU), 20% Static web throughput (256 KiB, 8 conn/vCPU), 20% OpenSSL AES-256-CBC (16 kB blocks), 5% Gzip compression (multi-core, level 5), 5% PassMark string sorting. Rationale for component selection: Primary workloads drivers are single-process static HTTP serving speed and throughput, text processing, TLS termination, and asset compression.
ecs.i2gne.16xlarge is a ecs.i2gne family (64 vCPUs, 256 GiB RAM, 7679 GB ssd storage) server offered by Alibaba Cloud with 64 vCPUs, 256 GiB of memory and 7.68 TB of storage. The pricing starts at 3.6 USD per hour.
The ecs.i2gne.16xlarge server is equipped with 64 logical CPU cores on 64 Intel Xeon 8163 physical CPU cores running at max. 2.5 Ghz, 256 GiB of memory, 7.68 TB of ssd storage, and no GPU. Additional block storage can be attached as needed.
The pricing for ecs.i2gne.16xlarge servers starts at 3.6 USD per hour, but the actual price depends on the selected region, zone and server allocation method (e.g. on-demand versus spot pricing options): currently, we track the prices in 13 regions and zones every 5 minutes, and the maximum price stands at 5.1072 USD.
The ecs.i2gne.16xlarge server is offered by Alibaba Cloud, founded in 2009, headquartered in Zhejiang, China. For more information, visit the Alibaba Cloud homepage.
The ecs.i2gne.16xlarge server is available in 13 availability zones of the following 7 regions: Hohhot (CN), Beijing (CN), Guangzhou (CN), Hangzhou (CN), Shanghai (CN), Hong Kong (HK), Riyadh (SA).
