Silicon Triangle
AWS Graviton4 Flagship Comparison: C8g vs M8g vs R8g
Next-gen Graviton4 ARM Neoverse V2 architecture across compute, memory, and general tiers
AWS Graviton4 delivers up to 30% better compute performance, 50% more cores, and 75% more memory bandwidth than Graviton3. Compare the three flagship 8th-generation families side by side.
1. Architectural & Silicon Specs Head-to-Head
Comparing underlying processor microarchitectures, memory ratios, and Nitro generation features using representative xlarge sizing.
c8gARM64 (Graviton)
C8G Compute Optimized
ProcessorAWS Graviton4 Processor
Clock Speed2.7 GHz
RAM / vCPU2.0 GiB/vCPU
Max Network50 Gbps
Max EBS IOPS240,000
AWS NitroSupported
Min Rate (c8g.xlarge)$0.1080/hr
Monthly Est.$78.81/mo
Cost per vCPU$0.0270/hr
Cost per GiB RAM$0.0135/hr
CoreMark Benchmark125,039
CoreMark / $1,158,197
Price IndexLowest Cost
Save 35% vs most expensive
Compute / $ Value100% (Leader)
m8gARM64 (Graviton)
M8G General Purpose
ProcessorAWS Graviton4 Processor
Clock Speed2.7 GHz
RAM / vCPU4.0 GiB/vCPU
Max Network50 Gbps
Max EBS IOPS240,000
AWS NitroSupported
Min Rate (m8g.xlarge)$0.1283/hr
Monthly Est.$93.67/mo
Cost per vCPU$0.0321/hr
Cost per GiB RAM$0.0080/hr
CoreMark Benchmark124,679
CoreMark / $971,626
Price Index78% of highest
Save 22% vs most expensive
Compute / $ Value84% of leader
r8gARM64 (Graviton)
R8G Memory Optimized
ProcessorAWS Graviton4 Processor
Clock Speed2.7 GHz
RAM / vCPU8.0 GiB/vCPU
Max Network50 Gbps
Max EBS IOPS240,000
AWS NitroSupported
Min Rate (r8g.xlarge)$0.1652/hr
Monthly Est.$120.57/mo
Cost per vCPU$0.0413/hr
Cost per GiB RAM$0.0052/hr
CoreMark Benchmark122,100
CoreMark / $739,283
Price Index100% of highest
Compute / $ Value64% of leader
2. Side-by-Side Sizing & Pricing Matrix
Direct price and benchmark comparison across matching instance tiers in the lowest-cost region. Lowest hourly cost in each row is highlighted in green.
| Size Tier | vCPU | Memory | c8gLinux Rate | m8gLinux Rate | r8gLinux Rate |
|---|---|---|---|---|---|
| .medium | 1 | 2 GB | |||
| .large | 2 | 4 GB | |||
| .xlarge | 4 | 8 GB | |||
| .2xlarge | 8 | 16 GB | |||
| .4xlarge | 16 | 32 GB | |||
| .8xlarge | 32 | 64 GB | |||
| .12xlarge | 48 | 96 GB | |||
| .16xlarge | 64 | 128 GB | |||
| .24xlarge | 96 | 192 GB | |||
| .48xlarge | 192 | 384 GB |
3. Workload Decision Framework
Clear, actionable rules on when each family wins based on workload profile, runtime language, and licensing boundaries.
Recommended:C8g (Compute)
When: High-density microservices, API gateways, and web application servers
Why: 2:1 RAM ratio maximizes CPU allocation per dollar with cutting-edge Neoverse V2 cores.
Recommended:M8g (General)
When: General enterprise workloads and Kubernetes worker nodes
Why: Balanced 4:1 RAM ratio prevents memory pressure during sudden concurrency spikes.
Recommended:R8g (Memory)
When: In-memory caches, distributed databases, and high-RAM analytics
Why: 8:1 RAM ratio with high-bandwidth DDR5 memory channels for data-intensive processing.
5. Related Architecture Comparisons
Explore adjacent generational comparisons and silicon trade-offs.