AMD Instinct MI440X OAM vs AMD Instinct MI455X OAM
Side-by-side specifications, performance, and rental pricing for datacenter AI workloads.
Instinct MI440X: CDNA 5, 2026 Instinct MI455X: CDNA 5, 2026
AMD Instinct MI440X OAM
Full specs →Architecture
CDNA 5
Year
2026
AMD Instinct MI455X OAM
Full specs →Architecture
CDNA 5
Year
2026
Memory
432 GB
Specifications
Instinct MI440X Instinct MI455X
Architecture
CDNA 5CDNA 5
Launch Year
20262026
Form Factor
OAMOAM
Memory
—432 GB
Memory Bandwidth
—23.3 TB/s
TDP
——
Process Node
——
Spec Instinct MI440X Instinct MI455X
Architecture CDNA 5CDNA 5
Launch Year 20262026
Form Factor OAMOAM
Memory —432 GB
Memory Bandwidth —23.3 TB/s
TDP ——
Process Node ——
Performance (TFLOPS)
Instinct MI440X Instinct MI455X
FP64
No verified data available No verified data available
FP32
No verified data available No verified data available
TF32
No verified data available No verified data available
BF16
No verified data available No verified data available
FP16
No verified data available No verified data available
FP8
No verified data available20,133 TFLOPS
sparse not published
FP6
No verified data available No verified data available
FP4
No verified data available40,265 TFLOPS
sparse not published
INT8
No verified data available No verified data available
Precision Instinct MI440X Instinct MI455X
FP64 No verified data available No verified data available
FP32 No verified data available No verified data available
TF32 No verified data available No verified data available
BF16 No verified data available No verified data available
FP16 No verified data available No verified data available
FP8 No verified data available20,133 TFLOPS
sparse not published
FP6 No verified data available No verified data available
FP4 No verified data available40,265 TFLOPS
sparse not published
INT8 No verified data available No verified data available
FLOPS by Precision
What actually differs
Both GPUs launched in 2026: the Instinct MI440X on CDNA 5 and the Instinct MI455X on CDNA 5.
For LLM training and inference, weight the FP8 and FP16 rows and memory capacity most heavily. For scientific and HPC workloads, the FP64 row is the one to read.
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