AMD is gearing up for a significant challenge in the AI accelerator market with its upcoming Instinct MI400 and MI500 series, positioning itself to compete with NVIDIA’s current dominance.
Unveiling the AMD MI400 Series: Variants and Features for 2027
At the Financial Analyst Day 2025, AMD showcased its upcoming MI400 and MI500 series AI GPU accelerators, emphasizing their role in the company’s long-term AI strategy. This annual launch cycle is designed to fortify AMD’s presence in AI as NVIDIA continues to lead in this sector.

Set to debut next year, the MI400 series promises several advancements:
- Enhanced HBM4 Capacity & Bandwidth
- Broader AI Format Support with Increased Throughput
- Standardized Rack-Scale Networking (UALoE, UAL, UEC)
The MI400 series is touted to achieve 40 PFLOPS (FP4) and 20 PFLOPS (FP8), effectively doubling the computational throughput of the currently popular MI350 series.

Additionally, the MI400 series will leverage HBM4 memory technology, featuring a 50% increase in memory capacity from the previous 288 GB of HBM3e to a substantial 432 GB of HBM4. This upgrade results in an impressive memory bandwidth of 19.6 TB/s, significantly surpassing the MI350 series’s 8 TB/s. Each GPU in this series boasts a scale-out bandwidth of 300 GB/s, indicating a major leap forward for AMD’s next-generation Instinct lineup.

When positioned against NVIDIA’s Vera Rubin, AMD’s Instinct MI400 GPUs showcase notable advantages:
- 1.5x Memory Capacity compared to competition
- Equivalent Memory Bandwidth and FLOPs (FP4 / FP8)
- 1.5x Greater Scale-Out Bandwidth

The MI400 series consists of two main models: the MI455X, targeted at scalable AI Training & Inference workloads, and the MI430X, designed for HPC and Sovereign AI tasks, complete with hardware-based FP64 capabilities, hybrid computing (CPU+GPU), and retaining the same HBM4 memory as its counterpart.

Looking ahead to 2027, AMD is scheduled to introduce the Instinct MI500 series, continuing its annual product refresh cycle. This strategy aims to deliver rapid advancements in datacenter AI technology, aligning with NVIDIA’s approach of providing standard and “Ultra”versions. The MI500 series is expected to significantly enhance compute, memory, and interconnect capabilities, further increasing AMD’s competitive edge in the AI landscape.
Comparison of AMD Instinct AI Accelerators
| Accelerator Name | AMD Instinct MI500 | AMD Instinct MI400 | AMD Instinct MI350X | AMD Instinct MI325X | AMD Instinct MI300X | AMD Instinct MI250X |
|---|---|---|---|---|---|---|
| GPU Architecture | CDNA Next / UDNA | CDNA 5 | CDNA 4 | Aqua Vanjaram (CDNA 3) | Aqua Vanjaram (CDNA 3) | Aldebaran (CDNA 2) |
| GPU Process Node | TBD | TBD | 3nm | 5nm+6nm | 5nm+6nm | 6 nm |
| XCDs (Chiplets) | TBD | 8 (MCM) | 8 (MCM) | 8 (MCM) | 8 (MCM) | 2 (MCM; 1 Per Die) |
| GPU Cores | TBD | TBD | 16, 384 | 19, 456 | 19, 456 | 14, 080 |
| GPU Clock Speed (Max) | TBD | TBD | 2400 MHz | 2100 MHz | 2100 MHz | 1700 MHz |
| INT8 Compute | TBD | TBD | 5200 TOPS | 2614 TOPS | 2614 TOPS | 383 TOPs |
| FP6/FP4 Matrix | TBD | 40 PFLOPs | 20 PFLOPs | N/A | N/A | N/A |
| FP8 Matrix | TBD | 20 PFLOPs | 5 PFLOPs | 2.6 PFLOPs | 2.6 PFLOPs | N/A |
| FP16 Matrix | TBD | 10 PFLOPs | 2.5 PFLOPs | 1.3 PFLOPs | 1.3 PFLOPs | 383 TFLOPs |
| FP32 Vector | TBD | TBD | 157.3 TFLOPs | 163.4 TFLOPs | 163.4 TFLOPs | 95.7 TFLOPs |
| FP64 Vector | TBD | TBD | 78.6 TFLOPs | 81.7 TFLOPs | 81.7 TFLOPs | 47.9 TFLOPs |
| VRAM | TBD | 432GB HBM4 | 288 GB HBM3e | 256 GB HBM3e | 192GB HBM3 | 128 GB HBM2e |
| Infinity Cache | TBD | TBD | 256 MB | 256 MB | 256 MB | N/A |
| Memory Clock | TBD | 19.6 TB/s | 8.0 Gbps | 5.9 Gbps | 5.2 Gbps | 3.2 Gbps |
| Memory Bus | TBD | TBD | 8192-bit | 8192-bit | 8192-bit | 8192-bit |
| Memory Bandwidth | TBD | TBD | 8TB/s | 6.0 TB/s | 5.3 TB/s | 3.2 TB/s |
| Form Factor | TBD | TBD | OAM | OAM | OAM | OAM |
| Cooling | TBD | TBD | Passive / Liquid | Passive Cooling | Passive Cooling | Passive Cooling |
| TDP (Max) | TBD | TBD | 1400W (355X) | 1000W | 750W | 560W |
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