On January 5, 2026, on the opening day of CES 2026 (Consumer Electronics Show), AMD Chair and CEO Dr. Lisa Su unveiled in her keynote: the Instinct MI400 series AI accelerators.
The most eye-catching is MI455X — AMD's most powerful AI accelerator ever, using a 2nm + 3nm hybrid process, 432GB HBM4, with FP4 compute up to 40 PFLOPS (20 PFLOPS FP8).
Key highlights
- MI455X: FP4 40 PFLOPS, FP8 20 PFLOPS, 10× over MI355X
- MI450: cost-performance version, FP4 28 PFLOPS, 288GB HBM4
- Process upgrade: world's first AI chip with 2nm + 3nm hybrid process (GCD on 2nm, MCD on 3nm)
- Memory upgrade: from MI350X's 288GB HBM3e to 432GB HBM4 (MI455X)
- Bandwidth upgrade: from MI350X's 8 TB/s to 19.6 TB/s (2.45×)
- Architecture upgrade: from CDNA 4 to CDNA 5
- Mass production: MI455X Q4 2026, MI450 Q3 2026
Full MI400 series specs
📌 Important correction (2026-06-16): After official spec verification, MI455X memory is 432GB HBM4 (not the earlier reported 288GB), and FP4 compute is 40 PFLOPS. Corrected herein.
| Model | Positioning | Memory | FP4 compute | FP8 compute | TDP (est.) |
|---|
| MI455X | Flagship training+inference | 432GB HBM4 | 40 PFLOPS | 20 PFLOPS | ~1,000W |
| MI450 | Cost-performance training | 288GB HBM4 | 28 PFLOPS | 14 PFLOPS | ~800W |
| MI440X | Enterprise inference | 216GB HBM4 | 25 PFLOPS | 12.5 PFLOPS | ~600W |
| MI430X | HPC / scientific computing | 192GB HBM4 | 20 PFLOPS | 10 PFLOPS | ~500W |
| MI400X | General / edge inference | 128GB HBM4 | 12 PFLOPS | 6 PFLOPS | ~400W |
Key upgrades (vs MI350 series):
- Memory: HBM3e → HBM4, capacity +50% (432GB vs 288GB)
- Bandwidth: 19.6 TB/s (vs MI350's 8 TB/s, +2.45×)
- Compute: FP4 40 PFLOPS (vs MI355X's 20 PFLOPS, +2×)
- Process: 2nm + 3nm hybrid (GCD on 2nm, MCD on 3nm)
- Architecture: CDNA 5 (vs MI350's CDNA 4)
| Metric | MI355X (2025) | MI455X (2026) | Improvement |
|---|
| FP4 compute | 20 PFLOPS | 40 PFLOPS | 2× |
| FP8 compute | 10 PFLOPS | 20 PFLOPS | 2× |
| Memory capacity | 288GB HBM3e | 432GB HBM4 | 1.5× |
| Memory bandwidth | 8 TB/s | 19.6 TB/s | 2.45× |
| Process | TSMC 3nm | 2nm + 3nm hybrid | New gen |
| Architecture | CDNA 4 | CDNA 5 | New gen |
| TDP | 800-1000W | ~1,000W | Flat |
Lisa Su at CES 2026:
"Four years ago, MI250's AI performance was X. Today, MI455X's performance is 1000× that. That's the pace of AI chip progress."
CDNA 5 architecture in detail
The MI400 series adopts the CDNA 5 architecture (MI355X uses CDNA 4):
Key upgrades
- Matrix Core upgrade: FP8/INT8/FP16 support, sparsity acceleration
- HBM4 controller: 12-layer HBM4 (vs HBM3e's 8 layers)
- Infinity Fabric 4.0: 50% higher die-to-die / die-to-GPU bandwidth
- Native sparsity support: MoE Expert-Parallel optimization
- Long-context optimization: 1M+ token KV Cache acceleration
vs. NVIDIA Blackwell / Rubin
| Metric | AMD MI455X | NVIDIA B200 | NVIDIA Rubin R200 (2026 Q4) |
|---|
| FP4 compute | 40 PFLOPS | 20 PFLOPS (45 sparse) | ~40 PFLOPS (est.) |
| FP8 compute | 20 PFLOPS | 10 PFLOPS (22.5 sparse) | ~20 PFLOPS (est.) |
| Memory | 432GB HBM4 | 192GB HBM3e | 288GB HBM4 |
| Memory bandwidth | 19.6 TB/s | 8 TB/s | 13 TB/s |
| TDP | ~1,000W | 700-1000W | ~1,000W |
| Process | 2nm + 3nm hybrid | TSMC 4np | TSMC 3nm |
| Mass production | 2026 Q4 | 2024 Q4 | 2026 Q4 |
| Software ecosystem | ROCm | CUDA | CUDA |
| Strength | Memory capacity, open ecosystem | Most mature ecosystem | Next-gen architecture |
| Weakness | Software ecosystem gap | Smaller memory | Not yet launched |
Conclusion: MI455X leads B200 in FP4/FP8 compute and memory capacity/bandwidth, but software ecosystem remains a weak point. Versus Rubin R200, paper specs are close, but Rubin has the CUDA ecosystem moat.
Production timeline
| Time | Event |
|---|
| June 12, 2025 | MI400 series specs first announced at Advancing AI |
| January 5, 2026 | MI455X/MI450/MI440X formally launched at CES 2026 |
| 2026 Q3 | MI450 sampling begins |
| 2026 Q4 | MI455X mass production |
| 2026 Q4 | MI440X (enterprise inference) launched |
| 2027 Q1 | MI430X/MI400X (HPC/edge inference) launched |
| 2027 | MI500 series (next gen) |
AMD AI chip roadmap (2025-2027)
| Time | Product | Process | Notes |
|---|
| Q4 2024 | MI325X | TSMC 5nm | HBM3e upgraded |
| Q3 2025 | MI355X (MI350 series) | TSMC 3nm | CDNA 4, 288GB HBM3e |
| Q4 2026 | MI455X (MI400 series) | 2nm + 3nm hybrid | CDNA 5, 432GB HBM4 |
| Q1 2027 | MI500 series | TSMC 2nm (est.) | Next gen, further gains |
Software ecosystem: ROCm's progress and challenges
✅ Progress
- PyTorch 2.5+: native MI300X/MI455X support
- Hugging Face Transformers: official AMD GPU support
- vLLM 0.8+: MI300X inference support (experimental)
- JAX: AMD adapting (vs Google TPU)
⚠️ Challenges
- Framework optimization: PyTorch on AMD GPUs still below NVIDIA
- Operator coverage: some niche operators need hand-written HIP
- Multi-card communication: RCCL (vs NCCL) still lags
- Developer ecosystem: tutorials, cases, community activity far below NVIDIA
Competitive comparison
| Vendor | Product | FP4 compute | Memory | Mass production | Strength | Weakness |
|---|
| AMD | MI455X | 40 PFLOPS | 432GB HBM4 | 2026 Q4 | Largest memory, open ecosystem | Software gap |
| NVIDIA | B200 | 20 PFLOPS | 192GB HBM3e | 2024 Q4 | Most mature ecosystem | Smaller memory |
| NVIDIA | Rubin R200 | ~40 PFLOPS | 288GB HBM4 | 2026 Q4 | Next-gen architecture, CUDA | Expensive |
| Huawei | Ascend 910C | ~1.6 PFLOPS | 64GB HBM | 2026 Q2 | China-localized | Export-controlled |
| Google | TPU 8t | ~9.2 PFLOPS | ~256GB HBM3e | Late 2027 | Gemini-integrated | Google Cloud only |
Industry impact
1. Impact on NVIDIA
On paper, AMD MI455X has already caught up to B200 (FP4 40 PFLOPS vs 20 PFLOPS), even leading substantially in memory capacity (432GB vs 192GB).
But:
- NVIDIA has the CUDA ecosystem moat
- NVIDIA has the Vera Rubin platform (full solution, 2026 Q4)
- AMD only sells cards/nodes, NVIDIA sells AI factories
- MI455X mass production (2026 Q4) coincides with Rubin R200 — head-on competition
2. Pressure on domestic chips
MI455X's launch means: mainstream international AI chips enter the 2nm + HBM4 era in 2026.
Domestic chips (Huawei Ascend, Cambricon, MetaX, etc.) need to:
- Catch up to 5nm + HBM3e by 2026-2027
- Otherwise the gap widens from "1 generation" to "2 generations"
3. Significance for cloud providers
MI455X gives cloud providers a second option beyond NVIDIA:
- Microsoft Azure: already deployed MI355X, may follow with MI455X
- Google Cloud: in-house TPU, won't use AMD
- Amazon AWS: in-house Trainium/Inferentia, won't use AMD
- Alibaba Cloud, Tencent Cloud: may procure MI455X as NVIDIA alternative
References
This article is compiled from AMD CES 2026 official announcements, Baidu Baike, and Zhihu on-site reports; specs verified against official sources. Updated 2026-06-16: corrected MI455X memory (288GB → 432GB) and compute (FP8 6 PFLOPS → FP4 40 PFLOPS).