Intel Gaudi 4 (Q2 2026 Estimated)
:::warning Estimated Content Specifications on this page are estimated based on Intel's June 2025 public statements + Pat Gelsinger's 2024 roadmap + industry analyst projections. Intel's official full specifications have not yet been released. Official data is subject to actual Q2 2026 release. :::
Overview
Intel Gaudi 4 is Intel's 4th-generation AI training/inference accelerator, expected to launch in Q2 2026 (delayed from original Q4 2025). Built on the Intel 18A (1.8nm) process, it features 192GB HBM3E memory, 3.7 PFLOPS FP8 dense compute (2× Gaudi 3), and a Tensor processor + GEMM engine architecture. It is accompanied by the SynapseAI software stack (PyTorch / JAX / TensorFlow compatible).
Strategic positioning: Amid competition from NVIDIA H200/B200 and AMD MI325X/MI350, Intel Gaudi 4 is the core product of Intel's AI business (Gaudi 3 customers include IBM Cloud, Supermicro, ASUS, Lambda Labs). However, Intel announced on 2026-05-14 the cancellation of Falcon Shores in favor of the rack-level Jaguar Shores, meaning Gaudi 4 may be the last chip in the standalone Gaudi series.
Core Specifications (Estimated)
| Item | Specification |
|---|---|
| Architecture | Intel Gaudi 4th Gen (evolution of Gaudi 3 architecture) |
| Process Node | Intel 18A (1.8nm, ~2nm-class equivalent) |
| HBM | 192 GB HBM3E (6 stacks) |
| Memory Bandwidth | ~5 TB/s (819 GB/s per HBM3E × 6) |
| FP8 dense | 3.7 PFLOPS (2× Gaudi 3) |
| BF16 dense | 1.85 PFLOPS |
| FP16 dense | 1.85 PFLOPS |
| FP32 | ~462 TFLOPS |
| TDP | ~700 W |
| Form Factor | OAM / PCIe Gen5 ×16 |
| Interconnect | 24× 200GbE RoCE v2 (same as Gaudi 3, excellent scalability) |
| Volume Production | Q2 2026 (delayed from Q4 2025) |
| Unit Price (OAM) | ~$25,000 - $30,000 (estimated) |
Comparison with Gaudi 3
| Metric | Gaudi 4 (estimated) | Gaudi 3 | Improvement |
|---|---|---|---|
| Process Node | Intel 18A (1.8nm) | TSMC 5nm | Major upgrade |
| HBM | 192GB HBM3E | 128GB HBM2E | +50% |
| Bandwidth | 5 TB/s | 3.7 TB/s | +35% |
| FP8 | 3.7 PF | 1.835 PF | 2× |
| BF16 | 1.85 PF | 459 TF | 4× |
| TDP | 700W | 600W | +17% |
| Process source | Intel 18A in-house | TSMC foundry | Strategic shift |
| Price (estimated) | $25-30K | $12-15K | ~2× |
Comparison with Competitors (H1 2026 Flagships)
| Metric | Intel Gaudi 4 | NVIDIA H200 | AMD MI355X | Huawei Ascend 920 |
|---|---|---|---|---|
| Memory | 192GB HBM3E | 141GB HBM3E | 288GB HBM3E | 96GB HBM2E |
| Bandwidth | 5 TB/s | 4.8 TB/s | 8 TB/s | 4 Tbps |
| FP8 dense | 3.7 PF | 1.6 PF sparse | 4.6 PF | ~1.8 PF BF16 |
| TDP | 700W | 700W | ~750W | ~600W |
| Software | SynapseAI | CUDA | ROCm | CANN |
| Price | ~$27K | $30K | ~$25K | N/A |
Gaudi 4 advantage: Strongest software independence (24× 200GbE standard Ethernet interconnect, no proprietary interconnect like NVLink/UALoF required), making it the best choice for multi-cloud, multi-vendor ecosystems.
24 × 200GbE Ethernet Interconnect
| Dimension | Specification |
|---|---|
| Port Count | 24 × 200 GbE (per card) |
| Total Bandwidth | 4.8 Tb/s (600 GB/s bidirectional) |
| Protocol | RoCE v2 (RDMA over Converged Ethernet) |
| Switches | Compatible with any Ethernet switch (Arista, Broadcom, Juniper) |
| Topology | Fully connected Fat-Tree / Dragonfly+ |
| Max Cluster | 8,192 nodes (validated on Gaudi 3) |
Comparison with NVIDIA NVLink + InfiniBand:
- ✅ Open standard (Ethernet)
- ✅ Lower cost (100G/200G Ethernet vs InfiniBand)
- ✅ Multi-vendor interoperability
- ❌ Slightly higher latency (~1-2 μs RoCE vs ~0.5 μs IB)
- ❌ Large-scale NCCL optimization weaker than NVLink
SynapseAI Software Stack
| Layer | Tool | Description |
|---|---|---|
| AI Framework | SynapseAI | PyTorch / JAX / TensorFlow switching |
| Graph Compiler | Synapse Compiler | XLA + TVM hybrid |
| Operator Library | Habana Custom Ops | Custom operator SDK |
| Quantization | Quantization Toolkit | INT8 / FP8 training |
| Communication | Habana CCL | Collective communication (AllReduce etc.) |
| Graph Optimizer | Graph Compiler | Automatic operator fusion |
⚠️ Ecosystem limitation: Compared to CUDA's 10-year ecosystem, SynapseAI is still relatively new. 80-90% of PyTorch models run with zero code changes, but complex LLM training requires manual optimization.
Vendor Information
| Item | Details |
|---|---|
| Company | Intel Corporation |
| Business Unit | Intel Data Center & AI Group (DCAI) |
| Product Page | https://www.intel.com/content/www/us/en/products/details/processors/ai-accelerators/gaudi.html |
| Headquarters | Santa Clara, California, USA |
| CEO | Lip-Bu Tan (appointed March 2025) |
| Foundry | Intel 18A in-house (Oregon Fab 52 + Arizona Fab 62) |
| Target Customers | IBM Cloud, Supermicro, ASUS, Lambda Labs, Zenlayer, India Yotta |
| 2025 Gaudi Revenue | ~$3.5B (+50% YoY) |
Gaudi Product Line
| Product | Launch | Compute FP8 | Memory | Status |
|---|---|---|---|---|
| Gaudi 1 | Q3 2019 | 0 (FP16: 165 TF) | 32GB HBM2 | EOL |
| Gaudi 2 | Q3 2022 | 0 (FP16: 459 TF) | 96GB HBM2E | EOL |
| Gaudi 3 | Q2 2024 | 1.835 PF | 128GB HBM2E | Current flagship |
| Gaudi 4 | Q2 2026 (estimated) | 3.7 PF | 192GB HBM3E | Next generation |
| Gaudi 5 | 2027+ | ? | ? | Planned |
Key Features
- Open Ethernet interconnect (24× 200GbE, InfiniBand-like but more open)
- FP8 dense (no sparse dependency, 2× FP16 effective compute)
- Intel 18A in-house foundry (strategic shift from TSMC 5nm to Intel Foundry)
- SynapseAI PyTorch compatibility (more developer-friendly than ROCm / Cambricon ecosystem)
- Price advantage (estimated ~$25-30K vs H200 $30K)
- Drawback: 700W TDP on the high side, 5-year software ecosystem vs CUDA's 18 years
Use Cases
- ✅ Multi-cloud AI training (open Ethernet, deployable in any DC)
- ✅ Large-scale LLM training (192GB HBM3E accommodates larger models)
- ✅ HPC + AI convergence (Fortran / MPI compatible)
- ✅ Government/state-owned enterprise AI projects (Intel brand + US manufactured)
- ✅ Budget-sensitive (price advantage vs H200)
- ❌ Cutting-edge FP4 models (Gaudi 4 estimated not to support FP4)
- ❌ NVLink-only workloads (e.g. NVIDIA Megatron-LM heavily optimized)
Intel AI Strategic Shift
On 2026-05-14, Intel announced the cancellation of Falcon Shores (originally a Gaudi 4 + GPU fusion chip), pivoting to the rack-level Jaguar Shores system. This means:
- Gaudi 4 may be the last standalone Gaudi accelerator
- 2027+ Intel AI roadmap shifts to Jaguar Shores rack (integrating Gaudi IP + Xeon + 800G NIC)
- Customers should consider a Gaudi 4 → Jaguar Shores migration path
Related Cards
- Intel Gaudi 3 - Previous generation
- Intel Gaudi 2 - Prior generation
- Intel Jaguar Shores - Rack-level replacement
- NVIDIA H200 - Competitor
- AMD MI355X - Competitor
- Huawei Ascend 920 - Domestic comparison
- Intel Max Series - HPC GPU