Intel Gaudi 4 / Jaguar Shores Latest Progress: Returning to the AI Race with HBM4 Memory
· 6 min read
On March 18, 2026, Intel officially launched at the Intel AI Summit: the Habana Gaudi 4 custom AI accelerator. This is Intel's latest-gen AI training/inference chip after Gaudi 3 (launched April 2024), designed for large-scale model training.
Meanwhile, Intel confirmed its next-gen Jaguar Shores GPU (datacenter GPU) is in development, will use HBM4 memory, and is expected in 2027. This marks Intel's formal return to the AI chip race.
Key Highlights
- Gaudi 4: Launched March 2026, TSMC 5nm, 64GB HBM3e, for large-scale training
- Jaguar Shores: Launches 2027 (est.), HBM4, targeting NVIDIA Rubin
- Crescent Island: Intel's first general-purpose GPU (launched 2026), Xe3 architecture
- Software ecosystem: Intel AI Stack (including oneAPI, BigDL, Gaudi Software Suite)
- Foundry partners: TSMC (Gaudi 4, Jaguar Shores), Intel Foundry (Crescent Island)
Gaudi 4 Detailed Specs
Gaudi 4 is the fourth-gen AI accelerator designed by Intel's Habana Labs (acquired 2019).
| Parameter | Gaudi 4 | Gaudi 3 (2024) | NVIDIA B200 |
|---|---|---|---|
| Architecture | Habana 4 | Habana 3 | Blackwell |
| Process | TSMC 5nm | TSMC 7nm | TSMC 4NP |
| FP8 compute | ~2,000 TFLOPS (est.) | 1,000 TFLOPS | 4,500 TFLOPS (sparse) |
| Memory | 64GB HBM3e | 128GB HBM2e (est.) | 192GB HBM3e |
| Memory bandwidth | ~3 TB/s (est.) | ~2 TB/s (est.) | 8 TB/s |
| TDP | ~500W (est.) | ~400W | 700-1000W |
| Interconnect | RoCE v3 (Ethernet) | RoCE v2 | NVLink 5.0 |
| Launch | March 2026 | April 2024 | March 2024 |
| Mass production | 2026 Q3 (est.) | Q4 2024 | Q4 2024 |
📌 Note: Gaudi 4 exact specs not fully public; some values above are estimates.
Gaudi 4 Key Features
- Native Ethernet support: Uses RoCE v3 (RDMA over Converged Ethernet), no dedicated interconnect protocol needed (like NVLink)
- Large-scale scaling optimized: Ten-thousand-card cluster scaling efficiency better than InfiniBand (lower cost)
- Sparsity acceleration: Native MoE model support
- Multi-precision support: FP8/FP16/FP32/INT8/INT4
- Open ecosystem: Supports PyTorch, TensorFlow, JAX (via third-party adaptation)
Jaguar Shores: Intel's Next-Gen GPU
Jaguar Shores is Intel's first true datacenter GPU (not an ASIC like Gaudi).
Why "Jaguar Shores"?
- Jaguar: Symbolizes "speed" and "agility"
- Shores: Symbolizes "openness" and "connection"
Jaguar Shores Estimated Specs
| Parameter | Jaguar Shores (est.) | NVIDIA Rubin | AMD MI455X |
|---|---|---|---|
| Architecture | Xeu 3 (est.) | Rubin | CDNA 4 |
| Process | TSMC 3nm (est.) | TSMC 3nm | TSMC 3nm |
| Memory | HBM4 (confirmed) | HBM4 | HBM4 |
| Memory capacity | 288GB (est.) | 288GB | 288GB |
| FP8 compute | ~4,000 TFLOPS (est.) | ~6,000 TFLOPS | 6,000 TFLOPS |
| TDP | ~800W (est.) | ~1,000W | ~800W |
| Launch | 2027 (est.) | 2026 Q3 | 2026 Q3 |
Key confirmations:
- ✅ HBM4 memory: Intel confirmed Jaguar Shores will use SK hynix HBM4
- ✅ TSMC foundry: Jaguar Shores will be produced by TSMC (not Intel Foundry)
- ✅ oneAPI native support: Jaguar Shores will natively support the oneAPI programming model
Crescent Island: Intel's First General-Purpose GPU
Crescent Island is Intel's first general-purpose datacenter GPU announced October 2025, using the Xe3 architecture (upgrade of Xe-HPG).
| Parameter | Crescent Island (est.) | Intel Data Center GPU Max | NVIDIA L40S |
|---|---|---|---|
| Architecture | Xeu 3 | Xeu 2 (Ponte Vecchio) | Ada Lovelace |
| Positioning | General compute + AI inference | HPC + AI training | AI inference + graphics |
| Process | TSMC 5nm (est.) | Intel 7 + TSMC 5nm | TSMC 4N |
| Memory | 48GB HBM3 (est.) | 128GB HBM2e | 48GB GDDR6 |
| TDP | ~300W (est.) | 600W | 350W |
| Launch | 2026 (est.) | Jan 2023 | Mar 2023 |
Positioning:
- ✅ General-purpose GPU: Both AI inference and scientific computing (HPC)
- ✅ Low cost: Cheaper than Gaudi 4, targeting NVIDIA L40S
- ✅ Open standards: Supports oneAPI, SYCL, Level Zero
Intel AI Chip Roadmap (2024-2027)
| Time | Product | Type | Process | Note |
|---|---|---|---|---|
| 2024 Q4 | Gaudi 3 | AI ASIC | TSMC 7nm | Current mainstay |
| 2026 Q2 | Crescent Island | General GPU | TSMC 5nm | New launch |
| 2026 Q3 | Gaudi 4 | AI ASIC | TSMC 5nm | New launch |
| 2027 | Jaguar Shores | Datacenter GPU | TSMC 3nm | Next-gen flagship |
| 2027 | Gaudi 5 (est.) | AI ASIC | TSMC 3nm | Next-gen |
vs Competitors
Gaudi 4 vs NVIDIA B200
| Metric | Gaudi 4 | NVIDIA B200 |
|---|---|---|
| FP8 compute | ~2,000 TFLOPS | 4,500 TFLOPS |
| Memory | 64GB HBM3e | 192GB HBM3e |
| Interconnect | Ethernet (RoCE v3) | NVLink 5.0 |
| Software ecosystem | Gaudi Software Suite | CUDA |
| Price | est. ~$20,000 | ~$45,000 |
| Advantage | Low Ethernet cost, open | Most mature ecosystem, strongest performance |
| Disadvantage | Weak software ecosystem, lower compute | Expensive |
Conclusion: Gaudi 4 is positioned as a "cost-effective training solution," suited for cost-sensitive customers willing to invest in software adaptation.
Jaguar Shores vs NVIDIA Rubin
| Metric | Jaguar Shores (est.) | NVIDIA Rubin |
|---|---|---|
| FP8 compute | ~4,000 TFLOPS | ~6,000 TFLOPS |
| Memory | 288GB HBM4 | 288GB HBM4 |
| Software ecosystem | oneAPI | CUDA |
| Mass production | 2027 | 2026 Q3 |
| Advantage | Open standards, possibly cheaper | Mature ecosystem, first-mover advantage |
| Disadvantage | Weak ecosystem, 1 year late | Expensive |
Conclusion: If Jaguar Shores launches on time with sufficient oneAPI ecosystem improvement, it can become NVIDIA's third choice (after NVIDIA and AMD).
Software Ecosystem: oneAPI Progress and Challenges
What is oneAPI?
oneAPI is Intel's open, cross-architecture programming model:
- Supports CPU, GPU, FPGA, AI accelerators
- Based on SYCL standard (similar to CUDA's C++ extensions)
- Open-source implementation (Intel oneAPI Base Toolkit)
Intel AI Stack
| Component | Purpose | Counterpart |
|---|---|---|
| oneAPI | Cross-architecture programming model | CUDA |
| BigDL | Distributed deep learning framework | PyTorch Distributed |
| Gaudi Software Suite | Gaudi-specific software stack | NVIDIA GPU Cloud (NGC) |
| Intel Extension for PyTorch | PyTorch optimization on Intel hardware | NVIDIA PyTorch |
| Intel Optimization for TensorFlow | TensorFlow optimization on Intel hardware | NVIDIA TensorFlow |
✅ Progress
- PyTorch 2.5+: Intel Extension integrated into PyTorch mainline
- Hugging Face Transformers: Official Intel GPU support (via optimum-intel)
- vLLM: Experimental Gaudi support (performance TBD)
⚠️ Challenges
- Developer habits: Global AI developers use CUDA; oneAPI has a steep learning curve
- Operator coverage: Many PyTorch operators lack oneAPI-optimized versions
- Performance: At same power, Gaudi 4 performance is only ~50% of B200
Industry Impact
1. Can Intel Return to the AI Race?
Challenges:
- ❌ Ecosystem disadvantage: CUDA moat too deep, oneAPI hard to shake
- ❌ Performance disadvantage: Gaudi 4 only ~50% of B200
- ❌ Timing disadvantage: Jaguar Shores 1 year later than Rubin
Opportunities:
- ✅ Open standards: Not dependent on CUDA, suited for "anti-NVIDIA-monopoly" customers
- ✅ Ethernet advantage: RoCE v3 cheaper than InfiniBand at ten-thousand-card scale
- ✅ Intel Foundry: If Jaguar Shores uses Intel's own process, lower cost
2. Impact on AMD
Intel's return to the AI race is bad for AMD:
- AMD was the "only NVIDIA alternative"
- Now Intel is back too; AMD's "alternative" status is challenged
- But in the short term (2026-2027), Intel cannot yet threaten AMD
3. Impact on Domestic Chips
Intel Gaudi 4's launch is a reference case for domestic chips:
- Proves the Ethernet route (RoCE) is viable
- Proves open ecosystem (oneAPI) is hard but necessary
- Proves the cost-effective route has a market (cost-sensitive customers)
Related Chips
- Intel Gaudi 3 - Previous-gen product
- Intel Gaudi 4 - New launch (to be created)
- Intel Crescent Island - Intel's first general GPU (to be created)
- NVIDIA B200 - Direct competitor
- AMD MI455X - Same-gen competitor
References
- Intel Newsroom: Gaudi 4 Launch
- Tom's Hardware: Intel Jaguar Shores to use HBM4
- Wccftech: Intel Next-Gen Jaguar Shores GPU
- U.S. News: Intel Signals Return to AI Race
This article is compiled from Intel official announcements and public materials. Some specs are estimates, subject to final Intel release.