GAUDI2 vs A16
Explore a head to head comparison of specifications, performance, and pricing.
GAUDI2
The intel GAUDI2 delivers high-performance computing capabilities for AI, machine learning, and data science applications.
A16
The NVIDIA A16 delivers high-performance computing capabilities for AI, machine learning, and data science applications.
GAUDI2 vs A16: Which Should You Choose?
The GAUDI2 offers 96 GB of VRAM — 1.5× the 64 GB on the A16 — making it better suited for large model workloads that require holding more parameters in GPU memory.
GAUDI2 — Best Use Cases
- •General-purpose GPU compute
- •Deep learning training and inference
- •AI model development
Choose GAUDI2 when:
- ✓You need 96 GB+ VRAM for large models or long context windows
A16 — Best Use Cases
- •General-purpose deep learning training
- •Fine-tuning models up to 13B parameters
- •AI inference at moderate throughput
- •Computer vision and NLP workloads
Choose A16 when:
- ✓64 GB VRAM is sufficient for your workload
See how the GAUDI2 & A16 compare
Compare detailed hardware specifications and average pricing for the GAUDI2 and A16.
Compare Hardware Specifications
| GAUDI2 | A16 | |
|---|---|---|
| GPU Type | GAUDI2 | A16 |
| VRAM per GPU | 96 GB | 64 GB |
| Manufacturer | intel | NVIDIA |
| Architecture | N/A | Ampere |
| Interconnect | pcie | PCIe Gen4 |
| Memory Bandwidth | N/A | 4x 200 GB/s |
| FP16 TFLOPS | N/A | 4.493 TFLOPS (1:1) |
| CUDA Cores | N/A | 4x 1,280 |
| Tensor Cores | N/A | 4x 40 (3rd Gen) |
| RT Cores | N/A | 4x 10 (2nd Gen) |
| Base Clock | N/A | 1312 MHz |
| Boost Clock | N/A | 1755 MHz |
| TDP | N/A | 250W |
| Process Node | N/A | TSMC 8nm |
| Data Formats | N/A | INT8, BF16, FP16, TF32, FP32 |
Compare Average On-Demand Pricing
| GAUDI2 | A16 | |
|---|---|---|
| 1 GPU | N/A | $0.51 /hr |
| 2 GPUs | N/A | $1.02 /hr |
| 4 GPUs | N/A | $2.05 /hr |
| 8 GPUs | $8.80 /hr | $4.09 /hr |
Frequently Asked Questions: GAUDI2 vs A16
The main differences are VRAM (96 GB vs 64 GB).
The GAUDI2 is generally better for large language model training due to its higher throughput and 64 GB of VRAM, which allows fitting larger models or larger batch sizes in a single pass. For smaller models or fine-tuning tasks where cost matters more, both GPUs can be effective.
Pricing for the GAUDI2 and A16 varies by cloud provider, region, and contract type. Shadeform aggregates pricing from 30+ GPU cloud providers so you can compare and find the best rate. Use the instance table above to see current on-demand prices.
The GAUDI2 has more VRAM at 96 GB, compared to 64 GB on the A16. Higher VRAM allows you to run larger models without quantization, use longer context windows, and process larger batch sizes — all of which improve throughput and reduce latency for memory-bound workloads.
The GAUDI2 is currently available across 1 cloud providers on Shadeform's network, compared to 1 for the A16. Shadeform lets you deploy either GPU across all available providers from a single platform, so you can always find available capacity without manually checking each cloud.
Mixing different GPU types in a single training cluster is generally not recommended, as it creates performance bottlenecks where faster GPUs wait for slower ones. For best results, use a homogeneous cluster of either GAUDI2 or A16. Shadeform supports on-demand clusters of up to 64 GPUs of the same type with no commitment required.
Explore GAUDI2 & A16 Instances
Browse available instances with GAUDI2 and A16 GPUs. Filter by provider, availability, and more to find the perfect instance for your needs.
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