Specifications Compared
| Spec | GAUDI2 | RTX-4070 |
|---|---|---|
| TDP | 600W | 200W |
| VRAM | 96 GB | 12 GB |
| Memory Type | HBM2e | GDDR6X |
| Architecture | Gaudi | Ada Lovelace |
| Form Factors | OAM | PCIe |
| Interconnect | Ethernet | |
| FP16 Performance | 420 TFLOPS | 29.1 TFLOPS |
| FP32 Performance | 420 TFLOPS | 29.1 TFLOPS |
| Memory Bandwidth | 2,460 GB/s | 504 GB/s |
Performance Analysis
The Gaudi 2's 420 TFLOPS FP16 and FP32 performance enables rapid matrix operations essential for deep learning training, processing models at scales unattainable by the RTX 4070 SUPER's 35 TFLOPS in those precisions. This delta translates to over 12 times faster throughput for compute-bound tasks like gradient computations during backpropagation. Balanced FP16 and FP32 ratings on both GPUs support mixed-precision training, but Gaudi 2 excels in sustained high-utilization scenarios. Memory differences prove critical: Gaudi 2's 96 GB HBM2e versus 12 GB GDDR6X allows massive batch sizes in LLM training, reducing iterations by handling datasets up to eight times larger without swapping. Its 2460 GB/s bandwidth, nearly five times the RTX 4070 SUPER's 504 GB/s, minimizes bottlenecks in data loading for inference, enabling larger concurrent requests. The Gaudi 2's 600W TDP reflects enterprise cooling needs, while RTX 4070 SUPER's 220W suits edge or desktop efficiency.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
Intel Gaudi 2
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 LeaderGPU | 8×Intel Gaudi 2 96GB VRAM | 96GB | 64 vCPU 2048GB RAM 96174GB Storage | Netherlands | $0.91/GPU/hr $7.29/hr total (8×) | Available | ||
 Denvr | 8×Intel Gaudi 2 96GB VRAM | 96GB | 160 vCPU 1024GB RAM 30400GB Storage | Virginia | $1.25/GPU/hr $10.00/hr total (8×) |
RTX 4070 SUPER
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 RunPod | NVIDIA GeForce RTX 4070 Ti 12GB VRAM | 12GB | 6 vCPU 30GB RAM | 🌍global | $0.50/GPU/hr |
When to Choose the Intel Gaudi 2
Choose the Intel Gaudi 2 for large-scale AI training and fine-tuning where 96 GB VRAM accommodates full LLM parameter sets without partitioning. Its 2460 GB/s bandwidth and 420 TFLOPS compute handle high-batch scientific simulations or multi-node clusters via Ethernet interconnect. Cloud users benefit from $0.91 per hour pricing for production workloads demanding OAM form factor scalability.
When to Choose the RTX 4070 SUPER
Opt for the NVIDIA GeForce RTX 4070 SUPER in consumer or small-team setups needing 12 GB VRAM for Stable Diffusion or lightweight inference at 35 TFLOPS FP16. Its 220W TDP and PCIe compatibility fit desktops or low-power clouds without live offers. Gamers or hobbyists leverage Ada Lovelace efficiencies for hybrid gaming-AI tasks.
Use Cases
Gaudi 2's 96 GB VRAM and 420 TFLOPS FP16 handle large models and batches infeasible on RTX 4070 SUPER's 12 GB. Bandwidth of 2460 GB/s accelerates data throughput in extended sessions.
Gaudi 2 supports high-concurrency inference with 96 GB VRAM for multiple large models. Its Ethernet interconnect scales clusters better than RTX 4070 SUPER's single-node limits.
420 TFLOPS FP32 on Gaudi 2 speeds gradient updates for billion-parameter models fitting in 96 GB. RTX 4070 SUPER's 35 TFLOPS limits scale on 12 GB VRAM.
RTX 4070 SUPER's 12 GB VRAM and 504 GB/s suffice for image generation at 35 TFLOPS. Lower 220W TDP fits consumer setups without Gaudi 2's enterprise overhead.
Gaudi 2 excels in memory-intensive simulations with 96 GB and 2460 GB/s; RTX 4070 SUPER handles lighter FP32 tasks at 35 TFLOPS on PCIe. Choice depends on dataset size.
Frequently Asked Questions
What is the VRAM difference between Gaudi 2 and RTX 4070 SUPER?▾
Gaudi 2 offers 96 GB HBM2e VRAM, while RTX 4070 SUPER provides 12 GB GDDR6X. This eightfold gap allows Gaudi 2 to load massive models without sharding. It impacts batch sizes in training directly.
How do FP16 performances compare?▾
Gaudi 2 delivers 420 TFLOPS FP16, exceeding RTX 4070 SUPER's 35 TFLOPS by over 12 times. This boosts AI training speed significantly. Inference latency drops accordingly on Gaudi 2.
What are the cloud pricing details?▾
Intel Gaudi 2 starts at $0.91 per hour, averaging $1.08 across two offers. RTX 4070 SUPER has no live cloud offers. Gaudi 2 suits budgeted enterprise rentals.
Which has higher memory bandwidth?▾
Gaudi 2 achieves 2460 GB/s, nearly five times RTX 4070 SUPER's 504 GB/s. Higher bandwidth reduces data stalls in large-batch training. It enables smoother inference pipelines.
Compare their TDPs and form factors.▾
Gaudi 2 consumes 600W in OAM form for servers; RTX 4070 SUPER uses 220W in PCIe for desktops. Gaudi 2 requires data center cooling. RTX 4070 SUPER fits power-constrained environments.
Is Gaudi 2 better for AI clusters?▾
Yes, Gaudi 2's Ethernet interconnect supports multi-GPU scaling unlike RTX 4070 SUPER's lack of specified interconnect. 420 TFLOPS per unit amplifies cluster throughput. It targets enterprise AI deployments.
Which is cheaper to rent, the Gaudi 2 or the RTX 4070?▾
Cloud rental prices for both the Gaudi 2 and RTX 4070 vary by provider, configuration, and availability. This page shows live pricing from 25+ providers updated every 60 seconds. Scroll to the Live Cloud Pricing section to compare current rates.
How much VRAM does the Gaudi 2 have compared to the RTX 4070?▾
The Gaudi 2 has 96 GB of HBM2e memory. The RTX 4070 has 12 GB of GDDR6X memory.
Can I find Gaudi 2 and RTX 4070 GPUs available to rent right now?▾
Yes. This page shows real-time availability across 25+ cloud GPU providers. The Live Cloud Pricing section displays only in-stock offers with current pricing.
What is the main difference between the Gaudi 2 and the RTX 4070?▾
The Gaudi 2 uses the Gaudi architecture (2022) while the RTX 4070 uses Ada Lovelace (2023). The Gaudi 2 delivers 14.4x the FP16 throughput and 4.9x the memory bandwidth of the RTX 4070.