A100 vs RTX Pro 6000
Explore a head to head comparison of specifications, performance, and pricing.
A100
The NVIDIA A100 is a powerful Ampere-based GPU designed for AI training, inference, and high-performance computing workloads.
RTX Pro 6000
The NVIDIA RTX Pro 6000 delivers high-performance computing capabilities for AI, machine learning, and data science applications.
A100 vs RTX Pro 6000: Which Should You Choose?
The RTX Pro 6000 offers 96 GB of VRAM — 2× the 40 GB on the A100 — making it better suited for large model workloads that require holding more parameters in GPU memory. On FP16 throughput, the RTX Pro 6000 delivers 126 TFLOPS versus 77.97 TFLOPS on the A100 — 1.6× faster for mixed-precision training and inference. Memory bandwidth favors the RTX Pro 6000 at 0.00 TB/s compared to 0.00 TB/s on the A100, which directly impacts inference latency for memory-bandwidth-bound models. Architecturally, the A100 is built on Ampere while the RTX Pro 6000 uses Blackwell, reflecting different generational capabilities and optimizations. On Shadeform, the RTX Pro 6000 starts from $1.25/hr versus $1.29/hr for the A100 — 3% more expensive — reflecting the performance premium. The RTX Pro 6000 is available across 7 cloud providers on Shadeform compared to 5 for the A100, giving more options for region and pricing flexibility.
A100 — 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 A100 when:
- ✓40 GB VRAM is sufficient for your workload
- ✓Maximum performance justifies the higher cost
- ✓Your workload does not require peak FP16 throughput
- ✓Your preferred provider already has availability
RTX Pro 6000 — Best Use Cases
- •Next-generation LLM pre-training at scale
- •Trillion-parameter model inference
- •Ultra-high-throughput AI workloads
- •Advanced HPC and scientific computing
Choose RTX Pro 6000 when:
- ✓You need 96 GB+ VRAM for large models or long context windows
- ✓Cost efficiency is your primary concern
- ✓You are training large models or running high-throughput inference
- ✓You need flexibility across multiple cloud providers or regions
See how the A100 & RTX Pro 6000 compare
Compare detailed hardware specifications and average pricing for the A100 and RTX Pro 6000.
Compare Hardware Specifications
| A100 | RTX Pro 6000 | |
|---|---|---|
| GPU Type | A100 | RTX Pro 6000 |
| VRAM per GPU | 40 GB | 96 GB |
| Manufacturer | NVIDIA | NVIDIA |
| Architecture | Ampere | Blackwell |
| Interconnect | PCIe Gen4 or SXM4 | PCIe Gen5 |
| Memory Bandwidth | 1.55 TB/s | 1.59 TB/s |
| FP16 TFLOPS | 77.97 TFLOPS (4:1) | 126.0 TFLOPS (1:1) |
| CUDA Cores | 6912 | 24064 |
| Tensor Cores | 432 (3rd Gen) | 752 (5th Gen) |
| RT Cores | N/A | 188 (4th Gen) |
| Base Clock | 765 MHz | 1860 MHz |
| Boost Clock | 1410 MHz | 2600 MHz |
| TDP | 250W-400W | 400W |
| Process Node | TSMC 7nm | TSMC 4N |
| Data Formats | INT8, BF16, FP16, TF32, FP32, FP64 | FP4, FP6, FP8, INT8, BF16, FP16, TF32, FP32 |
Compare Average On-Demand Pricing
| A100 | RTX Pro 6000 | |
|---|---|---|
| 1 GPU | $1.74 /hr | $1.70 /hr |
| 2 GPUs | $3.91 /hr | $3.30 /hr |
| 4 GPUs | $7.80 /hr | $6.60 /hr |
| 8 GPUs | $13.78 /hr | $14.11 /hr |
Frequently Asked Questions: A100 vs RTX Pro 6000
The main differences are VRAM (40 GB vs 96 GB), FP16 throughput (77.97 vs 126 TFLOPS), architecture (Ampere vs Blackwell). The A100 uses the Ampere architecture while the RTX Pro 6000 is based on Blackwell, giving each GPU different generational capabilities.
The RTX Pro 6000 is generally better for large language model training due to its higher throughput and 96 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.
On Shadeform, the RTX Pro 6000 is available from $1.25/hr. The A100 starts from $1.29/hr. Prices vary by provider, region, and contract length. Reserved commitments can reduce hourly costs significantly compared to on-demand pricing.
The RTX Pro 6000 has more VRAM at 96 GB, compared to 40 GB on the A100. 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.
Based on TFLOPS per dollar, the RTX Pro 6000 offers better raw compute value at current Shadeform on-demand rates. However, the best choice depends on your specific workload — if you need the extra VRAM or throughput of the A100, paying the premium may be justified by faster job completion and lower total cost.
The RTX Pro 6000 is currently available across 7 cloud providers on Shadeform's network, compared to 5 for the A100. 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 A100 or RTX Pro 6000. Shadeform supports on-demand clusters of up to 64 GPUs of the same type with no commitment required.
Explore A100 & RTX Pro 6000 Instances
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