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V100 vs RTX Pro 6000

Explore a head to head comparison of specifications, performance, and pricing.

V100

The NVIDIA V100 delivers high-performance computing capabilities for AI, machine learning, and data science applications.

ManufacturerNVIDIA
GPU ArchitectureVolta
Average Price$2.21/hr
GPU VRAM16 GB
Cloud Availability3 clouds
System Memory448 GB
CPU Cores92
Storage6.0 TB

RTX Pro 6000

The NVIDIA RTX Pro 6000 delivers high-performance computing capabilities for AI, machine learning, and data science applications.

ManufacturerNVIDIA
GPU Architecture
Average Price$7.34/hr
GPU VRAM96 GB
Cloud Availability7 clouds
System Memory1800 GB
CPU Cores240
Storage30.7 TB

V100 vs RTX Pro 6000: Which Should You Choose?

The RTX Pro 6000 offers 96 GB of VRAM — 6× the 16 GB on the V100 — 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 28.26 TFLOPS on the V100 — 4× faster for mixed-precision training and inference. Memory bandwidth favors the V100 at 0.90 TB/s compared to 0.00 TB/s on the RTX Pro 6000, which directly impacts inference latency for memory-bandwidth-bound models. Architecturally, the V100 is built on Volta while the RTX Pro 6000 uses Blackwell, reflecting different generational capabilities and optimizations. On Shadeform, the V100 starts from $0.39/hr versus $1.25/hr for the RTX Pro 6000 — 221% more expensive — reflecting the performance premium. The RTX Pro 6000 is available across 7 cloud providers on Shadeform compared to 3 for the V100, giving more options for region and pricing flexibility.

V100 — Best Use Cases

  • Deep learning training
  • HPC and scientific computing
  • Legacy ML infrastructure

Choose V100 when:

  • 16 GB VRAM is sufficient for your workload
  • Cost efficiency is your primary concern
  • 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
  • Maximum performance justifies the higher cost
  • You are training large models or running high-throughput inference
  • You need flexibility across multiple cloud providers or regions

See how the V100 & RTX Pro 6000 compare

Compare detailed hardware specifications and average pricing for the V100 and RTX Pro 6000.

Compare Hardware Specifications

V100RTX Pro 6000
GPU Type
V100
RTX Pro 6000
VRAM per GPU
16 GB
96 GB
Manufacturer
NVIDIA
NVIDIA
Architecture
Volta
Blackwell
Interconnect
PCIe Gen3
PCIe Gen5
Memory Bandwidth
900 GB/s
1.59 TB/s
FP16 TFLOPS
28.26 TFLOPS (2:1)
126.0 TFLOPS (1:1)
CUDA Cores
5120
24064
Tensor Cores
640 (1st Gen)
752 (5th Gen)
RT Cores
N/A
188 (4th Gen)
Base Clock
1230 MHz
1860 MHz
Boost Clock
1380 MHz
2600 MHz
TDP
250-300W
400W
Process Node
TSMC 12nm
TSMC 4N
Data Formats
FP16, FP32, FP64
FP4, FP6, FP8, INT8, BF16, FP16, TF32, FP32

Compare Average On-Demand Pricing

V100RTX Pro 6000
1 GPU
$1.36 /hr
$1.70 /hr
2 GPUs
$0.78 /hr
$3.30 /hr
4 GPUs
N/A
$6.60 /hr
8 GPUs
$3.76 /hr
$14.11 /hr

Frequently Asked Questions: V100 vs RTX Pro 6000

The main differences are VRAM (16 GB vs 96 GB), FP16 throughput (28.26 vs 126 TFLOPS), architecture (Volta vs Blackwell). The V100 uses the Volta 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 V100 is available from $0.39/hr. The RTX Pro 6000 starts from $1.25/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 16 GB on the V100. 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 V100, 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 3 for the V100. 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 V100 or RTX Pro 6000. Shadeform supports on-demand clusters of up to 64 GPUs of the same type with no commitment required.

Explore V100 & RTX Pro 6000 Instances

Browse available instances with V100 and RTX Pro 6000 GPUs. Filter by provider, availability, and more to find the perfect instance for your needs.

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