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RTX 6000 Ada vs B200

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

RTX 6000 Ada

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

ManufacturerNVIDIA
GPU Architecture
Average Price$3.62/hr
GPU VRAM48 GB
Cloud Availability4 clouds
System Memory640 GB
CPU Cores128
Storage15.4 TB

B200

The NVIDIA B200 delivers high-performance computing capabilities for AI, machine learning, and data science applications.

ManufacturerNVIDIA
GPU Architecture
Average Price$21.98/hr
GPU VRAM192 GB
Cloud Availability4 clouds
System Memory2900 GB
CPU Cores248
Storage30.7 TB

RTX 6000 Ada vs B200: Which Should You Choose?

The B200 offers 192 GB of VRAM — 4× the 48 GB on the RTX 6000 Ada — making it better suited for large model workloads that require holding more parameters in GPU memory. On FP16 throughput, the RTX 6000 Ada delivers 91.06 TFLOPS versus 1 TFLOPS on the B200 — 91× faster for mixed-precision training and inference. Memory bandwidth favors the RTX 6000 Ada at 0.96 TB/s compared to 0.01 TB/s on the B200, which directly impacts inference latency for memory-bandwidth-bound models. Architecturally, the RTX 6000 Ada is built on Ada Lovelace while the B200 uses Blackwell, reflecting different generational capabilities and optimizations. On Shadeform, the RTX 6000 Ada starts from $0.97/hr versus $5.29/hr for the B200 — 445% more expensive — reflecting the performance premium.

RTX 6000 Ada — Best Use Cases

  • LLM inference and model serving
  • Image generation and diffusion models
  • Smaller fine-tuning runs
  • Cost-efficient GPU compute

Choose RTX 6000 Ada when:

  • 48 GB VRAM is sufficient for your workload
  • Cost efficiency is your primary concern
  • You are training large models or running high-throughput inference

B200 — 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 B200 when:

  • You need 192 GB+ VRAM for large models or long context windows
  • Maximum performance justifies the higher cost
  • Your workload does not require peak FP16 throughput

See how the RTX 6000 Ada & B200 compare

Compare detailed hardware specifications and average pricing for the RTX 6000 Ada and B200.

Compare Hardware Specifications

RTX 6000 AdaB200
GPU Type
RTX 6000 Ada
B200
VRAM per GPU
48 GB
192 GB
Manufacturer
NVIDIA
NVIDIA
Architecture
Ada Lovelace
Blackwell
Interconnect
PCIe Gen4
SXM6
Memory Bandwidth
960 GB/s
8 TB/s
FP16 TFLOPS
91.06 TFLOPS (1:1)
1,191.2 TFLOPS (16:1)
CUDA Cores
18176
20480
Tensor Cores
568 (4th Gen)
640 (5th Gen)
RT Cores
142 (3rd Gen)
N/A
Base Clock
915 MHz
700 MHz
Boost Clock
2505 MHz
1965 MHz
TDP
300W
1000W
Process Node
TSMC 4N
TSMC 4NP
Data Formats
FP8, INT8, BF16, FP16, TF32, FP32
FP4, FP6, FP8, INT8, BF16, FP16, TF32, FP32, FP64

Compare Average On-Demand Pricing

RTX 6000 AdaB200
1 GPU
$1.20 /hr
$5.29 /hr
2 GPUs
$2.04 /hr
$10.49 /hr
4 GPUs
$3.88 /hr
$20.78 /hr
8 GPUs
$7.01 /hr
$36.68 /hr

Frequently Asked Questions: RTX 6000 Ada vs B200

The main differences are VRAM (48 GB vs 192 GB), FP16 throughput (91.06 vs 1 TFLOPS), architecture (Ada Lovelace vs Blackwell). The RTX 6000 Ada uses the Ada Lovelace architecture while the B200 is based on Blackwell, giving each GPU different generational capabilities.

The RTX 6000 Ada is generally better for large language model training due to its higher throughput and 48 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 6000 Ada is available from $0.97/hr. The B200 starts from $5.29/hr. Prices vary by provider, region, and contract length. Reserved commitments can reduce hourly costs significantly compared to on-demand pricing.

The B200 has more VRAM at 192 GB, compared to 48 GB on the RTX 6000 Ada. 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 6000 Ada 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 B200, paying the premium may be justified by faster job completion and lower total cost.

The RTX 6000 Ada is currently available across 4 cloud providers on Shadeform's network, compared to 4 for the B200. 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 RTX 6000 Ada or B200. Shadeform supports on-demand clusters of up to 64 GPUs of the same type with no commitment required.

Explore RTX 6000 Ada & B200 Instances

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