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B300 vs CPU

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

B300

The NVIDIA B300 delivers high-performance computing capabilities for AI, machine learning, and data science applications.

ManufacturerNVIDIA
GPU Architecture
Average Price$36.20/hr
GPU VRAM288 GB
Cloud Availability2 clouds
System Memory3750 GB
CPU Cores240
Storage6.0 TB

CPU

The n/a CPU delivers high-performance computing capabilities for AI, machine learning, and data science applications.

Manufacturern/a
GPU Architecture
Average Price$0.63/hr
GPU VRAM0 GB
Cloud Availability2 clouds
System Memory16 GB
CPU Cores16
Storage200 GB

See how the B300 & CPU compare

Compare detailed hardware specifications and average pricing for the B300 and CPU.

Compare Hardware Specifications

B300CPU
GPU Type
B300
CPU
VRAM per GPU
288 GB
0 GB
Manufacturer
NVIDIA
n/a
Architecture
Blackwell Ultra
N/A
Interconnect
SXM6
pcie
Memory Bandwidth
8 TB/s
N/A
FP16 TFLOPS
1,231.8 TFLOPS (16:1)
N/A
CUDA Cores
20480
N/A
Tensor Cores
640 (5th Gen)
N/A
Base Clock
1665 MHz
N/A
Boost Clock
2032 MHz
N/A
TDP
1000W
N/A
Process Node
TSMC 4NP
N/A
Data Formats
FP4, FP6, FP8, INT8, BF16, FP16, TF32, FP32, FP64
N/A

Compare Average On-Demand Pricing

B300CPU
1 GPU
$7.40 /hr
N/A
2 GPUs
$14.80 /hr
N/A
4 GPUs
$29.20 /hr
N/A
8 GPUs
$64.81 /hr
N/A

Frequently Asked Questions: B300 vs CPU

The main differences are VRAM (288 GB vs 0 GB).

The B300 is generally better for large language model training due to its higher throughput and 288 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 B300 and CPU 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 B300 has more VRAM at 288 GB, compared to 0 GB on the CPU. 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 B300 is currently available across 2 cloud providers on Shadeform's network, compared to 2 for the CPU. 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 B300 or CPU. Shadeform supports on-demand clusters of up to 64 GPUs of the same type with no commitment required.

Explore B300 & CPU Instances

Browse available instances with B300 and CPU GPUs. Filter by provider, availability, and more to find the perfect instance for your needs.

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