GPU comparison

B300 vs Quadro P6000

Specifications and current cloud pricing, side by side.

Blackwell UltravsPascalUpdated 33 days ago

The B300 provides the stronger choice for the most common use case of LLM training because its 2250 TFLOPS FP16 dense rating and 262 to 288 GB memory capacity exceed the corresponding capabilities of the Quadro P6000 by wide margins.

B300 from $0.50/GPU/hrQuadro P6000 from $1.10/GPU/hr

Right now, from live stock

  • Cheapest right now: B300 at $0.50/hr on RunPod

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  • Most providers in stock: B300 and Quadro P6000 (1 each)

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Specifications Compared

SpecB300Quadro P6000
TDP1400W250W
VRAM262-288 GB24 GB
CUDA CoresNot published3,840
FP4 (dense)13,500 TFLOPSNot published
FP8 (dense)4,500 TFLOPSNot published
Memory TypeHBM3eGDDR5X
ArchitectureBlackwell UltraPascal
FP16 (dense)2,250 TFLOPSNot published
Form FactorsSXM6PCIe
INT8 (dense)187.5 TOPSNot published
InterconnectNVLink, PCIe 6.0, InfiniBandPCIe 3.0
FP32 Performance75 TFLOPS12.6 TFLOPS
FP64 Performance1.25 TFLOPSNot published
Memory Bandwidth8,000 GB/s432 GB/s
FP4 (with sparsity)18,000 TFLOPSNot published
FP8 (with sparsity)9,000 TFLOPSNot published
FP16 (with sparsity)4,500 TFLOPSNot published
INT8 (with sparsity)375 TOPSNot published

Performance Analysis

The B300 provides FP16 dense performance at 2250 TFLOPS while no FP16 figure appears for the Quadro P6000. FP32 performance reaches 75 TFLOPS on the B300 against 12.6 TFLOPS on the Quadro P6000. The 8000 GB/s bandwidth on the B300 versus 432 GB/s on the Quadro P6000 permits substantially larger batch sizes during training and inference operations. FP16 dense throughput on the B300 supports faster execution of matrix operations compared with FP32 execution on the Quadro P6000. Memory capacity between 262 and 288 GB on the B300 accommodates models that exceed the 24 GB limit of the Quadro P6000. These differences translate to reduced iteration times on the B300 for precision formats that both GPUs can execute.

Current On-Demand Offers

Cheapest secure on-demand offer per provider that is reported in stock right now, per GPU per hour; multi-GPU instances show the whole-instance price alongside. Deploy opens the DeployGPU console for providers on the platform, otherwise the provider's own site. Stock is rechecked every minute.

B300

ProviderRegionGPUsPer GPU / hrInstance / hrDeploy
RunPodglobal1$0.50—Deploy

1 provider in stock, 2 offers (cheapest per provider shown). All B300 offers, price history and alerts

Quadro P6000

ProviderRegionGPUsPer GPU / hrInstance / hrDeploy
Paperspaceams11$1.10—Deploy

1 provider in stock, 6 offers (cheapest per provider shown). All Quadro P6000 offers, price history and alerts

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When to Choose the B300

The B300 suits LLM training workloads that require between 262 and 288 GB memory capacity together with 2250 TFLOPS FP16 dense performance. Fine tuning operations scale effectively when memory bandwidth reaches 8000 GB/s as listed for the B300.

When to Choose the Quadro P6000

The Quadro P6000 fits environments constrained to 250W TDP power envelopes and PCIe 3.0 interconnects. Scientific computing workloads that rely solely on 12.6 TFLOPS FP32 performance operate within the limits of the Quadro P6000 without requiring newer form factors.

Use Cases

LLM Training
B300

The B300 supplies 2250 TFLOPS FP16 dense performance and between 262 and 288 GB memory that exceed the 24 GB limit of the Quadro P6000.

LLM Inference
B300

FP8 dense performance at 4500 TFLOPS on the B300 combined with 8000 GB/s bandwidth supports larger batch processing than the Quadro P6000 can achieve.

Fine-tuning
B300

Memory capacity between 262 and 288 GB on the B300 permits fine tuning of models that surpass the 24 GB VRAM of the Quadro P6000.

Stable Diffusion
B300

The B300 FP16 dense rating of 2250 TFLOPS accelerates diffusion model steps beyond the FP32 only rating of 12.6 TFLOPS on the Quadro P6000.

Scientific Computing
Either

The Quadro P6000 delivers 12.6 TFLOPS FP32 within a 250W TDP while the B300 offers 75 TFLOPS FP32 for higher throughput when power limits allow.

Frequently Asked Questions

What FP32 performance do the B300 and Quadro P6000 deliver?▾

The B300 reaches 75 TFLOPS FP32 and the Quadro P6000 reaches 12.6 TFLOPS FP32.

Which GPU offers higher memory bandwidth?▾

The B300 provides 8000 GB/s memory bandwidth while the Quadro P6000 provides 432 GB/s memory bandwidth.

What power limits apply to each GPU?▾

The B300 carries a 1400W TDP and the Quadro P6000 carries a 250W TDP.

Does the B300 support NVLink?▾

The B300 includes NVLink interconnect support while the Quadro P6000 relies on PCIe 3.0.

Can the Quadro P6000 run FP16 workloads?▾

No FP16 performance figure is published for the Quadro P6000 whereas the B300 lists 2250 TFLOPS FP16 dense.

Which is cheaper to rent, the B300 or the Quadro P6000?▾

Cloud rental prices for both the B300 and Quadro P6000 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 B300 have compared to the Quadro P6000?▾

The B300 has 262 to 288 GB of HBM3e memory. The Quadro P6000 has 24 GB of GDDR5X memory.

Can I find B300 and Quadro P6000 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 B300 and the Quadro P6000?▾

The B300 uses the Blackwell Ultra architecture (2025) while the Quadro P6000 uses Pascal (2016). The B300 has 262-288 GB of HBM3e at 8,000 GB/s; the Quadro P6000 has 24 GB of GDDR5X at 432 GB/s, so the B300 has 18.5x the memory bandwidth of the Quadro P6000.

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How this page is made

  • Specifications come from the NVIDIA, AMD and Intel datasheets for the B300 and the Quadro P6000. Dense and sparse throughput are listed separately.
  • Prices and availability are live: every offer shown is an in-stock, on-demand listing from a provider we track, rechecked every minute.
  • The written comparison (overview, performance notes, when to choose each card, verdict, use cases and FAQ) was drafted with an AI model from the specification table above and passed an automated check that rejects any figure not in that table. It was last generated on . It contains no prices; those are always read live.
  • Read how we collect the data, or report an error on this page.

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