GPU comparison

Quadro P6000 vs RTX 5060

Specifications and current cloud pricing, side by side.

PascalvsBlackwellUpdated 33 days ago

The RTX 5060 wins for the most common use case of dense FP32 workloads because its 19.2 TFLOPS exceeds the 12.6 TFLOPS of the Quadro P6000 while operating at 145W instead of 250W and providing a newer interconnect standard.

Quadro P6000 from $1.10/GPU/hrRTX 5060 from $0.18/GPU/hr

Right now, from live stock

  • Cheapest right now: RTX 5060 at $0.18/hr on Vast.ai

    Deploy
  • Most providers in stock: Quadro P6000 and RTX 5060 (1 each)

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Specifications Compared

SpecQuadro P6000RTX 5060
TDP250W145W
VRAM24 GB8-16 GB
CUDA Cores3,8403,840
Memory TypeGDDR5XGDDR7
ArchitecturePascalBlackwell
Form FactorsPCIePCIe
InterconnectPCIe 3.0PCIe 5.0
Tensor CoresNot published120
FP32 Performance12.6 TFLOPS19.2 TFLOPS
Memory Bandwidth432 GB/s448 GB/s
FP4 (with sparsity)Not published614 TFLOPS

Performance Analysis

Dense FP32 performance stands at 12.6 TFLOPS for the Quadro P6000 and 19.2 TFLOPS for the RTX 5060. This 1.52 times higher dense FP32 figure on the RTX 5060 supports faster execution of compute kernels that rely on single precision arithmetic during training and inference steps. Memory bandwidth of 432 GB/s on the Quadro P6000 versus 448 GB/s on the RTX 5060 produces comparable data movement rates that limit maximum batch sizes in bandwidth constrained scenarios. The 24 GB VRAM on the Quadro P6000 versus the 8-16 GB range on the RTX 5060 determines the largest model sizes that fit without swapping. TDP of 250W on the Quadro P6000 versus 145W on the RTX 5060 translates to different cooling and power infrastructure requirements for sustained dense FP32 workloads. The FP4 figure with sparsity reaches 614 TFLOPS on the RTX 5060 only and cannot be compared directly to any published value on the Quadro P6000.

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.

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

RTX 5060

ProviderRegionGPUsPer GPU / hrInstance / hrDeploy
Vast.aiGermany, DE1$0.18—Deploy

1 provider in stock, 3 offers (cheapest per provider shown). All RTX 5060 offers, price history and alerts

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When to Choose the Quadro P6000

The Quadro P6000 suits workloads that require the full 24 GB GDDR5X capacity for large datasets or models that exceed the 8-16 GB limit of the RTX 5060. Its 12.6 TFLOPS dense FP32 remains adequate when memory volume outweighs the need for the 19.2 TFLOPS available on the newer card.

When to Choose the RTX 5060

Its PCIe 5.0 interconnect and 448 GB/s bandwidth support efficient operation in power constrained environments where the 24 GB VRAM of the older card is not required.

Use Cases

LLM Training
Quadro P6000

The Quadro P6000 provides 24 GB VRAM that accommodates larger models than the 8-16 GB range on the RTX 5060.

LLM Inference
RTX 5060

The RTX 5060 delivers 19.2 TFLOPS dense FP32 which exceeds the 12.6 TFLOPS on the Quadro P6000 at lower 145W TDP.

Fine-tuning
Quadro P6000

The Quadro P6000 supplies 24 GB GDDR5X that supports fine-tuning batches larger than those possible with 8-16 GB on the RTX 5060.

Stable Diffusion
RTX 5060

Scientific Computing
Either

Both cards handle dense FP32 tasks with the Quadro P6000 at 12.6 TFLOPS and 24 GB versus the RTX 5060 at 19.2 TFLOPS and 8-16 GB.

Frequently Asked Questions

What is the FP32 performance difference between these GPUs?▾

The Quadro P6000 reaches 12.6 TFLOPS dense FP32 and the RTX 5060 reaches 19.2 TFLOPS dense FP32.

Which GPU uses less power?▾

The RTX 5060 operates at 145W TDP while the Quadro P6000 operates at 250W TDP.

What memory bandwidth do these cards provide?▾

The Quadro P6000 provides 432 GB/s and the RTX 5060 provides 448 GB/s.

Which interconnect does each GPU support?▾

The Quadro P6000 supports PCIe 3.0 and the RTX 5060 supports PCIe 5.0.

Which is cheaper to rent, the Quadro P6000 or the RTX 5060?▾

Cloud rental prices for both the Quadro P6000 and RTX 5060 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 Quadro P6000 have compared to the RTX 5060?▾

The Quadro P6000 has 24 GB of GDDR5X memory. The RTX 5060 has 8 to 16 GB of GDDR7 memory.

Can I find Quadro P6000 and RTX 5060 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 Quadro P6000 and the RTX 5060?▾

The Quadro P6000 uses the Pascal architecture (2016) while the RTX 5060 uses Blackwell (2025). The Quadro P6000 has 24 GB of GDDR5X at 432 GB/s; the RTX 5060 has 8-16 GB of GDDR7 at 448 GB/s, so the RTX 5060 has 1.0x the memory bandwidth of the Quadro P6000.

Rent these GPUs

Each GPU page lists every current on-demand offer by provider, per GPU-hour, updated every minute.

Related comparisons

How this page is made

  • Specifications come from the NVIDIA, AMD and Intel datasheets for the Quadro P6000 and the RTX 5060. 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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