GPU comparison

A16 vs Quadro RTX 5000

Specifications and current cloud pricing, side by side.

AmperevsTuringUpdated 34 days ago

The Quadro RTX 5000 wins for the most common use case of dense tensor workloads because its 89.2 TFLOPS dense FP16 and 448 GB/s bandwidth exceed the corresponding 17.9 TFLOPS dense FP16 and 200 GB/s figures on the A16 by substantial margins.

A16 listed from $0.06/GPU/hrQuadro RTX 5000 listed from $0.82/GPU/hr

Right now, from live stock

  • Cheapest right now: Quadro RTX 5000 at $0.82/hr on Paperspace

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  • Most providers in stock: Quadro RTX 5000 (1)

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Specifications Compared

SpecA16Quadro RTX 5000
TDP250W230W
VRAM16 GB16 GB
CUDA Cores1,2803,072
Memory TypeGDDR6GDDR6
ArchitectureAmpereTuring
FP16 (dense)17.9 TFLOPS89.2 TFLOPS
Form FactorsPCIePCIe
INT8 (dense)35.9 TOPS178.4 TOPS
InterconnectPCIe 4.0NVLink, PCIe 3.0
Tensor Cores40384
FP32 Performance4.5 TFLOPS11.2 TFLOPS
Memory Bandwidth200 GB/s448 GB/s
FP16 (with sparsity)35.9 TFLOPSNot published
INT8 (with sparsity)71.8 TOPSNot published

Performance Analysis

Dense FP16 performance reaches 17.9 TFLOPS on the A16 compared with 89.2 TFLOPS dense FP16 on the Quadro RTX 5000. This gap means the Quadro RTX 5000 processes matrix operations more than five times faster in dense FP16 workloads such as certain inference steps. FP32 figures of 4.5 TFLOPS versus 11.2 TFLOPS produce a similar ratio and affect training throughput directly. Memory bandwidth of 200 GB/s on the A16 versus 448 GB/s on the Quadro RTX 5000 limits sustainable batch sizes on the A16 during data movement heavy phases. When sparsity is enabled the A16 reaches 35.9 TFLOPS FP16 with sparsity while the Quadro RTX 5000 lists no sparsity figure for FP16.

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.

A16

A16 is not offered on-demand by any provider we track right now. See the A16 rental page for last-seen listed prices and a price alert.

Quadro RTX 5000

ProviderRegionGPUsPer GPU / hrInstance / hrDeploy
Paperspaceny21$0.82—Deploy

1 provider in stock, 2 offers (cheapest per provider shown). All Quadro RTX 5000 offers, price history and alerts

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When to Choose the A16

The A16 suits environments where PCIe 4.0 interconnect and Ampere architecture features matter more than raw dense FP16 throughput. Its 250W TDP pairs with systems that already accommodate higher power draw while its 35.9 TOPS dense INT8 supports quantized workloads that do not require the 178.4 TOPS dense INT8 of the Quadro RTX 5000.

When to Choose the Quadro RTX 5000

Its NVLink support enables multi GPU scaling that the A16 lacks and its 11.2 TFLOPS FP32 accelerates scientific kernels that rely on dense floating point operations.

Use Cases

LLM Training
Quadro RTX 5000

The Quadro RTX 5000 supplies 89.2 TFLOPS dense FP16 and 11.2 TFLOPS FP32 that exceed the A16 values and support faster iteration on large matrix multiplies.

LLM Inference
Quadro RTX 5000

Dense FP16 at 89.2 TFLOPS and 178.4 TOPS dense INT8 on the Quadro RTX 5000 enable higher token throughput than the A16 equivalents of 17.9 TFLOPS dense FP16 and 35.9 TOPS dense INT8.

Fine-tuning
Quadro RTX 5000

Higher memory bandwidth of 448 GB/s on the Quadro RTX 5000 sustains larger batch sizes during gradient updates compared with 200 GB/s on the A16.

Stable Diffusion
Quadro RTX 5000

The Quadro RTX 5000 delivers 89.2 TFLOPS dense FP16 that accelerates diffusion steps beyond the 17.9 TFLOPS dense FP16 available on the A16.

Scientific Computing
Quadro RTX 5000

FP32 performance of 11.2 TFLOPS on the Quadro RTX 5000 exceeds the 4.5 TFLOPS on the A16 and benefits precision sensitive simulations.

Frequently Asked Questions

Which GPU offers higher dense FP16 performance?▾

The Quadro RTX 5000 lists 89.2 TFLOPS dense FP16 while the A16 lists 17.9 TFLOPS dense FP16.

How does memory bandwidth differ between the A16 and Quadro RTX 5000?▾

The A16 provides 200 GB/s while the Quadro RTX 5000 provides 448 GB/s.

What FP32 performance does each card deliver?▾

The A16 reaches 4.5 TFLOPS FP32 and the Quadro RTX 5000 reaches 11.2 TFLOPS FP32.

Do both GPUs support the same interconnect options?▾

The A16 uses PCIe 4.0 while the Quadro RTX 5000 supports NVLink in addition to PCIe 3.0.

Which card has the lower TDP rating?▾

The Quadro RTX 5000 lists 230W TDP compared with 250W on the A16.

Can sparsity be applied to FP16 on both models?▾

The A16 lists 35.9 TFLOPS FP16 with sparsity while the Quadro RTX 5000 publishes no sparsity figure for FP16.

Which is cheaper to rent, the A16 or the Quadro RTX 5000?▾

Cloud rental prices for both the A16 and Quadro RTX 5000 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 A16 have compared to the Quadro RTX 5000?▾

The A16 has 16 GB of GDDR6 memory. The Quadro RTX 5000 has 16 GB of GDDR6 memory.

Can I find A16 and Quadro RTX 5000 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 A16 and the Quadro RTX 5000?▾

The A16 uses the Ampere architecture (2021) while the Quadro RTX 5000 uses Turing (2018). The Quadro RTX 5000 delivers 5.0x the dense FP16 throughput (89.2 vs 17.9 TFLOPS, both without sparsity) and 2.2x the memory bandwidth of the A16.

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How this page is made

  • Specifications come from the NVIDIA, AMD and Intel datasheets for the A16 and the Quadro RTX 5000. 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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