GPU comparison

Quadro RTX 4000 vs RTX A6000

Specifications and current cloud pricing, side by side.

TuringvsAmpereUpdated 34 days ago

The RTX A6000 serves as the stronger choice for the most common use case of LLM inference because its 48 GB memory and 154.8 TFLOPS dense FP16 exceed the corresponding 8 GB and 57 TFLOPS figures of the Quadro RTX 4000 by substantial margins.

Quadro RTX 4000 from $0.56/GPU/hrRTX A6000 from $0.44/GPU/hr

Right now, from live stock

  • Cheapest right now: RTX A6000 at $0.44/hr on LeaderGPU

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  • Most providers in stock: RTX A6000 (4)

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  • Best $ per TFLOPS FP16 dense right now: RTX A6000 ($0.0029 per TFLOPS-hour at 154.8 TFLOPS)

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Specifications Compared

SpecQuadro RTX 4000RTX A6000
TDP125W300W
VRAM8 GB48 GB
CUDA Cores2,30410,752
Memory TypeGDDR6GDDR6
ArchitectureTuringAmpere
FP16 (dense)57 TFLOPS154.8 TFLOPS
Form FactorsPCIePCIe
INT8 (dense)Not published309.7 TOPS
InterconnectPCIe 3.0NVLink, PCIe 4.0
Tensor Cores288336
FP32 Performance7.1 TFLOPS38.7 TFLOPS
Memory Bandwidth416 GB/s768 GB/s
FP16 (with sparsity)Not published309.6 TFLOPS
INT8 (with sparsity)Not published619.4 TOPS

Performance Analysis

The dense FP16 performance reaches 154.8 TFLOPS on the RTX A6000 compared with 57 TFLOPS on the Quadro RTX 4000. This gap means training and inference steps complete in fewer cycles when dense FP16 operations dominate the workload. The FP32 figure of 38.7 TFLOPS on the RTX A6000 versus 7.1 TFLOPS on the Quadro RTX 4000 produces a similar acceleration pattern for precision sensitive computations. Memory bandwidth of 768 GB/s on the RTX A6000 versus 416 GB/s on the Quadro RTX 4000 permits larger batch sizes before memory capacity limits are reached. The 48 GB VRAM on the RTX A6000 versus 8 GB on the Quadro RTX 4000 further extends the feasible model scale for both training and inference sequences.

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 RTX 4000

ProviderRegionGPUsPer GPU / hrInstance / hrDeploy
Paperspaceams11$0.56—Deploy

1 provider in stock, 5 offers (cheapest per provider shown). All Quadro RTX 4000 offers, price history and alerts

RTX A6000

ProviderRegionGPUsPer GPU / hrInstance / hrDeploy
LeaderGPUThe Netherlands8$0.44$3.54Deploy
QuantaCloudus-midwest-12$0.48$0.96Deploy
Massed Computeus-central-22$0.55$1.10Deploy
Paperspaceny22$1.89$3.78Deploy

4 providers in stock, 39 offers (cheapest per provider shown). All RTX A6000 offers, price history and alerts

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When to Choose the Quadro RTX 4000

The Quadro RTX 4000 fits environments constrained by a 125W TDP limit where power delivery is restricted. Tasks that remain within the 8 GB VRAM capacity can utilize its 57 TFLOPS dense FP16 rating without requiring additional cooling infrastructure.

When to Choose the RTX A6000

The RTX A6000 fits workloads that require the 48 GB VRAM capacity to hold large models during training or inference. Its 154.8 TFLOPS dense FP16 rating combined with 768 GB/s bandwidth supports higher throughput on memory intensive operations compared with the Quadro RTX 4000.

Use Cases

LLM Training
RTX A6000

The 48 GB VRAM on the RTX A6000 accommodates larger models than the 8 GB on the Quadro RTX 4000.

LLM Inference
RTX A6000

The 154.8 TFLOPS dense FP16 rating on the RTX A6000 exceeds the 57 TFLOPS on the Quadro RTX 4000 for faster token generation.

Fine-tuning
RTX A6000

The 768 GB/s bandwidth on the RTX A6000 supports larger batch sizes than the 416 GB/s on the Quadro RTX 4000.

Stable Diffusion
RTX A6000

The 48 GB VRAM on the RTX A6000 holds higher resolution images compared with the 8 GB limit on the Quadro RTX 4000.

Scientific Computing
RTX A6000

The 38.7 TFLOPS FP32 on the RTX A6000 provides greater throughput than the 7.1 TFLOPS on the Quadro RTX 4000 for simulation workloads.

Frequently Asked Questions

What are the dense FP16 ratings for both GPUs?▾

The Quadro RTX 4000 achieves 57 TFLOPS dense FP16. The RTX A6000 achieves 154.8 TFLOPS dense FP16.

Which GPU has higher memory bandwidth?▾

The RTX A6000 reaches 768 GB/s while the Quadro RTX 4000 reaches 416 GB/s. Higher bandwidth reduces data movement bottlenecks during large tensor operations.

What TDP values are listed for these cards?▾

The Quadro RTX 4000 lists a 125W TDP. The RTX A6000 lists a 300W TDP.

Do both GPUs support the same interconnect options?▾

The Quadro RTX 4000 uses PCIe 3.0. The RTX A6000 supports NVLink and PCIe 4.0 in addition to PCIe connectivity.

Which is cheaper to rent, the Quadro RTX 4000 or the RTX A6000?▾

Cloud rental prices for both the Quadro RTX 4000 and RTX A6000 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 RTX 4000 have compared to the RTX A6000?▾

The Quadro RTX 4000 has 8 GB of GDDR6 memory. The RTX A6000 has 48 GB of GDDR6 memory.

Can I find Quadro RTX 4000 and RTX A6000 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 RTX 4000 and the RTX A6000?▾

The Quadro RTX 4000 uses the Turing architecture (2018) while the RTX A6000 uses Ampere (2020). The RTX A6000 delivers 2.7x the dense FP16 throughput (154.8 vs 57 TFLOPS, both without sparsity) and 1.8x the memory bandwidth of the Quadro RTX 4000.

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How this page is made

  • Specifications come from the NVIDIA, AMD and Intel datasheets for the Quadro RTX 4000 and the RTX A6000. 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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