GPU comparison

A16 vs RTX 5070

Specifications and current cloud pricing, side by side.

AmperevsBlackwellUpdated 34 days ago

The RTX 5070 wins for the most common use case of LLM inference because its FP16 dense performance of 61.7 TFLOPS and memory bandwidth of 672 GB/s exceed the corresponding A16 figures of 17.9 TFLOPS and 200 GB/s while both GPUs share the same 250 W TDP.

A16 listed from $0.06/GPU/hrRTX 5070 listed from $0.17/GPU/hr

Specifications Compared

SpecA16RTX 5070
TDP250W250W
VRAM16 GB12-16 GB
CUDA Cores1,2806,144
FP4 (dense)Not published493.9 TFLOPS
FP8 (dense)Not published123.5 TFLOPS
Memory TypeGDDR6GDDR7
ArchitectureAmpereBlackwell
FP16 (dense)17.9 TFLOPS61.7 TFLOPS
Form FactorsPCIePCIe
INT8 (dense)35.9 TOPS246.9 TOPS
InterconnectPCIe 4.0PCIe 5.0
Tensor Cores40192
FP32 Performance4.5 TFLOPS30.9 TFLOPS
Memory Bandwidth200 GB/s672 GB/s
FP4 (with sparsity)Not published987.8 TFLOPS
FP8 (with sparsity)Not published246.9 TFLOPS
FP16 (with sparsity)35.9 TFLOPS123.5 TFLOPS
INT8 (with sparsity)71.8 TOPS493.9 TOPS

Performance Analysis

The FP16 dense figure of 17.9 TFLOPS on the A16 versus 61.7 TFLOPS on the RTX 5070 indicates the RTX 5070 processes matrix operations in half precision at a higher rate for both training and inference steps. The FP32 figure of 4.5 TFLOPS on the A16 versus 30.9 TFLOPS on the RTX 5070 shows a similar advantage for single precision workloads. Memory bandwidth of 200 GB/s on the A16 versus 672 GB/s on the RTX 5070 allows the RTX 5070 to support larger batch sizes during data movement between memory and compute units. When comparing FP16 with sparsity the A16 reaches 35.9 TFLOPS while the RTX 5070 reaches 123.5 TFLOPS so the RTX 5070 maintains the lead in sparse tensor operations as well.

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.

RTX 5070

RTX 5070 is not offered on-demand by any provider we track right now. See the RTX 5070 rental page for last-seen listed prices and a price alert.

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When to Choose the A16

The A16 suits environments that require exactly 16 GB of dedicated GDDR6 memory and PCIe 4.0 compatibility with existing server infrastructure. Its INT8 dense rating of 35.9 TOPS supports inference tasks that do not demand the higher throughput numbers of newer cards. The 250 W TDP matches the RTX 5070 yet the older architecture may integrate more readily into systems without PCIe 5.0 support.

When to Choose the RTX 5070

Its FP32 rating of 30.9 TFLOPS accelerates scientific computing kernels that rely on single precision arithmetic. The PCIe 5.0 interconnect further reduces data transfer latency in multi GPU setups compared to the A16 PCIe 4.0 interconnect.

Use Cases

LLM Training
RTX 5070

The RTX 5070 FP16 dense rating of 61.7 TFLOPS exceeds the A16 rating of 17.9 TFLOPS and its 672 GB/s bandwidth supports larger batches.

LLM Inference
RTX 5070

The RTX 5070 FP16 dense rating of 61.7 TFLOPS and INT8 dense rating of 246.9 TOPS exceed the A16 ratings of 17.9 TFLOPS and 35.9 TOPS.

Fine-tuning
RTX 5070

The RTX 5070 FP16 with sparsity rating of 123.5 TFLOPS exceeds the A16 rating of 35.9 TFLOPS for gradient updates.

Stable Diffusion
RTX 5070

The RTX 5070 memory bandwidth of 672 GB/s and FP16 dense rating of 61.7 TFLOPS exceed the A16 figures for image generation steps.

Scientific Computing
RTX 5070

The RTX 5070 FP32 rating of 30.9 TFLOPS exceeds the A16 rating of 4.5 TFLOPS for precision sensitive simulations.

Frequently Asked Questions

What is the FP16 dense performance difference between the A16 and RTX 5070?▾

The A16 lists FP16 dense performance at 17.9 TFLOPS while the RTX 5070 lists 61.7 TFLOPS so the RTX 5070 provides higher throughput for half precision workloads.

How does memory bandwidth compare on the A16 versus the RTX 5070?▾

The A16 provides 200 GB/s bandwidth while the RTX 5070 provides 672 GB/s bandwidth allowing the RTX 5070 to move data faster during compute operations.

Do the A16 and RTX 5070 share the same power rating?▾

Both the A16 and the RTX 5070 list a TDP of 250 W so power draw remains identical under full load.

Which GPU offers higher INT8 dense performance?▾

The RTX 5070 lists INT8 dense performance at 246.9 TOPS while the A16 lists 35.9 TOPS so the RTX 5070 handles integer workloads at a higher rate.

What interconnect does each GPU use?▾

The A16 uses PCIe 4.0 interconnect while the RTX 5070 uses PCIe 5.0 interconnect for faster host communication.

Which is cheaper to rent, the A16 or the RTX 5070?▾

Cloud rental prices for both the A16 and RTX 5070 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 RTX 5070?▾

The A16 has 16 GB of GDDR6 memory. The RTX 5070 has 12 to 16 GB of GDDR7 memory.

Can I find A16 and RTX 5070 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 RTX 5070?▾

The A16 uses the Ampere architecture (2021) while the RTX 5070 uses Blackwell (2025). The RTX 5070 delivers 3.4x the dense FP16 throughput (61.7 vs 17.9 TFLOPS, both without sparsity) and 3.4x the memory bandwidth of the A16.

Rent these GPUs

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Related comparisons

How this page is made

  • Specifications come from the NVIDIA, AMD and Intel datasheets for the A16 and the RTX 5070. 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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