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Comparison

RTX A5000 vs RTX A4000

Both run on the same nodes, the same templates and the same tiers here — so the choice comes down to memory, bandwidth and price. Every figure below is from the catalogue or the vendor datasheet.

RTX A5000
$0.06/h24 GB · Ampere · 48 available
RTX A4000
$0.03/h16 GB · Ampere · 48 available
Price gap
50%On spot, per GPU-hour
Over 100 h
$3.00Difference for the same GPU-hours
In short

What actually separates them.

Four differences that change a decision, computed from the numbers rather than asserted.

Bigger models fit on the RTX A5000

24 GB against 16 GB. At FP16 that is about 9B parameters on one GPU, against 6B.

The RTX A4000 costs 50% less per hour

$0.03 against $0.06 on spot — $3.00 of difference over 100 GPU-hours.

Token generation is faster on the RTX A5000

768 GB/s against 448 GB/s. Inference reads the whole model from memory for every token, so bandwidth, not FLOPS, usually sets the ceiling.

More memory per dollar on the RTX A4000

533 GB per dollar per hour against 400 GB. The usual tie-breaker when both cards fit the job.

Side by side

Every figure we hold on both cards.

A row is marked only when both values exist and one is genuinely better. RTX A5000 leads on 4 rows, RTX A4000 on 4.

  RTX A5000 RTX A4000
GPU memoryDecides which models fit at all 24 GB GDDR6 16 GB GDDR6
Memory bandwidthSets token throughput on inference 768 GB/s 448 GB/s
FP32 28 TFLOPS 19 TFLOPS
8-bit float (FP8)Halves the memory a model needs, where the stack supports it Not supported Not supported
Architecture Ampere (2021) Ampere (2021)
Board powerLower is cheaper to run at scale — for us, not for your bill 230 W 140 W
GPU-to-GPU linkOnly matters for multi-GPU training NVLink PCIe only
Node sizes 1×, 2×, 4× 1×, 2×, 4×
Spot price $0.06/h $0.03/h
On-demand price $0.09/h $0.05/h
Memory per dollarGPU memory per $1 of spot time, per hour 400 GB 533 GB
30-day reclaim rateShare of spot instances reclaimed <5% <5%
Available now 48 GPUs 48 GPUs

Specifications come from each vendor's datasheet — linked on the RTX A5000 page and the RTX A4000 page. Prices are ours, per GPU-hour, billed per minute.

What fits

The same models, on one GPU of each.

Weights only, with 20% of the memory kept free for activations and the KV cache. A cross means one GPU is not enough — the model page has the multi-GPU arithmetic.

Model Precision RTX A5000 24 GB RTX A4000 16 GB
Llama 3.1 8B8B parameters FP16 · 16 GB Fits Needs 2× node
INT4 · 4 GB Fits Fits
Qwen2.5 32B32B parameters FP16 · 64 GB Needs 4× node Needs more than one node
INT4 · 16 GB Fits Needs 2× node
Llama 3.3 70B70B parameters FP16 · 140 GB Needs more than one node Needs more than one node
INT4 · 35 GB Needs 2× node Needs 4× node
Mixtral 8x22B141B parameters FP16 · 282 GB Needs more than one node Needs more than one node
INT4 · 71 GB Needs 4× node Needs more than one node
Cost

The same 100 GPU-hours on each.

Compute only, billed per minute. Storage is $0.08 per GB-month on either card.

 RTX A5000RTX A4000
One hour, spot$0.06$0.03
One day, spot$1.44$0.72
100 GPU-hours, spot$6.00$3.00
100 GPU-hours, on-demand$9.00$5.00
A month, reserved$43.80$21.90

Take the RTX A5000 when…

  • Fine-tuning small models — LoRA on 7B–13B models, and full fine-tuning below 3B.
  • Image and video generation — Diffusion pipelines run entirely in memory at this capacity.
  • Multi-GPU jobs over NVLink — GPU-to-GPU traffic stays off the PCIe bus, which is what makes tensor and pipeline parallelism worth it.

Full RTX A5000 page

Take the RTX A4000 when…

  • Quantised inference — Small and medium models in 4-bit or 8-bit form, with the whole model resident in memory.
  • Computer vision and batch jobs — Detection, classification, embeddings and transcoding at a very low hourly rate.
  • Anything that can checkpoint — On the spot tier this model is 40% below its own on-demand price, with a 2-minute notice before a reclaim.

Full RTX A4000 page

FAQ

RTX A5000 or RTX A4000?

Which is cheaper, the RTX A5000 or the RTX A4000?

The RTX A4000, at $0.03 per GPU-hour on spot against $0.06 — 50% less. On-demand: $0.05 against $0.09.

Which one should I take for inference?

Take the one that holds the model with room for the KV cache, then the one with more memory bandwidth. Here that is the RTX A5000 on capacity (24 GB) and the RTX A5000 on bandwidth.

Can I run both on the same job?

Not inside one instance — a node holds GPUs of a single model. You can run two instances in parallel, on the same persistent volume in turn, or split the work: a big card for the model that needs capacity, a cheap one for the parts that do not.

Other comparisons: the full list · all 47 models

Get started

Try both for less than the price of deciding.

An hour on each costs $0.09 on spot. Nothing renews, and your disk moves between them.

Billed per minute from the moment the instance is reachable. Minimum credit $40, no subscription.