Rent an NVIDIA V100 32GB from $0.06 per GPU-hour
NVIDIA V100 32GB price per hour: $0.06 per GPU-hour on spot, $0.09 on-demand, $0.06 reserved, billed by the minute. Volta with 32 GB and NVLink. No integer tensor cores and no FP8, so it is an FP16 machine — but a cheap one for training smaller models and for legacy CUDA code.
Billed per started minute. 128 GB of GPU memory on a 4× node. Persistent storage $0.08 per GB-month. No egress fees.
- GPU memory
- 32GBHBM2
- Bandwidth
- 900GB/sSets token throughput on inference
- Node sizes
- 1× · 2× · 4×Same price per GPU at every size
- Reclaim rate
- <5%Spot instances reclaimed over 30 days
What you get with each V100 node.
| Node | GPU memory | vCPU | RAM | Local NVMe | Spot | On-demand | Action |
|---|---|---|---|---|---|---|---|
| 1× V100 | 32 GB | 8 | 64 GB | 500 GB | $0.06/h | $0.09/h | Configure |
| 2× V100 | 64 GB | 16 | 128 GB | 1 TB | $0.12/h | $0.18/h | Configure |
| 4× V100 | 128 GB | 32 | 256 GB | 2 TB | $0.24/h | $0.36/h | Configure |
GPU-to-GPU link: NVLink 2, 300 GB/s. Local NVMe is scratch space wiped when the instance ends; keep anything you need on a persistent disk.
32 V100 GPUs free right now.
Straight from the capacity pool the console books against. Prices are identical in every region — pick the one closest to your data.
A region with zero free GPUs still accepts reserved capacity requests — we hold hardware for a term rather than sell what is already taken.
What fits in 32 GB — and what it costs per hour.
Weights need about 2 GB per billion parameters at FP16 / BF16. We keep 20% of the memory free for activations, the KV cache and the CUDA context, then take the smallest node that still fits.
| Open model | Parameters | FP16 / BF16node · spot price |
|---|---|---|
| Llama 3.1 8BThe default small model for fine-tuning and agents | 8B | 1× $0.06/h |
| Qwen3 14BMid-size dense Qwen3 | 14.8B | 2× $0.12/h |
| gpt-oss-20bSmall open-weight reasoning model for local and edge serving | 21B | 2× $0.12/h |
| Gemma 4 31BLargest dense Gemma 4, multimodal, 256K context | 31.3B | 4× $0.24/h |
| Qwen3.6 35B A3BSmall hybrid-attention mixture of experts | 35B | 4× $0.24/h |
| Llama 3.3 70BThe common 70B baseline (same size and layout as Llama 3.1 70B) | 70.6B | over 4× |
| gpt-oss-120bOpen-weight reasoning model, mixture of experts, tool use | 117B | over 4× |
| Qwen3 235B A22BFlagship Qwen3 mixture of experts, the 2507 checkpoint | 235B | over 4× |
| DeepSeek R1Reasoning model, the R1-0528 checkpoint | 671B | over 4× |
Each model links to its full sizing: KV cache by context length and every GPU that runs it — GPU requirements for 64 open models.
Real usage depends on context length, batch size and the serving engine: a long context can add tens of gigabytes of KV cache. Treat the table as the floor, not the ceiling — and if a job is close to the limit, take the next node size or quantise one step further.
What a dollar buys on a V100.
Ranked 4 of 21 data-center models in this catalogue on cost per gigabyte of GPU memory.
GPU memory you get for $1.00 of spot time, per hour.
Bandwidth decides token throughput far more often than raw FLOPS.
Spot price divided by published FP16 tensor throughput.
One GPU on spot, billed per minute, storage excluded.
Against the rest of the market
7 providers · September 2026- Median on-demand elsewhere
- $0.21Our on-demand is 57% below it
- Cheapest on-demand seen
- $0.12Our on-demand $0.09 is 25% below it
- Cheapest spot seen
- $0.51Our spot $0.06 is 88% below it
- 24 hours on one GPU
- $1.44 on spot$2.16 on-demand · $2.88 at the cheapest rate found elsewhere
Index built from published prices for the same GPU across 102 providers (provider pricing pages and public price indexes), September 2026. How the guarantee is enforced.
V100 32GB price per hour at 9 other providers.
The lowest published on-demand rate we recorded at each provider, cheapest first: $0.12 to $3.90 per GPU-hour, with a median of $0.55. Every row links to its source; a provider without a published price is left out rather than estimated.
| # | Provider | On-demandper GPU-hour | Spot | 730 h | Source |
|---|---|---|---|---|---|
| — | OnlineGPUthis site · how the price is set | $0.09 | $0.06 | $65.70 | pricing page |
| 1 | GPU.airecorded 15 Sep 2026 | $0.12 | not published | $87.60 | getdeploying.com |
| 2 | HyperAIrecorded 15 Sep 2026 | $0.14 | not published | $102.20 | getdeploying.com |
| 3 | Geoddrecorded 15 Sep 2026 | $0.16 | not published | $116.80 | getdeploying.com |
| 4 | Akash Networkrecorded 15 Sep 2026 | $0.21 | not published | $153.30 | console.akash.network |
| 5 | Cyfuture AIrecorded 15 Sep 2026 | $0.55 | not published | $401.50 | getdeploying.com |
| 6 | OVHcloudrecorded 15 Sep 2026 | $0.88 | not published | $642.40 | getdeploying.com |
| 7 | Paperspacerecorded 15 Sep 2026 | $2.30 | not published | $1,679.00 | shadeform.com |
| 8 | Runcraterecorded 15 Sep 2026 | $2.57 | not published | $1,876.10 | getdeploying.com |
| 9 | AWSrecorded 15 Sep 2026 | $3.90 | $0.51 | $2,848.46 | b0.p.awsstatic.com |
Recorded 15 September 2026 from published price pages (provider pricing pages and public price indexes), compute only: storage, egress and taxes excluded. Prices move — if a row is out of date, send us the link and it is corrected.
What people run on a V100 32GB.
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.
Anything that can checkpoint
On the spot tier this model is 33% below its own on-demand price, with a 2-minute notice before a reclaim.
NVIDIA V100 32GB, as published by NVIDIA.
Taken from the vendor datasheet. Where a figure is not published, the row is absent rather than estimated.
- Vendor
- NVIDIA
- Architecture
- Volta (2018)
- Segment
- Datacenter
- Memory
- 32 GB HBM2
- Memory bandwidth
- 900 GB/s
- FP16 / BF16 tensor
- 125 TFLOPS
- FP32
- 16 TFLOPS
- CUDA cores
- 5,120
- Board power
- 300 W
- Form factor
- SXM2
- Interconnect
- NVLink 2, 300 GB/s
- Multi-instance (MIG)
- Not available
- 8-bit float (FP8)
- Not supported — use FP16 or integer quantisation
Source: images.nvidia.com · verified against the vendor document
Software that runs on it
8 templatesPre-built environments, pulled on the node before you land on it. Or bring any OCI image from a public or private registry.
On the spot tier
<5% reclaimed · 30 d- 2 minutes of notice on the metadata endpoint, a webhook and the console
- The instance is stopped, not deleted — disk and IP stay attached
- Auto-relaunch on the next free V100, or switch the same disk to on-demand
- You save $0.72 a day per GPU against on-demand
If the V100 is not the right fit.
Next step up in memory: 40 GB instead of 32 GB
V100 16GB 16 GB HBM2 · Volta $0.04/h spotSame Volta generation
A100 PCIe 80GB 80 GB HBM2e · Ampere $0.09/h spotFaster memory: 1,935 GB/s against 900 GB/s
A100 SXM 80GB 80 GB HBM2e · Ampere $0.19/h spotFaster memory: 2,039 GB/s against 900 GB/s
Or put two of them side by side: V100 vs A100 40GB · V100 vs V100 16GB · V100 vs A100 PCIe
V100 32GB — the questions that come up
How much does a V100 32GB cost per hour?
Spot is $0.06 per GPU-hour and on-demand is $0.09, both billed per minute — every started minute costs the hourly price divided by 60, so $0.0010 on spot. Reserved capacity is $0.06 per GPU-hour on a monthly commitment. Storage and egress are not included in that rate: persistent disks are $0.08 per GB-month and there are no egress fees.
How many GPUs can I put in one instance?
Node sizes are 1×, 2×, 4× — up to 4 V100 32GB GPUs in a single virtual machine, with CPU, RAM and local NVMe scaled with the GPU count. The price per GPU is identical at every node size.
Can it run a 70B model?
Not on a single node of this model: at FP16 a 70B model needs about 140 GB of memory for the weights alone, more than 4× 32 GB leaves free. Quantised to 4 bits it needs about 35 GB — check the memory table above — or pick a model with more memory per GPU.
Which regions have it?
Available now in US East (Virginia), EU Central (Frankfurt). Prices are identical in every region; pick the one closest to your data.
How often is a spot V100 reclaimed?
Over the trailing 30 days, <5% of spot instances on this model were reclaimed. You get a 2-minute notice on the metadata endpoint, through a webhook and in the console; the instance is then stopped, never deleted, and the persistent disk stays attached.
Anything else about this model? Ask an engineer — the same people run the nodes. See also all prices, how we compare with 41 other providers and how to pay in crypto.
A V100 32GB for $0.06 an hour, running in under 60 seconds.
Prepaid in crypto, pay as you go: no card, no contract, no minimum commitment. Add credit, launch, stop whenever you want.
Billed per minute from the moment the instance is reachable. Minimum credit $30, no subscription. 32 V100 GPUs available right now.