Nvidia RTX 4000 Ada

Nvidia RTX 4000 Ada

Single-slot professional card for desktop AI, rendering, and compute workloads.

Arch
Ada Lovelace
Memory
20 GB GDDR6
Bandwidth
360 GB/s
Released
Q3 2023

Price history

Weekly median price per GPU per hour

Last 12 months
Aggregating historical prices...

At a glance Updated 20 minutes ago

Cheapest in stock
$0.20 /GPU/hr
on-demand · 1x · GPU.ai
Median price (current)
$0.24 /GPU/hr
on-demand
90-day trend
--
Coverage
6 providers
29 price points

Pricing & availability

How this list works

The two views

By provider shows one card per company, placed where its best offer ranked. By configuration lists every offer.

Order

What you can rent comes first: in stock, then waitlist, then not reported, then out of stock. Priced offers rank ahead of quote-only, and on-demand ahead of other billing types.

Within a group, five factors set the order:

  1. Location: datacenter proximity, blended with provider HQ.
  2. Price: hourly price, per GPU and in total.
  3. Billing type: reserved ahead of spot, spot ahead of quote-only.
  4. Specs: more VRAM, vCPUs and RAM.
  5. Provider diversity: a provider's repeat rows rank slightly lower, so one company can't take all the top spots.

Search

We match the provider, its country, GPU model, form factor, billing type, availability and instance name. Matching is partial and case-insensitive. Everyday words work too, so "interruptible" finds spot and "sold out" finds out of stock.

Transparency and funding

  • Ads and sponsors: Paid placements sit at the top of the list and are always labeled as sponsored content. Sponsorship never influences the organic ranking itself.
  • Affiliates: Affiliate links are marked. We may earn a commission if you click them, but commissions never affect the order.
  • Prices: Shown in USD, converted at daily reference rates where a provider publishes in another currency. A month means 720 hours. How we estimate costs.
Vast.ai logo

Vast.ai

In stock

United States of America flag USA 14 configs 1x-4x

On-Demand
from $0.20
Reserved
from $0.19
Spot
from $0.15
From $0.20 /GPU/hr On-Demand
Visit website
GPU.ai logo

GPU.ai

In stock

United Arab Emirates flag UAE 1 config 1x

On-Demand
from $0.20
From $0.20 /GPU/hr On-Demand
Visit website
Akamai Cloud logo

United States of America flag USA 9 configs 1x-4x

On-Demand
from $0.52
From $0.52 /GPU/hr On-Demand
Visit website
DigitalOcean logo

United States of America flag USA 1 config 1x

On-Demand
from $0.76
From $0.76 /GPU/hr On-Demand
Visit website
Sesterce logo

Sesterce

Out of stock

France flag France 1 config 1x

On-Demand
from $0.87
From $0.87 /GPU/hr On-Demand
Visit website

Heads up: A provider's own page may quote a different figure, for example on tax, region or a promotion. A monthly-only plan shows a derived hourly rate. Verify before provisioning. More on how we price.

What can the RTX 4000 Ada run?

One RTX 4000 Ada has 20 GB of VRAM. In practice, that's enough memory for roughly 22B parameters at 4-bit or 4B at 16-bit, assuming a 32K context. Below are some open-weight LLMs, with the estimated memory and GPUs each one needs.

Fits on 1 Single node ≤ 8 Multi-node
Model Memory (INT4 / FP4) RTX 4000 Adas needed Cost /hr Cost /mo
Alibaba Cloud logo Qwen3.8-27B 27B
18 GB
1
$0.24
$173
Google Cloud logo Gemma 4 31B 30.7B
22 GB
2
$0.48
$346
OpenAI logo GPT-OSS-120B 117B · 5.1B active
67 GB
4
$0.96
$691
Z.AI logo GLM-5.3-Flash 320B · 18B active
178 GB
10
MiniMax logo MiniMax-M3 428B · 23B active
239 GB
14
DeepSeek logo DeepSeek V4.1 Flash 552B · 16B active
306 GB
17
Moonshot AI logo Kimi K3 2.8T · 104B active
1,544 GB
86

Estimates based on the median on-demand rate. Memory is weights plus FP8 KV cache at 32K context per request (FP16/BF16 in the 16-bit column). GPU counts assume 90% of advertised VRAM is usable. No guarantee of runtime support, usable performance, or that a matching quantized build exists. How we estimate costs.

Technical Specifications

Nvidia RTX 4000 Ada · Per GPU

Compute · dense
FP8 213.8 TFLOPS 427.6 with sparsity
FP16 / BF16 106.9 TFLOPS 213.8 with sparsity
FP32 26.7 TFLOPS
Precision support FP8FP16BF16TF32FP32INT4INT8
Memory
Capacity 20 GB GDDR6
Bandwidth 360 GB/s
Bus width 160-bit
ECC Yes
Silicon
Architecture Ada Lovelace
Process TSMC 4N
Transistors 35.8 billion
Shader cores 6,144 CUDA cores
Matrix cores 192 Tensor cores
Compute units 48 SMs
Fabric and host
Host interface PCIe 4.0 x16
Power
Board power 130 W
Cooling Active

Source: official Nvidia RTX 4000 Ada datasheet.

Frequently Asked Questions

How much does the RTX 4000 Ada cost per hour?

As of September 17, 2026, the median on-demand price is $0.24 per GPU per hour across 5 providers with a priced on-demand config.

Billing typeConfigsMedian /GPU/hrCheapest

On-demand

18

$0.24

$0.20 (in stock, GPU.ai)

Reserved

7

$0.19 (3 mo, in stock, Vast.ai)

Spot

4

$0.15 (in stock, Vast.ai)

No median for reserved and spot: we only show this when at least 3 providers list the GPU on that billing type.

Who has the cheapest RTX 4000 Ada?

The cheapest verified in-stock on-demand RTX 4000 Ada tracked by GetDeploying is $0.20 per GPU per hour from GPU.ai. Cheapest verified in stock on other billing types: reserved $0.19 (3 mo) and spot $0.15, both from Vast.ai.

How much does the RTX 4000 Ada cost per month?

At 720 hours per month, one RTX 4000 Ada costs an estimated $173 at the median on-demand price. Cheapest verified in stock: $144 per month on-demand, $137 reserved (3 mo), $108 spot.

Where can I rent an RTX 4000 Ada?

GetDeploying currently tracks RTX 4000 Ada configs from 6 providers. The cheapest verified in-stock on-demand configs come from GPU.ai, Runpod and Vast.ai. See the full price comparison above for every provider and config.

How many RTX 4000 Ada GPUs do I need?

One RTX 4000 Ada runs models up to roughly 22B parameters at 4-bit quantization or 4B at 16-bit, assuming a 32K context. Larger models run across multiple GPUs: the model table above shows the estimated memory and GPU count for popular open-weight LLMs.

Why choose the RTX 4000 Ada?

20GB GDDR6 with ECC in a single-slot, 130W card, so it fits workstations and dense chassis that cannot take a dual-slot GPU. Ada Lovelace FP8 Tensor Cores cover AI development alongside rendering and viewport work.

When is the RTX 4000 Ada not a good fit?

20GB limits the model sizes you can hold in memory, and there is no NVLink to pool across cards. Step up to the RTX 4500 Ada for 24GB or the RTX 6000 Ada for 48GB when the model does not fit.

Alternatives to Nvidia RTX 4000 Ada

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