Why choose the RTX 3070?

8GB GDDR6 with Ampere Tensor Cores. Low-cost entry point for learning GPU computing and basic inference.

When is the RTX 3070 not a good fit?

8GB VRAM is insufficient for most AI models at FP16. Better suited for learning and prototyping than production use.

Are RTX 3070 prices going up or down?

The median on-demand price across providers has fallen about 16% since August 2025, from $0.11 to $0.09/hr per GPU. This reflects the market-wide median, which moves both when providers change prices and when lower or higher priced offerings enter the market.

What size AI models can the RTX 3070 run?

With 8GB of VRAM, the RTX 3070 is mainly limited to small quantized models and lightweight GPU workloads.

How much VRAM does the RTX 3070 have?

The RTX 3070 has 8GB of VRAM. Multi-GPU setups increase total memory, but that memory is not automatically pooled across GPUs.

What is the RTX 3070's memory bandwidth?

The RTX 3070 has 448 GB/s of memory bandwidth. Higher bandwidth helps with faster data transfer between GPU memory and compute cores.

What data types does the RTX 3070 support?

The RTX 3070 supports 6 precision formats. Training: BF16, FP16, TF32, FP32. Inference: INT4, INT8.

Does the RTX 3070 support NVLink?

No. The RTX 3070 is a PCIe-only GPU with no NVLink, so it is better suited to single-GPU inference and smaller-scale workloads than large distributed training jobs.

How much does the RTX 3070 cost per hour?

RTX 3070 pricing currently ranges from $0.04/hr to $0.13/hr per GPU, depending on the provider, instance type, and billing model.

How much does the RTX 3070 cost per month?

At 720 hours per month, one RTX 3070 can cost between $28.80 to $96.53 per month, depending on the provider. Reserved and spot pricing can lower that further.

Which cloud providers offer the RTX 3070?

The RTX 3070 is available from 4 cloud providers, including Runpod, Salad, Theta EdgeCloud. Pricing and availability vary by region and billing model.

Can I rent the RTX 3070 in the cloud?

Yes. We currently track 12 RTX 3070 listings across 4 cloud providers: Billing type Listings Avg $/GPU/hr On-demand 10 $0.09/hr Reserved 1 $0.06/hr Spot 1 $0.04/hr

Nvidia RTX 3070

Entry-level Ampere GPU for learning GPU programming.

Last update 10 minutes ago

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Aggregating historical prices...

Key Specifications

Architecture

Ampere

Memory

8GB GDDR6

Memory Bandwidth

448 GB/s

Release date

Q4 2020

RTX 3070 Pricing and Availability

You can start using a RTX 3070 for $0.04/hr per GPU (on-demand). It's a low-risk price point for smaller workloads compared to the market high of $0.13/hr.

4 providers

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, largest first:

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

Search

We match the provider, 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 Our sponsor

USA 6 configs 1x-4x

On-Demand from $0.05 Reserved from $0.06 Spot from $0.0422

From $0.05 / GPU / hr On-Demand Visit website


1x RTX 3070	8GB	28	63GB	Spot	$0.0422	$0.0422	In stock
1x RTX 3070	8GB	5	8GB	On-Demand	$0.06	$0.06	In stock
1x RTX 3070	8GB	4	16GB	Reserved (6mo)	$0.06	$0.06	In stock
2x RTX 3070	16GB	11	16GB	On-Demand	$0.05	$0.11	In stock
4x RTX 3070	32GB	18	36GB	On-Demand	$0.05	$0.22	In stock
3x RTX 3070	24GB	12	47GB	On-Demand	$0.13	$0.40	In stock

Runpod In stock

USA 4 configs 1x-8x

On-Demand from $0.13

From $0.13 / GPU / hr On-Demand Visit website


1x RTX 3070	8GB	4	16GB	On-Demand	$0.13	$0.13	In stock
2x RTX 3070	16GB	8	32GB	On-Demand	$0.13	$0.26	In stock
4x RTX 3070	32GB	16	64GB	On-Demand	$0.13	$0.52	In stock
8x RTX 3070	64GB	32	128GB	On-Demand	$0.13	$1.04	In stock

Theta EdgeCloud In stock

USA 1 config 1x

On-Demand from $0.09

From $0.09 / GPU / hr On-Demand Visit website


1x RTX 3070	8GB	8	15GB	On-Demand	$0.09	$0.09	In stock

Salad

USA 1 config 1x

On-Demand from $0.0400

From $0.0400 / GPU / hr On-Demand Visit website


1x RTX 3070	8GB	4	8GB	On-Demand	$0.0400	$0.0400	Not reported

Heads up: We do our best to keep these specs & prices accurate. However, cloud costs may fluctuate based on region, usage, and other factors not listed here. These are estimates based on common setups and are for informational purposes only. Always verify current rates & exact specs with the provider before provisioning.

Frequently Asked Questions

Why choose the RTX 3070?: 8GB GDDR6 with Ampere Tensor Cores. Low-cost entry point for learning GPU computing and basic inference.
When is the RTX 3070 not a good fit?: 8GB VRAM is insufficient for most AI models at FP16. Better suited for learning and prototyping than production use.
Are RTX 3070 prices going up or down?: The median on-demand price across providers has fallen about 16% since August 2025, from $0.11 to $0.09/hr per GPU. This reflects the market-wide median, which moves both when providers change prices and when lower or higher priced offerings enter the market.
What size AI models can the RTX 3070 run?: With 8GB of VRAM, the RTX 3070 is mainly limited to small quantized models and lightweight GPU workloads.
How much VRAM does the RTX 3070 have?: The RTX 3070 has 8GB of VRAM. Multi-GPU setups increase total memory, but that memory is not automatically pooled across GPUs.
What is the RTX 3070's memory bandwidth?: The RTX 3070 has 448 GB/s of memory bandwidth. Higher bandwidth helps with faster data transfer between GPU memory and compute cores.
What data types does the RTX 3070 support?: The RTX 3070 supports 6 precision formats. Training: BF16, FP16, TF32, FP32. Inference: INT4, INT8.
Does the RTX 3070 support NVLink?: No. The RTX 3070 is a PCIe-only GPU with no NVLink, so it is better suited to single-GPU inference and smaller-scale workloads than large distributed training jobs.
How much does the RTX 3070 cost per hour?: RTX 3070 pricing currently ranges from $0.04/hr to $0.13/hr per GPU, depending on the provider, instance type, and billing model.
How much does the RTX 3070 cost per month?: At 720 hours per month, one RTX 3070 can cost between $28.80 to $96.53 per month, depending on the provider. Reserved and spot pricing can lower that further.
Which cloud providers offer the RTX 3070?: The RTX 3070 is available from 4 cloud providers, including Runpod, Salad, Theta EdgeCloud. Pricing and availability vary by region and billing model.
Can I rent the RTX 3070 in the cloud?: Yes. We currently track 12 RTX 3070 listings across 4 cloud providers:

Billing type Listings Avg $/GPU/hr

On-demand 10 $0.09/hr

Reserved 1 $0.06/hr

Spot 1 $0.04/hr

Billing type	Listings	Avg $/GPU/hr
On-demand	10	$0.09/hr
Reserved	1	$0.06/hr
Spot	1	$0.04/hr

Technical Specifications


Architecture	Ampere
Process Size	8 nm
Transistors	17,400 million
Bus Interface	PCIe 4.0 x16
Base Clock	1500 MHz
Boost Clock	1725 MHz
Memory Clock	1750 MHz, 14 Gbps effective
Memory Size	8 GB
Memory Type	GDDR6
Memory Bus	256 bit
Bandwidth	448.0 GB/s
Tensor Cores	184
FP16 (half)	20.31 TFLOPS (1:1)
FP32 (float)	20.31 TFLOPS
FP64 (double)	317.4 GFLOPS (1:64)
CUDA	8.6