consumer
Rent Nvidia RTX 3060 Laptop GPU.
Ampere
12GB VRAM
From $0.065/hr
Per hour
$0.065
Per day
$1.56
Per week
$10.92
Per month
$47
Provider spread
2 providers ·
up to 30% cheaper at the low end
Cheapest · $0.065/hr on Theta EdgeCloud
Median $0.079/hr
Most expensive · $0.093/hr on Clore.ai
Price history
Daily median across providers.
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Where to rent it
All providers carrying this GPU.
AI models that fit
See all 6 →
Run these on this GPU.
- Llama 4 Scout 17B 16E Instruct Fp8 Lora 1× · int4
- Llama 4 Scout Instruct (17Bx16E) 1× · int4
- Llama 4 Maverick Instruct (17Bx128E) FP8 1× · int4
Cloud instances
See all 2 →
Hyperscaler bundles.
Pre-configured on 1 clouds — from $0.06/hr total
($0.065/hr per GPU).
FAQ
Frequently asked.
What's a cloud instance bundle for the Nvidia RTX 3060 Laptop GPU?
A pre-configured VM that pairs the Nvidia RTX 3060 Laptop GPU with a fixed amount of vCPU, RAM, and SSD on a hyperscaler (AWS, Google Cloud, Azure, Oracle, Vultr, etc.). You pay one hourly rate for the whole bundle; the per-GPU rate on the table is just the bundle price divided by the GPU count.
Why is per-GPU pricing on instances different from raw GPU rental rates?
Hyperscaler bundles include managed networking, premium NVMe storage, an SLA, and 24/7 support. P2P marketplaces (Vast.ai, RunPod community, io.net) skip those line items, which is why their raw GPU rates are often 3–10× cheaper. The trade-off is reliability and integration: a hyperscaler instance plugs into your existing VPC, IAM, and observability stack out of the box.
Which hyperscaler is cheapest for the Nvidia RTX 3060 Laptop GPU?
Sort the table by the $/hr per GPU column — the lowest row is the cheapest hyperscaler today. Pricing shifts as providers re-price spot capacity and refresh quotas, so the leader can change week to week. Click Launch on a row to head to that provider's sign-up page (affiliate link, doesn't change the rate you pay).
Can I run my own image or container on these instances?
Yes. All listed hyperscalers expose standard compute APIs — bring your own AMI/image, mount custom volumes, install your own drivers, run any container runtime you like. The bundle just sets the hardware shape; the OS layer is yours to configure.
How do I get the cheapest rate on the Nvidia RTX 3060 Laptop GPU overall?
If you can tolerate a P2P marketplace, the Overview tab's "Where to rent it" table usually has the lowest hourly rate by a wide margin. Use a hyperscaler bundle only when you need managed networking, SLAs, or are already inside that cloud's ecosystem (compliance, data-egress costs, IAM).
Cloud instance options
Pre-configured instances on hyperscalers.
Whole-instance bundles (GPU + vCPU + RAM + disk) on the major clouds. Per-GPU rate often drops as the count rises. View = spec page · Launch = sign up (affiliate).
Cheapest bundle
$0.06/hr
Lowest $/hr per GPU
$0.065/hr
Providers
1
Instance shapes
2
| Provider | Instance | GPUs | vCPU | RAM | Disk | $/hr | $/hr per GPU | |
|---|---|---|---|---|---|---|---|---|
| community-1x | 1× | — | — | — | $0.06/hr | $0.065/hr | ||
| community-1x | 1× | — | — | — | $0.10/hr | $0.10/hr |
Looking for the cheapest rate?
Hyperscaler bundles include managed networking + SLAs. Raw per-GPU rental on P2P marketplaces is typically 3–10× cheaper.
See raw rental rates on the Overview tab →
FAQ
Cloud instances — common questions.
What's a cloud instance bundle for the Nvidia RTX 3060 Laptop GPU?
A pre-configured VM that pairs the Nvidia RTX 3060 Laptop GPU with a fixed amount of vCPU, RAM, and SSD on a hyperscaler (AWS, Google Cloud, Azure, Oracle, Vultr, etc.). You pay one hourly rate for the whole bundle; the per-GPU rate on the table is just the bundle price divided by the GPU count.
Why is per-GPU pricing on instances different from raw GPU rental rates?
Hyperscaler bundles include managed networking, premium NVMe storage, an SLA, and 24/7 support. P2P marketplaces (Vast.ai, RunPod community, io.net) skip those line items, which is why their raw GPU rates are often 3–10× cheaper. The trade-off is reliability and integration: a hyperscaler instance plugs into your existing VPC, IAM, and observability stack out of the box.
Which hyperscaler is cheapest for the Nvidia RTX 3060 Laptop GPU?
Sort the table by the $/hr per GPU column — the lowest row is the cheapest hyperscaler today. Pricing shifts as providers re-price spot capacity and refresh quotas, so the leader can change week to week. Click Launch on a row to head to that provider's sign-up page (affiliate link, doesn't change the rate you pay).
Can I run my own image or container on these instances?
Yes. All listed hyperscalers expose standard compute APIs — bring your own AMI/image, mount custom volumes, install your own drivers, run any container runtime you like. The bundle just sets the hardware shape; the OS layer is yours to configure.
How do I get the cheapest rate on the Nvidia RTX 3060 Laptop GPU overall?
If you can tolerate a P2P marketplace, the Overview tab's "Where to rent it" table usually has the lowest hourly rate by a wide margin. Use a hyperscaler bundle only when you need managed networking, SLAs, or are already inside that cloud's ecosystem (compliance, data-egress costs, IAM).
AI models
INT4
INT4
INT4
INT4
INT4
INT4
Models that run on this GPU.
GPU-count + quantization recommendations covering fine-tuning, inference, and run-it-yourself scenarios on the Nvidia RTX 3060 Laptop GPU.
Llama 4 Scout 17B 16E Instruct Fp8 Lora
by Meta AI
Required GPUs
1× Nvidia RTX 3060 Laptop GPU
Total VRAM
12 GB
Parameters
17B
Context
10.5M tokens
Llama 4 Scout Instruct (17Bx16E)
by Meta AI
Required GPUs
1× Nvidia RTX 3060 Laptop GPU
Total VRAM
12 GB
Parameters
17B
Context
1M tokens
Llama 4 Maverick Instruct (17Bx128E) FP8
by Meta AI
Required GPUs
1× Nvidia RTX 3060 Laptop GPU
Total VRAM
12 GB
Parameters
17B
Context
1M tokens
Llama 4 Scout (17Bx16E)
by Meta AI
Required GPUs
1× Nvidia RTX 3060 Laptop GPU
Total VRAM
12 GB
Parameters
17B
Context
262K tokens
DeepSeek Coder V2 Lite
by DeepSeek
Required GPUs
1× Nvidia RTX 3060 Laptop GPU
Total VRAM
12 GB
Parameters
16B (2B active)
Context
128K tokens
DeepSeek R1 Distill Qwen 14B
by DeepSeek
Required GPUs
1× Nvidia RTX 3060 Laptop GPU
Total VRAM
12 GB
Parameters
15B
Context
128K tokens
Renting for inference?
Pair these models with the cheapest provider on the rental table.
See rental rates on the Overview tab →
FAQ
AI models on this GPU.
What's a cloud instance bundle for the Nvidia RTX 3060 Laptop GPU?
A pre-configured VM that pairs the Nvidia RTX 3060 Laptop GPU with a fixed amount of vCPU, RAM, and SSD on a hyperscaler (AWS, Google Cloud, Azure, Oracle, Vultr, etc.). You pay one hourly rate for the whole bundle; the per-GPU rate on the table is just the bundle price divided by the GPU count.
Why is per-GPU pricing on instances different from raw GPU rental rates?
Hyperscaler bundles include managed networking, premium NVMe storage, an SLA, and 24/7 support. P2P marketplaces (Vast.ai, RunPod community, io.net) skip those line items, which is why their raw GPU rates are often 3–10× cheaper. The trade-off is reliability and integration: a hyperscaler instance plugs into your existing VPC, IAM, and observability stack out of the box.
Which hyperscaler is cheapest for the Nvidia RTX 3060 Laptop GPU?
Sort the table by the $/hr per GPU column — the lowest row is the cheapest hyperscaler today. Pricing shifts as providers re-price spot capacity and refresh quotas, so the leader can change week to week. Click Launch on a row to head to that provider's sign-up page (affiliate link, doesn't change the rate you pay).
Can I run my own image or container on these instances?
Yes. All listed hyperscalers expose standard compute APIs — bring your own AMI/image, mount custom volumes, install your own drivers, run any container runtime you like. The bundle just sets the hardware shape; the OS layer is yours to configure.
How do I get the cheapest rate on the Nvidia RTX 3060 Laptop GPU overall?
If you can tolerate a P2P marketplace, the Overview tab's "Where to rent it" table usually has the lowest hourly rate by a wide margin. Use a hyperscaler bundle only when you need managed networking, SLAs, or are already inside that cloud's ecosystem (compliance, data-egress costs, IAM).