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NVIDIA RTX 5060

8 GB VRAM2 providers9 offerings4 regions

The NVIDIA RTX 5060 is a consumer-grade GPU built on the Blackwell architecture, featuring 8 GB of memory. Currently available from 2 providers starting at $0.07/GPU/hour, with a market median of $0.12/GPU/hour across 9 configurations.

Cheapest
$0.070/hr
Vast.ai
Median
$0.120/hr
across 9 offerings
Most expensive
$0.180/hr
Theta EdgeCloud
90-day trend
-63.6%
median rate

Hardware specifications

Same across all providers

Memory
8 GB
GDDR7
What LLMs fit? ↓
Architecture
Blackwell
Brand
NVIDIA
Series
GeForce RTX
Market price history

Median price across all providers

Prices updated 2 hours ago

2 offerings from 2 providers

Sorted by price ascending. Compare configurations side-by-side.

ProviderCountvCPURAMRegionPer GPU hourTotal/hrAction
Vast.ai logoVast.aiReferral linkTrendingCheapest
×1616 GB
IndiaUnited KingdomRussia
From$0.070
-18.2% 30d
From$0.07
Launch
×13215 GB
United States
From$0.130
-14.7% 30d
From$0.13
Launch

LLMs that fit on the NVIDIA RTX 5060

Estimated VRAM for popular open-weight LLMs at 16-bit (FP16/BF16), 8-bit (FP8/INT8) and 4-bit (INT4/MXFP4) precision, against 8 GB per GPU.

ModelParameters16-bit8-bit4-bit
Mistral Small 3.2 24B
Mistral AI
24B
58 GB
Too large
32 GB
Too large
18 GB
Tight on 2× · 4% spare
gpt-oss-20b
OpenAI
21B
3.6B active
Not released
Not released
17 GB
Tight on 2× · 16% spare
Gemma 3 12B
Google
12.2B
29 GB
Too large
16 GB
Tight on 2× · 19% spare
9.4 GB
2× · 6.6 GB free
or 1× · 2% spare
Granite 4.1 8B
IBM
8.8B
21 GB
Too large
12 GB
2× · 4.4 GB free
6.8 GB
1× · 1.2 GB free
Qwen3 8B
Alibaba
8.2B
20 GB
Too large
11 GB
2× · 5.2 GB free
6.3 GB
1× · 1.7 GB free
Llama 3.1 8B Instruct
Meta
8B
19 GB
Too large
11 GB
2× · 5.4 GB free
6.2 GB
1× · 1.8 GB free
Mistral 7B Instruct v0.3
Mistral AI
7.2B
17 GB
Tight on 2× · 10% spare
9.6 GB
2× · 6.4 GB free
or 1× · 0% spare
5.6 GB
1× · 2.4 GB free
Qwen3 4B
Alibaba
4B
9.7 GB
2× · 6.3 GB free
5.3 GB
1× · 2.7 GB free
3.1 GB
1× · 4.9 GB free

Estimates: model weights plus 20% for KV cache and runtime overhead, at short context lengths. Long contexts and large batches need more. Rows marked “tight” hold the weights but not that full margin. A ×N figure is the total VRAM across N of these GPUs and makes no claim about interconnect throughput. How we estimate this · Start from a model instead

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Frequently asked questions

How much does the RTX 5060 cost per hour?
The RTX 5060 starts at $0.07 per GPU-hour, with a median of $0.12 across 9 available configurations. Actual pricing depends on the provider, region, and whether you rent on-demand, spot or reserved.
Which cloud providers offer the RTX 5060?
2 providers currently list the RTX 5060: Vast.ai, Theta EdgeCloud. Compare their hourly pricing, regions and machine specs in the table above.
How much VRAM does the RTX 5060 have?
The RTX 5060 comes with 8 GB of VRAM, which determines the largest models and batch sizes it can hold in memory for training and inference.
Which LLMs can I run on the RTX 5060?
With 8 GB of VRAM, a single RTX 5060 can serve models such as Granite 4.1 8B, Qwen3 8B, Llama 3.1 8B Instruct, Mistral 7B Instruct v0.3. The table above lists the estimated VRAM for each model at 16-bit, 8-bit and 4-bit precision, including the multi-GPU configurations needed for larger models.
What's the biggest LLM I can run on multiple RTX 5060 GPUs?
The largest models we track that fit across several RTX 5060 cards are Gemma 3 12B on 2 GPUs at 4-bit. A multi-GPU configuration means you rent and pay for every card for the whole run, and splitting a model across cards costs throughput as well: the GPUs exchange activations on every token, so performance depends on how fast they are wired together. We do not track interconnect, so check the provider's node specification. The table above gives the smallest configuration for each model at 16-bit, 8-bit and 4-bit precision.
Where is the RTX 5060 cheapest?
The lowest on-demand price we currently track for the RTX 5060 is $0.07 per GPU-hour at Vast.ai. Because providers update pricing and availability frequently, check the live table above before you launch.