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NVIDIA GTX 1660 Super

6 GB VRAM125 W TDP2 providers5 offerings3 regions

The NVIDIA GTX 1660 Super is a consumer-grade GPU built on the Turing architecture, featuring 6 GB of memory with 336 GB/s of memory bandwidth and a 125 W TDP. It delivers 5 TFLOPS of FP32 performance. Currently available from 2 providers starting at $0.02/GPU/hour, with a market median of $0.04/GPU/hour across 5 configurations.

Cheapest
$0.020/hr
Vast.ai
Median
$0.040/hr
across 5 offerings
Most expensive
$0.070/hr
Theta EdgeCloud
90-day trend
-33.3%
median rate

Hardware specifications

Same across all providers

TDP
125 W
Memory bandwidth
336 GB/s
Architecture
Turing
FP32 performance
5 TFLOPS
Brand
NVIDIA
Series
GeForce GTX
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
×11121 GB
ChinaHong KongUnited States
From$0.020
0.0% 30d
From$0.02
Launch
×11631 GB
United States
$0.070
0.0% 30d
$0.07
Launch

LLMs that fit on the NVIDIA GTX 1660 Super

Estimated VRAM for popular open-weight LLMs at 16-bit (FP16/BF16), 8-bit (FP8/INT8) and 4-bit (INT4/MXFP4) precision, against 6 GB per GPU. Showing the 12 largest that fit.

ModelParameters16-bit8-bit4-bit
Qwen3.6 35B-A3B
Alibaba
35B
3B active
86 GB
Too large
47 GB
Too large
28 GB
Tight on 4× · 4% spare
Qwen3 32B
Alibaba
32.8B
79 GB
Too large
43 GB
Too large
25 GB
Tight on 4× · 14% spare
Gemma 4 31B
Google
31.3B
75 GB
Too large
41 GB
Too large
24 GB
Tight on 4× · 19% spare
GLM-4.7 Flash
Z.ai
31.2B
75 GB
Too large
41 GB
Too large
24 GB
Barely fits on 4×
Qwen3.6 27B
Alibaba
27.8B
67 GB
Too large
37 GB
Too large
21 GB
4× · 2.7 GB free
Mistral Small 3.2 24B
Mistral AI
24B
58 GB
Too large
32 GB
Too large
18 GB
4× · 5.6 GB free
gpt-oss-20b
OpenAI
21B
3.6B active
Not released
Not released
17 GB
4× · 7.5 GB free
Gemma 3 12B
Google
12.2B
29 GB
Too large
16 GB
4× · 7.9 GB free
9.4 GB
2× · 2.6 GB free
Granite 4.1 8B
IBM
8.8B
21 GB
4× · 2.9 GB free
12 GB
Barely fits on 2×
6.8 GB
2× · 5.2 GB free
or 1× · 6% spare
Qwen3 8B
Alibaba
8.2B
20 GB
4× · 4.3 GB free
11 GB
2× · 1.2 GB free
6.3 GB
2× · 5.7 GB free
or 1× · 14% spare
Llama 3.1 8B Instruct
Meta
8B
19 GB
4× · 4.7 GB free
11 GB
2× · 1.4 GB free
6.2 GB
2× · 5.8 GB free
or 1× · 16% spare
Mistral 7B Instruct v0.3
Mistral AI
7.2B
17 GB
4× · 6.6 GB free
9.6 GB
2× · 2.4 GB free
5.6 GB
Barely fits on 1×

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 GTX 1660 Super cost per hour?
The GTX 1660 Super starts at $0.02 per GPU-hour, with a median of $0.04 across 5 available configurations. Actual pricing depends on the provider, region, and whether you rent on-demand, spot or reserved.
Which cloud providers offer the GTX 1660 Super?
2 providers currently list the GTX 1660 Super: Theta EdgeCloud, Vast.ai. Compare their hourly pricing, regions and machine specs in the table above.
How much VRAM does the GTX 1660 Super have?
The GTX 1660 Super comes with 6 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 GTX 1660 Super?
With 6 GB of VRAM, a single GTX 1660 Super can serve models such as 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 GTX 1660 Super GPUs?
The largest models we track that fit across several GTX 1660 Super cards are GLM-4.7 Flash on 4 GPUs at 4-bit, Qwen3.6 27B on 4 GPUs at 4-bit, Mistral Small 3.2 24B on 4 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 GTX 1660 Super cheapest?
The lowest on-demand price we currently track for the GTX 1660 Super is $0.02 per GPU-hour at Vast.ai. Because providers update pricing and availability frequently, check the live table above before you launch.