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NVIDIA A16

16 GB VRAM4 providers12 offerings5 regions

The NVIDIA A16 is an enterprise-class GPU built on the Ampere architecture, featuring 16 GB of memory. Currently available from 4 providers starting at $0.48/GPU/hour, with a market median of $0.51/GPU/hour across 12 configurations.

Cheapest
$0.477/hr
Vultr
Median
$0.509/hr
across 12 offerings
Most expensive
$0.564/hr
Sesterce Cloud
90-day trend
-9.1%
median rate

Hardware specifications

Same across all providers

Architecture
Ampere
Brand
NVIDIA
Series
A16
Market price history

Median price across all providers

Prices updated 3 hours ago

4 offerings from 4 providers

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

ProviderCountvCPURAMRegionPer GPU hourTotal/hrAction
Vultr logoVultrCheapest
×424256 GB
IndiaUnited StatesSingapore+2
From$0.477
From$1.91
Launch
×212128 GB
India
$0.540
0.0% 30d
From$1.08
Launch
×224256 GB
India
$0.560
0.0% 30d
From$1.12
Launch
Sesterce Cloud logoSesterce CloudReferral link
×212128 GB
India
From$0.561
-0.2% 30d
From$1.12
Launch

LLMs that fit on the NVIDIA A16

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

ModelParameters16-bit8-bit4-bit
Laguna-S 2.1
Poolside
118B
8B active
282 GB
Too large
155 GB
Too large
90 GB
8× · 38 GB free
gpt-oss-120b
OpenAI
117B
5.1B active
Not released
Not released
78 GB
8× · 50 GB free
Qwen3.6 35B-A3B
Alibaba
35B
3B active
86 GB
8× · 42 GB free
47 GB
4× · 17 GB free
28 GB
2× · 4.4 GB free
Qwen3 32B
Alibaba
32.8B
79 GB
8× · 49 GB free
43 GB
4× · 21 GB free
25 GB
2× · 6.8 GB free
Gemma 4 31B
Google
31.3B
75 GB
8× · 53 GB free
or 4× · 2% spare
41 GB
4× · 23 GB free
24 GB
2× · 8 GB free
GLM-4.7 Flash
Z.ai
31.2B
75 GB
8× · 53 GB free
or 4× · 2% spare
41 GB
4× · 23 GB free
24 GB
2× · 8 GB free
Qwen3.6 27B
Alibaba
27.8B
67 GB
8× · 61 GB free
or 4× · 15% spare
37 GB
4× · 27 GB free
or 2× · 4% spare
21 GB
2× · 11 GB free
Mistral Small 3.2 24B
Mistral AI
24B
58 GB
4× · 6.4 GB free
32 GB
Barely fits on 2×
18 GB
2× · 14 GB free
or 1× · 4% spare
gpt-oss-20b
OpenAI
21B
3.6B active
Not released
Not released
17 GB
2× · 15 GB free
or 1× · 16% spare
Gemma 3 12B
Google
12.2B
29 GB
2× · 2.8 GB free
16 GB
2× · 16 GB free
or 1× · 19% spare
9.4 GB
1× · 6.6 GB free
Granite 4.1 8B
IBM
8.8B
21 GB
2× · 11 GB free
12 GB
1× · 4.4 GB free
6.8 GB
1× · 9.2 GB free
Qwen3 8B
Alibaba
8.2B
20 GB
2× · 12 GB free
11 GB
1× · 5.2 GB free
6.3 GB
1× · 9.7 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 A16 cost per hour?
The A16 starts at $0.48 per GPU-hour, with a median of $0.51 across 12 available configurations. Actual pricing depends on the provider, region, and whether you rent on-demand, spot or reserved.
Which cloud providers offer the A16?
4 providers currently list the A16: Vultr, Sesterce Cloud, Runcrate, Omega Gradient. Compare their hourly pricing, regions and machine specs in the table above.
How much VRAM does the A16 have?
The A16 comes with 16 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 A16?
With 16 GB of VRAM, a single A16 can serve models such as Gemma 3 12B, Granite 4.1 8B, Qwen3 8B. 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 A16 GPUs?
The largest models we track that fit across several A16 cards are Laguna-S 2.1 on 8 GPUs at 4-bit, gpt-oss-120b on 8 GPUs at 4-bit, Qwen3.6 35B-A3B 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 A16 cheapest?
The lowest on-demand price we currently track for the A16 is $0.48 per GPU-hour at Vultr. Because providers update pricing and availability frequently, check the live table above before you launch.