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NVIDIA A30

24 GB VRAM165 FP16 TFLOPS165 W TDP0 providers0 offerings0 regions

The NVIDIA A30 is an enterprise-class GPU built on the Ampere architecture, featuring 24 GB of memory with 933 GB/s of memory bandwidth and a 165 W TDP. It delivers 10.3 TFLOPS of FP32 performance and 165 TFLOPS of FP16 tensor performance.

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Hardware specifications

Same across all providers

FP16 performance
165 TFLOPS
peak
TDP
165 W
Memory bandwidth
933 GB/s
Architecture
Ampere
FP32 performance
10.3 TFLOPS
Brand
NVIDIA
Series
A30
Market price history

Median price across all providers

Prices updated 5 hours ago

1 offering from 0 providers

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

ProviderCountvCPURAMRegionPer GPU hourTotal/hrAction
Sesterce Cloud logoSesterce CloudReferral link
×11648 GB--
$0.385
0.0% 30d
From$0.39

LLMs that fit on the NVIDIA A30

Estimated VRAM for popular open-weight LLMs at 16-bit (FP16/BF16), 8-bit (FP8/INT8) and 4-bit (INT4/MXFP4) precision, against 24 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 1× · 4% spare
Qwen3 32B
Alibaba
32.8B
79 GB
Too large
43 GB
Too large
25 GB
Tight on 1× · 14% spare
Gemma 4 31B
Google
31.3B
75 GB
Too large
41 GB
Too large
24 GB
Tight on 1× · 19% spare
GLM-4.7 Flash
Z.ai
31.2B
75 GB
Too large
41 GB
Too large
24 GB
Barely fits on 1×
Qwen3.6 27B
Alibaba
27.8B
67 GB
Too large
37 GB
Too large
21 GB
1× · 2.7 GB free
Mistral Small 3.2 24B
Mistral AI
24B
58 GB
Too large
32 GB
Too large
18 GB
1× · 5.6 GB free
gpt-oss-20b
OpenAI
21B
3.6B active
Not released
Not released
17 GB
1× · 7.5 GB free
Gemma 3 12B
Google
12.2B
29 GB
Too large
16 GB
1× · 7.9 GB free
9.4 GB
1× · 15 GB free
Granite 4.1 8B
IBM
8.8B
21 GB
1× · 2.9 GB free
12 GB
1× · 12 GB free
6.8 GB
1× · 17 GB free
Qwen3 8B
Alibaba
8.2B
20 GB
1× · 4.3 GB free
11 GB
1× · 13 GB free
6.3 GB
1× · 18 GB free
Llama 3.1 8B Instruct
Meta
8B
19 GB
1× · 4.7 GB free
11 GB
1× · 13 GB free
6.2 GB
1× · 18 GB free
Mistral 7B Instruct v0.3
Mistral AI
7.2B
17 GB
1× · 6.6 GB free
9.6 GB
1× · 14 GB free
5.6 GB
1× · 18 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

Which cloud providers offer the A30?
2 providers currently list the A30: Sesterce Cloud, AceCloud. Compare their hourly pricing, regions and machine specs in the table above.
How much VRAM does the A30 have?
The A30 comes with 24 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 A30?
With 24 GB of VRAM, a single A30 can serve models such as GLM-4.7 Flash, Qwen3.6 27B, Mistral Small 3.2 24B, gpt-oss-20b. 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.