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NVIDIA A100X

80 GB VRAM312 FP16 TFLOPS300 W TDP1 providers3 offerings1 regions

The NVIDIA A100X is an enterprise-class GPU built on the Ampere architecture, featuring 80 GB of memory with 1,935 GB/s of memory bandwidth and a 300 W TDP. It delivers 19.5 TFLOPS of FP32 performance and 312 TFLOPS of FP16 tensor performance. Currently available from 1 provider starting at $1.28/GPU/hour, with a market median of $1.28/GPU/hour across 3 configurations.

Cheapest
$1.280/hr
Vast.ai
Median
$1.280/hr
across 3 offerings
Most expensive
$1.280/hr
Vast.ai
90-day trend
0.0%
median rate

Hardware specifications

Same across all providers

Memory
80 GB
HBM2e
What LLMs fit? ↓
FP16 performance
312 TFLOPS
peak
TDP
300 W
Memory bandwidth
1,935 GB/s
Architecture
Ampere
FP32 performance
19.5 TFLOPS
Brand
NVIDIA
Series
A100
Market price history

Median price across all providers

Prices updated

1 offering from 1 providers

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

ProviderCountvCPURAMRegionPer GPU hourTotal/hrAction
Vast.aiReferral linkTrendingCheapest
×13263 GB
United States
$1.280
From$1.28
Launch

LLMs that fit on the NVIDIA A100X

Estimated VRAM for popular open-weight LLMs at 16-bit (FP16/BF16), 8-bit (FP8/INT8) and 4-bit (INT4/MXFP4) precision, against 80 GB per GPU. Showing the 12 largest that fit.

ModelParameters16-bit8-bit4-bit
DeepSeek V4 Flash
DeepSeek
284B
—
Not released
—
Not released
192 GB
4× · 128 GB free
or 2× · 0% spare
Solar Open2 250B
Upstage
250B
15B active
601 GB
Too large
330 GB
Tight on 4× · 16% spare
192 GB
4× · 128 GB free
Qwen3 235B-A22B
Alibaba
235B
22B active
564 GB
Too large
310 GB
4× · 9.7 GB free
181 GB
4× · 139 GB free
or 2× · 6% spare
Laguna-S 2.1
Poolside
118B
8B active
282 GB
4× · 38 GB free
155 GB
2× · 4.8 GB free
90 GB
2× · 70 GB free
or 1× · 6% spare
gpt-oss-120b
OpenAI
117B
5.1B active
—
Not released
—
Not released
78 GB
1× · 1.7 GB free
Qwen3.6 35B-A3B
Alibaba
35B
3B active
86 GB
2× · 74 GB free
or 1× · 11% spare
47 GB
1× · 33 GB free
28 GB
1× · 52 GB free
Qwen3 32B
Alibaba
32.8B
79 GB
1× · 1.4 GB free
43 GB
1× · 37 GB free
25 GB
1× · 55 GB free
Gemma 4 31B
Google
31.3B
75 GB
1× · 4.9 GB free
41 GB
1× · 39 GB free
24 GB
1× · 56 GB free
GLM-4.7 Flash
Z.ai
31.2B
75 GB
1× · 5.1 GB free
41 GB
1× · 39 GB free
24 GB
1× · 56 GB free
Qwen3.6 27B
Alibaba
27.8B
67 GB
1× · 13 GB free
37 GB
1× · 43 GB free
21 GB
1× · 59 GB free
Mistral Small 3.2 24B
Mistral AI
24B
58 GB
1× · 22 GB free
32 GB
1× · 48 GB free
18 GB
1× · 62 GB free
gpt-oss-20b
OpenAI
21B
3.6B active
—
Not released
—
Not released
17 GB
1× · 63 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 A100X cost per hour?
The A100X starts at $1.28 per GPU-hour, with a median of $1.28 across 3 available configurations. Actual pricing depends on the provider, region, and whether you rent on-demand, spot or reserved.
Which cloud providers offer the A100X?
1 providers currently list the A100X: Vast.ai. Compare their hourly pricing, regions and machine specs in the table above.
How much VRAM does the A100X have?
The A100X comes with 80 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 A100X?
With 80 GB of VRAM, a single A100X can serve models such as gpt-oss-120b, Qwen3.6 35B-A3B, Qwen3 32B, Gemma 4 31B. 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 A100X GPUs?
The largest models we track that fit across several A100X cards are DeepSeek V4 Flash on 4 GPUs at 4-bit, Solar Open2 250B on 4 GPUs at 4-bit, Qwen3 235B-A22B on 4 GPUs at 8-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 A100X cheapest?
The lowest on-demand price we currently track for the A100X is $1.28 per GPU-hour at Vast.ai. Because providers update pricing and availability frequently, check the live table above before you launch.