datacenter
Nvidia A100 SXM mieten.
Ampere
40GB VRAM
400W
From $1.39/hr
Per hour
$1.39
Per day
$33.36
Per week
$233.52
Per month
$1001
Provider spread
5 providers ·
up to 30% cheaper at the low end
Cheapest · $1.39/hr on RunPod
Median $1.60/hr
Most expensive · $1.99/hr on Lambda Labs
Price history
Daily median across providers.
Loading...
Where to rent it
All providers carrying this GPU.
Buy vs rent
Should you rent or own?
Your usage
Rent on cloud
Per day
—
Per month
—
at $1.39/hr cheapest provider rate
Own on-prem
Electricity per day
—
400W TDP
Cloud instance options
Pre-configured instances on hyperscalers.
Whole-instance bundles (GPU + vCPU + RAM + disk) on the major clouds. Per-GPU rate often drops as the count rises. View = spec page · Launch = sign up (affiliate).
Cheapest bundle
$1.52/hr
Lowest $/hr per GPU
$1.48/hr
Providers
6
Instance shapes
17
| Provider | Instance | GPUs | vCPU | RAM | Disk | $/hr | $/hr per GPU | |
|---|---|---|---|---|---|---|---|---|
| A100_sxm4_80G | 1× | 14 | 100 GB | 625 GB | $1.52/hr | $1.52/hr | ||
| A100_sxm4_80G_DGX | 1× | 16 | 160 GB | 1000 GB | $1.52/hr | $1.52/hr | ||
| A100_sxm4 | 1× | 14 | 117 GB | 1700 GB | $1.54/hr | $1.54/hr | ||
| on-demand · A100 SXM | 1× | 24 | 120 GB | — | $1.60/hr | $1.60/hr | ||
| 1x A100_40G_SXM4 | 1× | 14 | 117 GB | 1700 GB | $1.68/hr | $1.68/hr |
Launch ↗Empfehlung
|
|
| 1x A100_80G_SXM4 | 1× | 24 | 116 GB | 2125 GB | $1.80/hr | $1.80/hr |
Launch ↗Empfehlung
|
|
| A100_SXM4_80Gx8_3 | 8× | 240 | 1280 GB | 9578 GB | $11.88/hr | $1.48/hr | ||
| A100_sxm4_80Gx8 | 8× | 126 | 1500 GB | 10000 GB | $12.14/hr | $1.52/hr | ||
| A100_sxm4x8 | 8× | 120 | 940 GB | 13600 GB | $12.32/hr | $1.54/hr | ||
| 8x A100_80G_SXM4 | 8× | 240 | 1280 GB | 9578 GB | $12.96/hr | $1.62/hr |
Launch ↗Empfehlung
|
|
| 8x A100_40G_SXM4 | 8× | 120 | 940 GB | 13600 GB | $13.44/hr | $1.68/hr |
Launch ↗Empfehlung
|
|
| p4d.24xlarge | 8× | — | — | — | $21.96/hr | $2.74/hr | ||
| BM.GPU4.8 | 8× | — | — | — | $24.40/hr | $3.05/hr | ||
| ND96asr_v4 | 8× | — | — | — | $27.20/hr | $3.40/hr | ||
| p4de.24xlarge | 8× | — | — | — | $27.45/hr | $3.43/hr | ||
| BM.GPU.A100-v2.8 | 8× | — | — | — | $32.00/hr | $4.00/hr | ||
| ND96amsr_A100_v4 | 8× | — | — | — | $32.77/hr | $4.10/hr |
Looking for the cheapest rate?
Hyperscaler bundles include managed networking + SLAs. Raw per-GPU rental on P2P marketplaces is typically 3–10× cheaper.
See raw rental rates on the Overview tab →
FAQ
Cloud instances — common questions.
What's a cloud instance bundle for the Nvidia A100 SXM?
A pre-configured VM that pairs the Nvidia A100 SXM with a fixed amount of vCPU, RAM, and SSD on a hyperscaler (AWS, Google Cloud, Azure, Oracle, Vultr, etc.). You pay one hourly rate for the whole bundle; the per-GPU rate on the table is just the bundle price divided by the GPU count. Like raw GPU rental it is on-demand — billed while the instance runs, no subscription — though hyperscalers also sell reserved or committed-use plans that trade a term commitment for a lower rate.
Why is per-GPU pricing on instances different from raw GPU rental rates?
Hyperscaler bundles include managed networking, premium NVMe storage, an SLA, and 24/7 support. P2P marketplaces (Vast.ai, RunPod community, io.net) skip those line items, which is why their raw GPU rates are often 3–10× cheaper. The trade-off is reliability and integration: a hyperscaler instance plugs into your existing VPC, IAM, and observability stack out of the box.
Which hyperscaler is cheapest for the Nvidia A100 SXM?
Sort the table by the $/hr per GPU column — the lowest row is the cheapest hyperscaler today. Pricing shifts as providers re-price spot capacity and refresh quotas, so the leader can change week to week. Click Launch on a row to head to that provider's sign-up page (affiliate link, doesn't change the rate you pay).
Can I run my own image or container on these instances?
Yes. All listed hyperscalers expose standard compute APIs — bring your own AMI/image, mount custom volumes, install your own drivers, run any container runtime you like. The bundle just sets the hardware shape; the OS layer is yours to configure.
How do I get the cheapest rate on the Nvidia A100 SXM overall?
If you can tolerate a P2P marketplace, the Overview tab's "Where to rent it" table usually has the lowest hourly rate by a wide margin. Use a hyperscaler bundle only when you need managed networking, SLAs, or are already inside that cloud's ecosystem (compliance, data-egress costs, IAM).
AI models
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Models that run on this GPU.
Open-Weights-Modelle, die für Inferenz auf diese Karte passen, mit der kleinsten Kartenzahl und der Genauigkeit, mit der jedes geladen wird. Täglich aus der Modellgröße und dem Kartenspeicher berechnet. Die 60 größten von 243 passenden Modellen.
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INT4
Beam 1.0 501B A23B
by Reflection
Required GPUs
8× Nvidia A100 SXM
VRAM gesamt
320 GB
Parameters
501B
Context
1M tokens
Qwen3 Coder 480B A35B
by Alibaba (Qwen Team)
Required GPUs
8× Nvidia A100 SXM
VRAM gesamt
320 GB
Parameters
480B
Context
1M tokens
Minimax M1 80K
by MiniMax
Required GPUs
8× Nvidia A100 SXM
VRAM gesamt
320 GB
Parameters
456B
Context
1M tokens
MiniMax-Text-01
by MiniMax
Required GPUs
8× Nvidia A100 SXM
VRAM gesamt
320 GB
Parameters
456B (46B active)
Context
4M tokens
MiniMax M1
by MiniMax
Required GPUs
8× Nvidia A100 SXM
VRAM gesamt
320 GB
Parameters
456B
Context
1M tokens
MiniMax M3
by MiniMax
Required GPUs
8× Nvidia A100 SXM
VRAM gesamt
320 GB
Parameters
427B
Context
1M tokens
ERNIE 4.5 VL 424B A47B
by Baidu
Required GPUs
8× Nvidia A100 SXM
VRAM gesamt
320 GB
Parameters
424B
Context
131K tokens
?
INT4
Hermes 3 405B Instruct
by Nous Research
Required GPUs
8× Nvidia A100 SXM
VRAM gesamt
320 GB
Parameters
405B
Context
131K tokens
?
INT4
Hermes 4 405B
by Nous Research
Required GPUs
8× Nvidia A100 SXM
VRAM gesamt
320 GB
Parameters
405B
Context
131K tokens
Llama 3.1 405B
by Meta AI
Required GPUs
8× Nvidia A100 SXM
VRAM gesamt
320 GB
Parameters
405B
Context
128K tokens
Llama 4 Maverick
by Meta AI
Required GPUs
8× Nvidia A100 SXM
VRAM gesamt
320 GB
Parameters
402B
Context
1M tokens
Trinity Large Thinking
by Arcee AI
Required GPUs
8× Nvidia A100 SXM
VRAM gesamt
320 GB
Parameters
399B
Context
512K tokens
Qwen3.5 397B A17B
by Alibaba (Qwen Team)
Required GPUs
8× Nvidia A100 SXM
VRAM gesamt
320 GB
Parameters
397B
Context
262K tokens
?
INT4
Nex-N2-Pro
by Nex Agi
Required GPUs
8× Nvidia A100 SXM
VRAM gesamt
320 GB
Parameters
397B
Context
262K tokens
?
INT4
Nex-N2.5-Pro
by Nex Agi
Required GPUs
8× Nvidia A100 SXM
VRAM gesamt
320 GB
Parameters
397B
Context
262K tokens
Hunyuan-Large
by Tencent
Required GPUs
8× Nvidia A100 SXM
VRAM gesamt
320 GB
Parameters
389B (52B active)
Context
256K tokens
GLM-4.7
by Zhipu AI
Required GPUs
8× Nvidia A100 SXM
VRAM gesamt
320 GB
Parameters
358B
Context
205K tokens
GLM-4.6
by Zhipu AI
Required GPUs
8× Nvidia A100 SXM
VRAM gesamt
320 GB
Parameters
357B
Context
205K tokens
GLM-4.5
by Zhipu AI
Required GPUs
8× Nvidia A100 SXM
VRAM gesamt
320 GB
Parameters
355B (32B active)
Context
128K tokens
GLM 5.3 Flash
by Zhipu AI
Required GPUs
8× Nvidia A100 SXM
VRAM gesamt
320 GB
Parameters
321B
Context
1M tokens
MiMo-V2.5
by Xiaomi
Required GPUs
8× Nvidia A100 SXM
VRAM gesamt
320 GB
Parameters
315B
Context
1M tokens
MiMo-V2.6-Flash
by Xiaomi
Required GPUs
8× Nvidia A100 SXM
VRAM gesamt
320 GB
Parameters
311B
Context
1M tokens
MiMo-V2-Flash
by Xiaomi
Required GPUs
8× Nvidia A100 SXM
VRAM gesamt
320 GB
Parameters
310B
Context
256K tokens
DeepSeek V4 Flash Vision Exp
by DeepSeek
Required GPUs
8× Nvidia A100 SXM
VRAM gesamt
320 GB
Parameters
305B
Context
1M tokens
DeepSeek V4 Flash 0731
by DeepSeek
Required GPUs
8× Nvidia A100 SXM
VRAM gesamt
320 GB
Parameters
304B
Context
1M tokens
ERNIE 4.5 300B A47B
by Baidu
Required GPUs
8× Nvidia A100 SXM
VRAM gesamt
320 GB
Parameters
300B
Context
131K tokens
Hy3 preview
by Tencent
Required GPUs
8× Nvidia A100 SXM
VRAM gesamt
320 GB
Parameters
299B
Context
262K tokens
Hy3
by Tencent
Required GPUs
8× Nvidia A100 SXM
VRAM gesamt
320 GB
Parameters
299B
Context
262K tokens
DeepSeek V4 Flash
by DeepSeek
Required GPUs
8× Nvidia A100 SXM
VRAM gesamt
320 GB
Parameters
292B
Context
1M tokens
?
FP8
Inkling Small
by Thinking Machines
Required GPUs
8× Nvidia A100 SXM
VRAM gesamt
320 GB
Parameters
266B
Context
524K tokens
DeepSeek Coder V2 236B
by DeepSeek
Required GPUs
4× Nvidia A100 SXM
VRAM gesamt
160 GB
Parameters
236B (21B active)
Context
128K tokens
Qwen3 235B A22B Instruct 2507
by Alibaba (Qwen Team)
Required GPUs
4× Nvidia A100 SXM
VRAM gesamt
160 GB
Parameters
235B
Context
262K tokens
Qwen 3 235B
by Alibaba (Qwen Team)
Required GPUs
4× Nvidia A100 SXM
VRAM gesamt
160 GB
Parameters
235B (22B active)
Context
131K tokens
Qwen3 VL 235B A22B Thinking
by Alibaba (Qwen Team)
Required GPUs
4× Nvidia A100 SXM
VRAM gesamt
160 GB
Parameters
235B
Context
1M tokens
Qwen3 Max
by Alibaba (Qwen Team)
Required GPUs
4× Nvidia A100 SXM
VRAM gesamt
160 GB
Parameters
235B
Context
262K tokens
Qwen3 235B A22B Thinking 2507
by Alibaba (Qwen Team)
Required GPUs
4× Nvidia A100 SXM
VRAM gesamt
160 GB
Parameters
235B
Context
1M tokens
Qwen3 VL 235B A22B Instruct
by Alibaba (Qwen Team)
Required GPUs
4× Nvidia A100 SXM
VRAM gesamt
160 GB
Parameters
235B
Context
262K tokens
MiniMax M2.5
by MiniMax
Required GPUs
4× Nvidia A100 SXM
VRAM gesamt
160 GB
Parameters
230B
Context
205K tokens
MiniMax M2.7
by MiniMax
Required GPUs
4× Nvidia A100 SXM
VRAM gesamt
160 GB
Parameters
230B
Context
205K tokens
MiniMax M2.1
by MiniMax
Required GPUs
4× Nvidia A100 SXM
VRAM gesamt
160 GB
Parameters
230B
Context
205K tokens
MiniMax M2
by MiniMax
Required GPUs
4× Nvidia A100 SXM
VRAM gesamt
160 GB
Parameters
229B
Context
205K tokens
MiniMax M3.1 Flash
by MiniMax
Required GPUs
4× Nvidia A100 SXM
VRAM gesamt
160 GB
Parameters
220B
Context
1M tokens
Step 3.7 Flash
by StepFun
Required GPUs
4× Nvidia A100 SXM
VRAM gesamt
160 GB
Parameters
201B
Context
256K tokens
?
INT4
Seed-1.8
by ByteDance (Seed team)
Required GPUs
4× Nvidia A100 SXM
VRAM gesamt
160 GB
Parameters
200B
Context
256K tokens
Step 3.5 Flash
by StepFun
Required GPUs
4× Nvidia A100 SXM
VRAM gesamt
160 GB
Parameters
199B
Context
262K tokens
Mixtral 8x22B
by Mistral AI
Required GPUs
4× Nvidia A100 SXM
VRAM gesamt
160 GB
Parameters
141B (39B active)
Context
66K tokens
Devstral 2 2512
by Mistral AI
Required GPUs
2× Nvidia A100 SXM
VRAM gesamt
80 GB
Parameters
128B
Context
262K tokens
?
INT4
Ling-3.0-flash
by Inclusionai
Required GPUs
2× Nvidia A100 SXM
VRAM gesamt
80 GB
Parameters
127B
Context
131K tokens
?
INT4
Ling 3.0 Flash Fin
by Inclusionai
Required GPUs
2× Nvidia A100 SXM
VRAM gesamt
80 GB
Parameters
127B
Context
256K tokens
?
INT4
Ling-3.0-flash-VL
by Inclusionai
Required GPUs
2× Nvidia A100 SXM
VRAM gesamt
80 GB
Parameters
125B
Context
131K tokens
Mistral Large 2
by Mistral AI
Required GPUs
2× Nvidia A100 SXM
VRAM gesamt
80 GB
Parameters
123B
Context
128K tokens
Qwen3.5-122B-A10B
by Alibaba (Qwen Team)
Required GPUs
2× Nvidia A100 SXM
VRAM gesamt
80 GB
Parameters
122B
Context
262K tokens
Mistral Small 4
by Mistral AI
Required GPUs
2× Nvidia A100 SXM
VRAM gesamt
80 GB
Parameters
121B
Context
262K tokens
Nemotron 3 Super
by Nvidia
Required GPUs
2× Nvidia A100 SXM
VRAM gesamt
80 GB
Parameters
120B
Context
1M tokens
GPT-OSS 120B
by OpenAI
Required GPUs
2× Nvidia A100 SXM
VRAM gesamt
80 GB
Parameters
120B (5B active)
Context
128K tokens
?
INT4
Laguna S 2.1
by Poolside
Required GPUs
2× Nvidia A100 SXM
VRAM gesamt
80 GB
Parameters
118B
Context
1M tokens
Llama 4 Scout (17Bx16E)
by Meta AI
Required GPUs
2× Nvidia A100 SXM
VRAM gesamt
80 GB
Parameters
109B
Context
262K tokens
Llama 4 Scout
by Meta AI
Required GPUs
2× Nvidia A100 SXM
VRAM gesamt
80 GB
Parameters
109B
Context
10M tokens
GLM 4.5V
by Zhipu AI
Required GPUs
2× Nvidia A100 SXM
VRAM gesamt
80 GB
Parameters
108B
Context
66K tokens
GLM 4.6V
by Zhipu AI
Required GPUs
2× Nvidia A100 SXM
VRAM gesamt
80 GB
Parameters
108B
Context
131K tokens
Renting for inference?
Pair these models with the cheapest provider on the rental table.
See rental rates on the Overview tab →