datacenter
Alquilar Nvidia H100.
Hopper
80GB VRAM
From $2.29/hr
Per hour
$2.29
Per day
$54.96
Per week
$384.72
Per month
$1649
Provider spread
3 providers ·
up to 28% cheaper at the low end
Cheapest · $2.29/hr on Theta EdgeCloud
Median $2.81/hr
Most expensive · $3.20/hr on Thunder Compute
Price history
Daily median across providers.
Loading...
Where to rent it
All providers carrying this GPU.
Workloads
Suitable workloads.
AI models that fit
See all 58 →
Run these on this GPU.
- Llama 3.1 405B 8× · fp16
- Kimi K2 8× · fp8
- DeepSeek V3 8× · fp8
Cloud instances
See all 72 →
Hyperscaler bundles.
Pre-configured on 2 clouds — from $2.29/hr total
($2.29/hr per GPU).
FAQ
Frequently asked.
How much does it cost to rent the Nvidia H100 right now?
The cheapest current listing is $2.29/hr on Theta EdgeCloud, and the median across the 3 providers listing it is $2.81/hr. Running one around the clock for a month (730 hours) at the cheapest rate costs about $1,672.
What AI models can the Nvidia H100 run?
With 80 GB it holds a 70B model at INT8/FP8 (about 70 GB of weights) on one card, or at 4-bit with plenty of room for long contexts and many concurrent requests. It can QLoRA fine-tune 70B models. FP16 70B (about 140 GB) needs two cards.
Which models are recommended for the Nvidia H100?
56 models in our catalog have a recommended configuration for this card, with the quantization that fits its 80 GB — see the AI models tab.
Why does the Nvidia H100 cost different amounts on different providers?
Marketplaces such as Vast.ai and Clore.ai list machines from independent hosts who set their own prices, so competition pushes rates down but reliability varies by host. Operator clouds such as Lambda and the hyperscalers charge more for consistent hardware, support and networking. Prices here are per GPU, so they compare directly.
How is the Nvidia H100 price calculated?
We collect listings from each provider's public API or price page — every 5–10 minutes for marketplaces, up to daily for operator clouds — and show the median hourly price per provider from the last 24 hours, so one unusually cheap listing doesn't set the headline. Details are on the methodology page.
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
$2.29/hr
Lowest $/hr per GPU
$2.29/hr
Providers
2
Instance shapes
72
| Provider | Instance | GPUs | vCPU | RAM | Disk | $/hr | $/hr per GPU | |
|---|---|---|---|---|---|---|---|---|
| G-H100_80GB-x1 | 1× | 10 | 80 GB | 512 GB | $2.29/hr | $2.29/hr | ||
| G-H100_80GB-x1 | 1× | 10 | 80 GB | 512 GB | $2.29/hr | $2.29/hr | ||
| G-H100_80GB-x1 | 1× | 10 | 80 GB | 512 GB | $2.29/hr | $2.29/hr | ||
| G-H100_80GB-x1 | 1× | 10 | 80 GB | 512 GB | $2.29/hr | $2.29/hr | ||
| G-H100_80GB-x1 | 1× | 10 | 80 GB | 512 GB | $2.29/hr | $2.29/hr | ||
| G-H100_80GB-x1 | 1× | 10 | 80 GB | 512 GB | $2.29/hr | $2.29/hr | ||
| G-H100_80GB-x1 | 1× | 10 | 80 GB | 512 GB | $2.29/hr | $2.29/hr | ||
| G-H100_80GB-x1 | 1× | 10 | 80 GB | 512 GB | $2.29/hr | $2.29/hr | ||
| G-H100_80GB-x1 | 1× | 10 | 80 GB | 512 GB | $2.29/hr | $2.29/hr | ||
| G-H100_80GB-x1 | 1× | 10 | 80 GB | 512 GB | $2.29/hr | $2.29/hr | ||
| G-H100_80GB-x1 | 1× | 10 | 80 GB | 512 GB | $2.29/hr | $2.29/hr | ||
| G-H100_80GB-x1 | 1× | 10 | 80 GB | 512 GB | $2.29/hr | $2.29/hr | ||
| G-H100_80GB-x1 | 1× | 10 | 80 GB | 512 GB | $2.29/hr | $2.29/hr | ||
| G-H100_80GB-x1 | 1× | 10 | 80 GB | 512 GB | $2.29/hr | $2.29/hr | ||
| G-H100_80GB-x1 | 1× | 10 | 80 GB | 512 GB | $2.29/hr | $2.29/hr | ||
| G-H100_80GB-x1 | 1× | 10 | 80 GB | 512 GB | $2.29/hr | $2.29/hr | ||
| G-H100_80GB-x1 | 1× | 10 | 80 GB | 512 GB | $2.29/hr | $2.29/hr | ||
| G-H100_80GB-x1 | 1× | 10 | 80 GB | 512 GB | $2.29/hr | $2.29/hr | ||
| G-H100_80GB-x1 | 1× | 10 | 80 GB | 512 GB | $2.29/hr | $2.29/hr | ||
| h100_native | 1× | 4 | 32 GB | 100 GB | $3.20/hr | $3.20/hr | ||
| h100_native | 1× | 4 | 32 GB | 100 GB | $3.20/hr | $3.20/hr | ||
| h100_native | 1× | 4 | 32 GB | 100 GB | $3.20/hr | $3.20/hr | ||
| h100_x1 | 1× | 4 | 32 GB | 100 GB | $3.20/hr | $3.20/hr | ||
| h100_x1 | 1× | 4 | 32 GB | 100 GB | $3.20/hr | $3.20/hr | ||
| h100_x1 | 1× | 4 | 32 GB | 100 GB | $3.20/hr | $3.20/hr | ||
| G-H100_80GB-x2 | 2× | 20 | 160 GB | 1024 GB | $4.58/hr | $2.29/hr | ||
| G-H100_80GB-x2 | 2× | 20 | 160 GB | 1024 GB | $4.58/hr | $2.29/hr | ||
| G-H100_80GB-x2 | 2× | 20 | 160 GB | 1024 GB | $4.58/hr | $2.29/hr | ||
| G-H100_80GB-x2 | 2× | 20 | 160 GB | 1024 GB | $4.58/hr | $2.29/hr | ||
| G-H100_80GB-x2 | 2× | 20 | 160 GB | 1024 GB | $4.58/hr | $2.29/hr | ||
| G-H100_80GB-x2 | 2× | 20 | 160 GB | 1024 GB | $4.58/hr | $2.29/hr | ||
| G-H100_80GB-x2 | 2× | 20 | 160 GB | 1024 GB | $4.58/hr | $2.29/hr | ||
| G-H100_80GB-x2 | 2× | 20 | 160 GB | 1024 GB | $4.58/hr | $2.29/hr | ||
| G-H100_80GB-x2 | 2× | 20 | 160 GB | 1024 GB | $4.58/hr | $2.29/hr | ||
| G-H100_80GB-x2 | 2× | 20 | 160 GB | 1024 GB | $4.58/hr | $2.29/hr | ||
| G-H100_80GB-x2 | 2× | 20 | 160 GB | 1024 GB | $4.58/hr | $2.29/hr | ||
| G-H100_80GB-x2 | 2× | 20 | 160 GB | 1024 GB | $4.58/hr | $2.29/hr | ||
| G-H100_80GB-x2 | 2× | 20 | 160 GB | 1024 GB | $4.58/hr | $2.29/hr | ||
| G-H100_80GB-x2 | 2× | 20 | 160 GB | 1024 GB | $4.58/hr | $2.29/hr | ||
| G-H100_80GB-x2 | 2× | 20 | 160 GB | 1024 GB | $4.58/hr | $2.29/hr | ||
| G-H100_80GB-x2 | 2× | 20 | 160 GB | 1024 GB | $4.58/hr | $2.29/hr | ||
| G-H100_80GB-x2 | 2× | 20 | 160 GB | 1024 GB | $4.58/hr | $2.29/hr | ||
| G-H100_80GB-x2 | 2× | 20 | 160 GB | 1024 GB | $4.58/hr | $2.29/hr | ||
| G-H100_80GB-x2 | 2× | 20 | 160 GB | 1024 GB | $4.58/hr | $2.29/hr | ||
| h100_x2 | 2× | 8 | 64 GB | 100 GB | $6.40/hr | $3.20/hr | ||
| h100_x2 | 2× | 8 | 64 GB | 100 GB | $6.40/hr | $3.20/hr | ||
| h100_x2 | 2× | 8 | 64 GB | 100 GB | $6.40/hr | $3.20/hr | ||
| G-H100_80GB-x4 | 4× | 40 | 320 GB | 1024 GB | $9.16/hr | $2.29/hr | ||
| G-H100_80GB-x4 | 4× | 40 | 320 GB | 1024 GB | $9.16/hr | $2.29/hr | ||
| G-H100_80GB-x4 | 4× | 40 | 320 GB | 1024 GB | $9.16/hr | $2.29/hr | ||
| G-H100_80GB-x4 | 4× | 40 | 320 GB | 1024 GB | $9.16/hr | $2.29/hr | ||
| G-H100_80GB-x4 | 4× | 40 | 320 GB | 1024 GB | $9.16/hr | $2.29/hr | ||
| G-H100_80GB-x4 | 4× | 40 | 320 GB | 1024 GB | $9.16/hr | $2.29/hr | ||
| G-H100_80GB-x4 | 4× | 40 | 320 GB | 1024 GB | $9.16/hr | $2.29/hr | ||
| G-H100_80GB-x4 | 4× | 40 | 320 GB | 1024 GB | $9.16/hr | $2.29/hr | ||
| G-H100_80GB-x4 | 4× | 40 | 320 GB | 1024 GB | $9.16/hr | $2.29/hr | ||
| G-H100_80GB-x4 | 4× | 40 | 320 GB | 1024 GB | $9.16/hr | $2.29/hr | ||
| G-H100_80GB-x4 | 4× | 40 | 320 GB | 1024 GB | $9.16/hr | $2.29/hr | ||
| G-H100_80GB-x4 | 4× | 40 | 320 GB | 1024 GB | $9.16/hr | $2.29/hr | ||
| G-H100_80GB-x4 | 4× | 40 | 320 GB | 1024 GB | $9.16/hr | $2.29/hr | ||
| G-H100_80GB-x4 | 4× | 40 | 320 GB | 1024 GB | $9.16/hr | $2.29/hr | ||
| G-H100_80GB-x4 | 4× | 40 | 320 GB | 1024 GB | $9.16/hr | $2.29/hr | ||
| G-H100_80GB-x4 | 4× | 40 | 320 GB | 1024 GB | $9.16/hr | $2.29/hr | ||
| G-H100_80GB-x4 | 4× | 40 | 320 GB | 1024 GB | $9.16/hr | $2.29/hr | ||
| G-H100_80GB-x4 | 4× | 40 | 320 GB | 1024 GB | $9.16/hr | $2.29/hr | ||
| G-H100_80GB-x4 | 4× | 40 | 320 GB | 1024 GB | $9.16/hr | $2.29/hr | ||
| h100_x4 | 4× | 60 | 480 GB | 100 GB | $12.80/hr | $3.20/hr | ||
| h100_x4 | 4× | 60 | 480 GB | 100 GB | $12.80/hr | $3.20/hr | ||
| h100_x4 | 4× | 60 | 480 GB | 100 GB | $12.80/hr | $3.20/hr | ||
| h100_x8 | 8× | 120 | 960 GB | 100 GB | $25.60/hr | $3.20/hr | ||
| h100_x8 | 8× | 120 | 960 GB | 100 GB | $25.60/hr | $3.20/hr | ||
| h100_x8 | 8× | 120 | 960 GB | 100 GB | $25.60/hr | $3.20/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.
How much does it cost to rent the Nvidia H100 right now?
The cheapest current listing is $2.29/hr on Theta EdgeCloud, and the median across the 3 providers listing it is $2.81/hr. Running one around the clock for a month (730 hours) at the cheapest rate costs about $1,672.
What AI models can the Nvidia H100 run?
With 80 GB it holds a 70B model at INT8/FP8 (about 70 GB of weights) on one card, or at 4-bit with plenty of room for long contexts and many concurrent requests. It can QLoRA fine-tune 70B models. FP16 70B (about 140 GB) needs two cards.
Which models are recommended for the Nvidia H100?
56 models in our catalog have a recommended configuration for this card, with the quantization that fits its 80 GB — see the AI models tab.
Why does the Nvidia H100 cost different amounts on different providers?
Marketplaces such as Vast.ai and Clore.ai list machines from independent hosts who set their own prices, so competition pushes rates down but reliability varies by host. Operator clouds such as Lambda and the hyperscalers charge more for consistent hardware, support and networking. Prices here are per GPU, so they compare directly.
How is the Nvidia H100 price calculated?
We collect listings from each provider's public API or price page — every 5–10 minutes for marketplaces, up to daily for operator clouds — and show the median hourly price per provider from the last 24 hours, so one unusually cheap listing doesn't set the headline. Details are on the methodology page.
AI models
FP16
FP8
FP8
FP16
FP16
FP16
INT4
FP16
FP16
FP16
FP16
FP16
FP16
FP16
FP16
FP16
FP16
FP16
FP16
FP16
FP16
FP16
FP16
FP16
FP16
FP16
FP16
FP16
FP16
FP16
FP16
FP16
FP16
FP16
FP16
FP16
FP16
FP16
FP16
FP16
FP16
FP16
FP16
FP16
INT4
INT4
INT4
INT4
INT4
INT4
INT4
INT4
INT4
INT4
INT4
INT4
Models that run on this GPU.
GPU-count + quantization recommendations covering fine-tuning, inference, and run-it-yourself scenarios on the Nvidia H100.
Llama 3.1 405B
by Meta AI
Required GPUs
8× Nvidia H100
Total VRAM
640 GB
Parameters
405B
Context
128K tokens
Standard datacenter setup
?
FP8
Kimi K2
by Moonshot AI
Required GPUs
8× Nvidia H100
Total VRAM
640 GB
Parameters
1000B (32B active)
Context
256K tokens
MoE — only active experts loaded per token
DeepSeek V3
by DeepSeek
Required GPUs
8× Nvidia H100
Total VRAM
640 GB
Parameters
671B (37B active)
Context
128K tokens
MoE deployment, ~37B active params
DeepSeek R1
by DeepSeek
Required GPUs
8× Nvidia H100
Total VRAM
640 GB
Parameters
671B (37B active)
Context
128K tokens
DeepSeek R1 Distill Llama 70B
by DeepSeek
Required GPUs
2× Nvidia H100
Total VRAM
160 GB
Parameters
70B
Context
128K tokens
DeepSeek R1 Distill Qwen 32B
by DeepSeek
Required GPUs
1× Nvidia H100
Total VRAM
80 GB
Parameters
33B
Context
128K tokens
Llama 3.1 70B
by Meta AI
Required GPUs
2× Nvidia H100
Total VRAM
160 GB
Parameters
70B
Context
128K tokens
Mistral Large 2
by Mistral AI
Required GPUs
1× Nvidia H100
Total VRAM
80 GB
Parameters
123B
Context
128K tokens
Llama 3.3 70B
by Meta AI
Required GPUs
2× Nvidia H100
Total VRAM
160 GB
Parameters
70B
Context
128K tokens
Mixtral 8x22B
by Mistral AI
Required GPUs
4× Nvidia H100
Total VRAM
320 GB
Parameters
141B (39B active)
Context
66K tokens
Qwen 2.5 72B
by Alibaba (Qwen Team)
Required GPUs
2× Nvidia H100
Total VRAM
160 GB
Parameters
73B
Context
128K tokens
Gemma 3 27B
by Google DeepMind
Required GPUs
1× Nvidia H100
Total VRAM
80 GB
Parameters
27B (27B active)
Context
128K tokens
Gemma 2 27B
by Google DeepMind
Required GPUs
1× Nvidia H100
Total VRAM
80 GB
Parameters
27B
Context
8K tokens
Qwen: Qwen3.6 27B
by Alibaba (Qwen Team)
Required GPUs
1× Nvidia H100
Total VRAM
80 GB
Parameters
27B
Context
262K tokens
Qwen: Qwen3.5-27B
by Alibaba (Qwen Team)
Required GPUs
1× Nvidia H100
Total VRAM
80 GB
Parameters
27B
Context
262K tokens
NVIDIA: Nemotron 3 Nano 30B A3B
by Nvidia
Required GPUs
1× Nvidia H100
Total VRAM
80 GB
Parameters
30B
Context
262K tokens
AllenAI: Olmo 3 32B Think
by Allen Institute for AI (AI2)
Required GPUs
1× Nvidia H100
Total VRAM
80 GB
Parameters
32B
Context
66K tokens
Qwen: Qwen3 VL 32B Instruct
by Alibaba (Qwen Team)
Required GPUs
1× Nvidia H100
Total VRAM
80 GB
Parameters
32B
Context
262K tokens
Qwen: Qwen3 VL 30B A3B Thinking
by Alibaba (Qwen Team)
Required GPUs
1× Nvidia H100
Total VRAM
80 GB
Parameters
30B
Context
131K tokens
Qwen: Qwen3 VL 30B A3B Instruct
by Alibaba (Qwen Team)
Required GPUs
1× Nvidia H100
Total VRAM
80 GB
Parameters
30B
Context
262K tokens
Tongyi DeepResearch 30B A3B
by Alibaba (Qwen Team)
Required GPUs
1× Nvidia H100
Total VRAM
80 GB
Parameters
30B
Context
131K tokens
Qwen: Qwen3 30B A3B Thinking 2507
by Alibaba (Qwen Team)
Required GPUs
1× Nvidia H100
Total VRAM
80 GB
Parameters
30B
Context
131K tokens
Qwen: Qwen3 Coder 30B A3B Instruct
by Alibaba (Qwen Team)
Required GPUs
1× Nvidia H100
Total VRAM
80 GB
Parameters
30B
Context
160K tokens
Qwen: Qwen3 30B A3B Instruct 2507
by Alibaba (Qwen Team)
Required GPUs
1× Nvidia H100
Total VRAM
80 GB
Parameters
30B
Context
262K tokens
Z.ai: GLM 4 32B
by Zhipu AI
Required GPUs
1× Nvidia H100
Total VRAM
80 GB
Parameters
32B
Context
128K tokens
Qwen: Qwen3 30B A3B
by Alibaba (Qwen Team)
Required GPUs
1× Nvidia H100
Total VRAM
80 GB
Parameters
30B
Context
131K tokens
Qwen: Qwen3 32B
by Alibaba (Qwen Team)
Required GPUs
1× Nvidia H100
Total VRAM
80 GB
Parameters
32B
Context
131K tokens
GLM-5.1
by Zhipu AI
Required GPUs
1× Nvidia H100
Total VRAM
80 GB
Parameters
32B
Context
203K tokens
?
FP16
ByteDance Seed: Seed-2.0-Lite
by Bytedance Seed
Required GPUs
1× Nvidia H100
Total VRAM
80 GB
Parameters
32B
Context
262K tokens
Baidu: ERNIE 4.5 VL 28B A3B
by Baidu
Required GPUs
1× Nvidia H100
Total VRAM
80 GB
Parameters
28B
Context
131K tokens
Qwen2.5 32B
by Alibaba (Qwen Team)
Required GPUs
1× Nvidia H100
Total VRAM
80 GB
Parameters
32B
Context
131K tokens
Nemotron 3 Nano Omni 30B A3b Reasoning Fp8
by Nvidia
Required GPUs
1× Nvidia H100
Total VRAM
80 GB
Parameters
30B
Context
131K tokens
Cogito V1 Preview Qwen 32B
by Deepcogito
Required GPUs
1× Nvidia H100
Total VRAM
80 GB
Parameters
32B
Context
131K tokens
Gemma 3 27B It
by Google DeepMind
Required GPUs
1× Nvidia H100
Total VRAM
80 GB
Parameters
27B
Context
66K tokens
Qwen QwQ-32B
by Alibaba (Qwen Team)
Required GPUs
1× Nvidia H100
Total VRAM
80 GB
Parameters
32B
Context
131K tokens
Qwen 2.5 Coder 32B Instruct
by Alibaba (Qwen Team)
Required GPUs
1× Nvidia H100
Total VRAM
80 GB
Parameters
32B
Context
16K tokens
Qwen3 30B A3b Base
by Alibaba (Qwen Team)
Required GPUs
1× Nvidia H100
Total VRAM
80 GB
Parameters
30B
Context
33K tokens
Gemma 3 27B Pt
by Google DeepMind
Required GPUs
1× Nvidia H100
Total VRAM
80 GB
Parameters
27B
Qwen3 30B A3B Instruct 2507 Lora
by Alibaba (Qwen Team)
Required GPUs
1× Nvidia H100
Total VRAM
80 GB
Parameters
30B
Context
262K tokens
Nvidia Nemotron 3 Nano 30B A3b Bf16
by Nvidia
Required GPUs
1× Nvidia H100
Total VRAM
80 GB
Parameters
30B
Context
262K tokens
Medgemma 27B Text It
by Google DeepMind
Required GPUs
1× Nvidia H100
Total VRAM
80 GB
Parameters
27B
Context
131K tokens
Qwen2.5 32B Instruct
by Alibaba (Qwen Team)
Required GPUs
1× Nvidia H100
Total VRAM
80 GB
Parameters
32B
Context
33K tokens
Gemma 3 27B It Lora
by Google DeepMind
Required GPUs
1× Nvidia H100
Total VRAM
80 GB
Parameters
27B
Gemma 4 31B It Lora
by Google DeepMind
Required GPUs
1× Nvidia H100
Total VRAM
80 GB
Parameters
31B
Context
262K tokens
Nemotron-3-Nano-Omni-30B-A3B-Reasoning
by Nvidia
Required GPUs
1× Nvidia H100
Total VRAM
80 GB
Parameters
30B
Context
262K tokens
gemma-4-31B-it-turbo
by Google DeepMind
Required GPUs
1× Nvidia H100
Total VRAM
80 GB
Parameters
31B
Context
262K tokens
Qwen3.5 122B A10b Fp8
by Alibaba (Qwen Team)
Required GPUs
1× Nvidia H100
Total VRAM
80 GB
Parameters
122B
Context
262K tokens
DeepSeek R1 Distill Llama 70B
by DeepSeek
Required GPUs
1× Nvidia H100
Total VRAM
80 GB
Parameters
70B
Context
128K tokens
Single H100 with INT4 — sweet spot.
Llama 3.1 70B
by Meta AI
Required GPUs
1× Nvidia H100
Total VRAM
80 GB
Parameters
70B
Context
128K tokens
Qwen: Qwen3.5-122B-A10B
by Alibaba (Qwen Team)
Required GPUs
1× Nvidia H100
Total VRAM
80 GB
Parameters
122B
Context
262K tokens
Nvidia Nemotron 3 Super 120B A12b Fp8
by Nvidia
Required GPUs
1× Nvidia H100
Total VRAM
80 GB
Parameters
120B
Context
262K tokens
Nvidia Nemotron 3 Super 120B A12b Bf16
by Nvidia
Required GPUs
1× Nvidia H100
Total VRAM
80 GB
Parameters
120B
Context
262K tokens
GPT-OSS 120B
by OpenAI
Required GPUs
1× Nvidia H100
Total VRAM
80 GB
Parameters
120B (5B active)
Context
128K tokens
Command R+
by Cohere
Required GPUs
1× Nvidia H100
Total VRAM
80 GB
Parameters
104B
Context
128K tokens
GLM-4.5-Air
by Zhipu AI
Required GPUs
1× Nvidia H100
Total VRAM
80 GB
Parameters
106B (12B active)
Context
128K tokens
NVIDIA: Nemotron 3 Super
by Nvidia
Required GPUs
1× Nvidia H100
Total VRAM
80 GB
Parameters
120B
Context
1M tokens
NVIDIA-Nemotron-3-Super-120B-A12B
by Nvidia
Required GPUs
1× Nvidia H100
Total VRAM
80 GB
Parameters
120B
Context
262K tokens
gpt-oss-120b-Turbo
by OpenAI
Required GPUs
1× Nvidia H100
Total VRAM
80 GB
Parameters
120B
Context
131K tokens
Renting for inference?
Pair these models with the cheapest provider on the rental table.
See rental rates on the Overview tab →
FAQ
AI models on this GPU.
How much does it cost to rent the Nvidia H100 right now?
The cheapest current listing is $2.29/hr on Theta EdgeCloud, and the median across the 3 providers listing it is $2.81/hr. Running one around the clock for a month (730 hours) at the cheapest rate costs about $1,672.
What AI models can the Nvidia H100 run?
With 80 GB it holds a 70B model at INT8/FP8 (about 70 GB of weights) on one card, or at 4-bit with plenty of room for long contexts and many concurrent requests. It can QLoRA fine-tune 70B models. FP16 70B (about 140 GB) needs two cards.
Which models are recommended for the Nvidia H100?
56 models in our catalog have a recommended configuration for this card, with the quantization that fits its 80 GB — see the AI models tab.
Why does the Nvidia H100 cost different amounts on different providers?
Marketplaces such as Vast.ai and Clore.ai list machines from independent hosts who set their own prices, so competition pushes rates down but reliability varies by host. Operator clouds such as Lambda and the hyperscalers charge more for consistent hardware, support and networking. Prices here are per GPU, so they compare directly.
How is the Nvidia H100 price calculated?
We collect listings from each provider's public API or price page — every 5–10 minutes for marketplaces, up to daily for operator clouds — and show the median hourly price per provider from the last 24 hours, so one unusually cheap listing doesn't set the headline. Details are on the methodology page.