NVIDIA A100 Price Update with Specs and Availability Info

In 2025, AI reigns supreme—with GPT-grade LLMs, computer vision, simulation, and scientific computing taking center stage. But there's one piece of hardware powering these breakthroughs like nothing else: the NVIDIA A100 GPU. Three years after its introduction, it's still widely regarded as the go-to workhorse for serious AI workloads. According to Runpod, “due to its availability and lower cost relative to H100, the A100 often hits a sweet spot for AI projects in 2024/2025”

That raises the natural question—what does the A100 cost today, and how much can you expect to pay to run it in your data center or in the cloud? In this blog, we’ll cover updated NVIDIA A100 price ranges, feature deep-dives into its specs, cloud rental rates, and availability. Whether you're buying hardware or renting GPU instances, you'll get a clear picture to help with budgeting. Let’s begin.

Inside the A100: Specs for Heavy-Duty AI and HPC

NVIDIA’s A100 is part of the Ampere generation and comes with high-end specs tailored to compute-intensive workloads:

CUDA Cores: 6,912

Tensor Cores: 432 (3rd-gen Ampere)

Memory: 40 GB or 80 GB HBM2e

Memory Bandwidth: 1.6 TB/s (40 GB) / 2.0 TB/s (80 GB)

Performance:

FP32: 19.5 TFLOPS

FP64 Tensor: 19.5 TFLOPS (ampere)

TF32, BFLOAT16, FP16: Up to 312 TFLOPS

INT8: Up to 624 TOPS

TDP: 300–400 W

MIG Support: up to 7 instances per GPU

This combination of high memory, huge bandwidth, tensor speeds, and partitioning makes the A100 ideal for large model training, inference, HPC, and mixed workloads. NVIDIA's spec page confirms these details.

NVIDIA A100 Price: On-Prem Hardware (2025)

Buying A100 cards outright still involves a multi-thousand-dollar investment. According to Cyfuture Cloud's recent data:

A100 40 GB: approximately $7,500–$10,000

A100 80 GB: approximately $9,500–$14,000

These prices reflect global average, region-based markup, and the used market. PCIe versions tend to be cheaper, while server-ready SXM modules or enterprise batches could push the cost to the $14K upper range.

Renting A100: Cloud and Non-Hyperscale Prices

Hyperscale Clouds

These are typically the highest by default:

Google Cloud, AWS p4d.24xlarge, Azure ND96asr:
Expect $4–4.3/hour per A100 GPU Google charges $4.27/h for their single A100 instance.

Non-Hyperscaler Clouds

Offer aggressive pricing with equivalent hardware:

Thunder Compute: A100 40 GB at $0.66/hr

Lambda GPU Cloud:

A100 40 GB: $1.29/hr

A100 SXM 80 GB: $1.79/hr

TensorDock: A100 instances from $1.63/hr, with spot at $0.67/hr

Hyperstack: A100 PCIe 80 GB for $1.35/hr on-demand and $0.95/hr reserved

DataCrunch: A100 SXM 80/40 GB at $1.115–1.12/hr (2-year contract: $0.84/hr)

Summary: Cost per GPU Hour

Even the best hyperscale discounts lag behind specialist providers by 3–6x.

Availability and Accessibility Today

A100 remains widely available, while H100 allocation is limited and costly

Non-hyperscaler clouds report easy provisioning for single or few GPUs—ideal for startups and research labs. Providers like Lambda, Thunder, TensorDock, DataCrunch, and Hyperstack are often faster to spin up than AWS/Azure spots.

Hyperscalers require pre-approval and may impose quotas

On-prem SXM GPUs need compatible servers and cooling infrastructure—capex-heavy but offering full control.

Calculate Your Monthly GPU Budget

Assuming continuous use for training (assuming 100 hrs/month):

Thunder Compute (@ $0.66/hr): $66

TensorDock Spot (@ $0.67/hr): $67

Lambda / Hyperstack / DataCrunch: $112–$129

AWS/Azure/GCP: $400+

A single A100 VM on a budget platform can cost under $100/month vs $400+ on hyperscalers. Reserved pricing lowers rates further with long-term commitment.

Choosing A100: Value Checklist

Workload Type: Training & inference can leverage MIG—common in A100.
Continuous or Burst Use? Spot/preemptible rates work best for batch training.
Hardware Access Needed? On-prem PCIe or SXM is capex-intensive.
Compliance or Data Residency? DIY GPU clusters vs cloud rental.
Support and SLAs: Hyperscalers offer enterprise-grade support; smaller providers vary.

In Conclusion: A100 Stands Strong in 2025

NVIDIA’s A100 remains a gold standard for AI workloads—in both capability and value. Today, you can get cloud A100 access—40GB version—for under $1/hr, with Thunder Compute offering the best rates (~$0.66/hr). On-prem options range from $9,500–$14,000, balancing performance and upfront investment

Comparatively, hyperscalers are significantly more expensive. If your workload allows flexibility, smaller GPU cloud providers are the smart, cost-effective choice. For heavier enterprise needs, consider reserved pricing or hybrid deployments.

Whether you’re running a single A100 for research or building out an AI inference farm—understanding these NVIDIA A100 price dynamics ensures you get the performance you need at the right cost.