Live data — A100 pricing pulled from database in real time

The NVIDIA A100 Tensor Core GPU dominated AI infrastructure from 2020 through 2024 — and in 2026 it is finally reaching its lowest prices ever. Three forces collided to create the current $0.42–$1.74/hr floor: Blackwell (B200, GB200) pulling enterprise demand upmarket, hyperscalers retiring A100 clusters in favor of newer architectures, and community GPU networks aggregating spare A100 capacity at near-commodity rates. The result is an 8–11× price gap between the cheapest A100 on the market and AWS's p4d.24xlarge instances — for identical NVIDIA silicon. This page tracks every live A100 cloud rental available in 2026, pulling prices directly from our database across 15+ providers. Whether you are running Mistral 7B inference, fine-tuning Llama 3 8B, or batch-processing embeddings overnight, the A100 at 2026 prices is the best cost-per-output available for every workload that fits in 80GB of VRAM. Use the live table below or the GPU Cost Calculator to find the exact provider for your workload.

How We Track A100 Prices

GridStackHub pulls A100 pricing from three sources: direct provider API calls, verified pricing pages, and crowdsourced spot market data. Prices are updated daily — the live table above reflects our most recent scrape. VERIFIED badges mean we confirmed the price via live API; ESTIMATE means we sourced from a public pricing page and recommend verifying before committing. All prices are on-demand unless labeled SPOT. See our full methodology or browse the GPU Cost Calculator for cost projections across 50+ configurations.

$0.42/hr

Cheapest A100 80GB available today — 89% cheaper than AWS p4d equivalent ($3.67–$4.84/hr). Same NVIDIA A100 silicon, different supply chain. The gap has never been wider.

A100 Cloud Pricing — Live Table (April 2026)

GridStackHub tracks A100 pricing across 15+ cloud providers daily. The table below is pulled live from our database — sorted cheapest per GPU per hour. Both A100 80GB and A100 40GB records are shown where available.

# Provider GPU Per GPU/hr Type GPUs Notes
Loading live A100 pricing…

The A100 price floor is $0.42/hr and falling. Community GPU networks like Salad Cloud aggregate underutilized A100 capacity from data centers worldwide. Availability varies — for production workloads requiring SLA guarantees, $0.78–$1.50/hr on-demand options are more reliable. Use the GPU Cost Calculator to model your actual monthly spend.

Compare Across GPU Generations

The A100 sits at the intersection of three GPU tiers — older budget options below and newer flagship hardware above. Here is how to navigate them:

Next Step What It Covers Key Price Point
NVIDIA B200 (Blackwell) 2.3× faster than H200, 192GB HBM3e — from $5.29/hr on Lambda $5.29/hr
NVIDIA H200 (Hopper refresh) 141GB HBM3e — from $2.99/hr. Best-in-class inference for 70B+ models $2.99/hr
AMD MI300X (192GB HBM3) 192GB — eliminates tensor parallelism for 70B+ models. $1.85/hr $1.85/hr
NVIDIA L4 (Cost-optimized) Inference-optimized, 48GB. Best cost-per-token for smaller models $0.60/hr

For a full comparison across 32+ providers and 50+ GPU configurations, use the GPU Cost Calculator.

Why A100 Is at Historic Lows in 2026

A100 prices have never been cheaper. Three converging forces drove the 2026 price floor:

  • Blackwell displacement. NVIDIA's B200 and GB200 NVL72 racks shipped at scale in Q1 2026, pulling enterprise demand away from A100 and H100. Teams that need frontier performance moved up. Teams that need cost efficiency stayed on A100 — and the price gap widened to match.
  • Hyperscaler inventory rotation. Meta, Microsoft, and Google began retiring A100 clusters in favor of B200 and their own custom silicon (Trainium 3, TPU v6). That used A100 supply flowed into the secondary market — dramatically expanding available capacity.
  • Community GPU network maturity. Salad Cloud, Vast.ai, and similar platforms aggregated A100 instances from commercial data centers and research institutions. What was once $2–$3/hr on AWS can now be sourced from the same-generation silicon at $0.42–$0.78/hr through these networks.

The result: Salad Cloud at $0.42/hr, Thunder Compute at $0.78/hr, Vast.ai starting at $0.80/hr — versus AWS p4d.24xlarge at $3.67–$4.84/hr per A100. That is an 8–11× price gap for identical A100 silicon.

Price window note. A100 pricing at $0.42/hr is an artifact of supply temporarily exceeding demand. As older A100 inventory retires and enterprise demand normalizes around H100/B200, the floor will likely move back toward $0.75–$1.00/hr by 2027. If you have long-horizon A100 workloads, now is the time to lock in reserved pricing.

A100 80GB vs A100 40GB: Full Comparison

Two A100 variants exist. Understanding the difference prevents costly mistakes when provisioning at scale:

Spec A100 80GB SXM4 A100 40GB PCIe Winner
GPU Memory 80 GB HBM2e 40 GB HBM2 80GB +2×
Memory Bandwidth 2,000 GB/s 1,555 GB/s 80GB +29%
TF32 Throughput 312 TFLOPS 312 TFLOPS Tied
BF16/FP16 312 TFLOPS (sparse) 312 TFLOPS (sparse) Tied
NVLink bandwidth 600 GB/s 400 GB/s 80GB +50%
Max model at BF16 ~34B params ~16B params 80GB +2×
Max model at INT4 ~160B params ~80B params 80GB +2×
Typical cloud price $0.42–$3.67/hr $0.125–$1.79/hr 40GB (cheaper)
Cost per GB VRAM $0.0053/GB (at $0.42) $0.0031/GB (at $0.125) 40GB (at floor)

Which variant to choose

A100 80GB is the right choice for most teams:

  • Running 7B–34B models in BF16 precision (single GPU inference)
  • Fine-tuning 13B–34B models with full parameter updates
  • High-throughput batched inference needing large KV-cache allocation
  • Multi-GPU tensor parallelism jobs where NVLink bandwidth matters

A100 40GB makes sense when:

  • Your model and batch size are confirmed to fit in 40GB
  • You need maximum GPU density (e.g., 8× 40GB vs 4× 80GB per node)
  • Running smaller models (7B at BF16, 13B at INT8) at maximum throughput per dollar
  • Budget-constrained and Vultr's $0.125/hr 40GB is available for your workload

When A100 Beats H100 in 2026

The H100 is not always the best choice. For a significant class of workloads, the A100 at 2026 prices is strictly better on cost per output:

✓ LLM Inference (7B–34B)

vLLM and TGI run 7B–34B models efficiently on A100 80GB. At $0.78/hr vs H100's $1.74/hr minimum, the A100 saves 55% on inference costs without meaningful latency difference for most serving patterns.

✓ LoRA / QLoRA Fine-tuning

LoRA fine-tuning for 7B–13B models on A100 80GB is near-identical wall-clock time vs H100 at 1/3 the cost. For non-latency-sensitive training jobs, this is the best $/output available in 2026.

✓ Stable Diffusion / Image Gen

A100's 80GB VRAM enables large batch sizes for SDXL, Flux, and Stable Diffusion 3. With 2× the VRAM of an H100 at half the price, throughput per dollar is significantly higher.

✓ Batch Processing Jobs

Any workload that can run overnight (embeddings, document processing, batch scoring) benefits from A100's $0.42–$0.78/hr pricing. A 12-hour batch job costs $5–$9 on A100 vs $17–$58 on AWS H100.

⚡ H100 Better: Large-Scale Training

H100's FP8 tensor cores (3,958 TFLOPS vs A100's 312 TFLOPS TF32) provide genuine speedup for continuous pretraining at scale. The TCO math favors H100 when training > 10B tokens/week.

⚡ H100 Better: 70B+ Inference

For low-latency inference on 70B+ models (Llama 3 70B, Mixtral 8x22B), H100's higher memory bandwidth and NVLink throughput reduce TTFT and inter-token latency meaningfully at scale.

Rule of thumb: If your workload fits in 80GB and you're not constrained by training throughput or P99 inference latency, run it on A100 in 2026. The 3–10× cost difference compounds dramatically at scale.

Frequently Asked Questions

What is the cheapest A100 GPU cloud provider in 2026?
As of April 2026, the cheapest A100 GPU cloud pricing is Salad Cloud at approximately $0.42/hr for an A100 80GB — though this is community/spot pricing with variable availability. For reliable on-demand access, Thunder Compute offers A100s from $0.78/hr. The price gap versus hyperscalers is dramatic: AWS p4d.24xlarge costs $3.67–$4.84/hr per A100. GridStackHub tracks live pricing from 15+ providers daily — use the live table above or the GPU Cost Calculator for the latest numbers.
Why is A100 pricing at historic lows in 2026?
A100 GPU cloud prices hit historic lows in 2026 for three reasons. First, NVIDIA's Blackwell (B200, B300) and Hopper (H100, H200) architectures have pulled enterprise demand upmarket — teams requiring frontier performance have moved on. Second, a wave of A100 supply entered the market as hyperscalers rotate inventory toward newer GPUs: Meta, Microsoft, and Google retiring older A100 clusters created secondary market overflow. Third, community GPU networks like Salad and Vast.ai have aggregated consumer-grade A100 supply at near-commodity pricing. For cost-sensitive inference and fine-tuning workloads, 2026 is arguably the best time to run on A100.
A100 80GB vs 40GB: which should I use?
The A100 80GB is the clear choice for most AI workloads in 2026 due to its ability to run larger models in a single GPU. The 80GB variant fits 70B parameter models at INT4 or 34B models at BF16, while the 40GB tops out at ~30B INT4. The 80GB also has 2TB/s memory bandwidth versus 1.6TB/s on the 40GB — a 29% bandwidth advantage that matters for inference throughput. The 40GB A100 makes sense only if your model is confirmed to fit in 40GB and you need maximum GPU density — for example, 8× 40GB nodes for smaller model serving.
Is A100 or H100 better for fine-tuning in 2026?
For fine-tuning 7B–34B parameter models with LoRA or QLoRA, the A100 80GB at $0.78–$1.50/hr delivers significantly better cost efficiency than the H100 at $1.74–$4.84/hr. The H100's FP8 training advantage (approximately 2× raw throughput) is mostly irrelevant for small-to-mid scale fine-tuning jobs where GPU memory and wall-clock cost matter more than peak FLOPS. A100 makes sense for fine-tuning budgets under $500/month. H100 becomes cost-effective when running continuous training jobs at scale where training time directly reduces iteration cycle time.
How do community GPU networks like Salad Cloud compare to AWS for A100?
Community GPU networks aggregate spare A100 capacity from data centers, research labs, and commercial operators — passing the cost savings directly to users. The A100 silicon is identical to what AWS runs. The differences are: (1) Availability — community networks have less predictable supply; AWS guarantees on-demand capacity. (2) SLA — AWS provides 99.99% SLA and enterprise support; Salad/Vast.ai offer best-effort availability. (3) Networking — AWS has faster intra-region networking for multi-GPU jobs; community networks vary. For batch workloads, experimentation, and development, community A100 at $0.42–$0.78/hr is excellent. For production serving with SLA requirements, budget $0.78–$1.50/hr for a reputable mid-tier provider.

Track A100 Prices and Get Alerts

A100 pricing is moving fast in 2026. As Blackwell supply increases and older A100 inventory retires, prices will shift. Get ahead of it:

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