Nvidia A100 80 Gb

Updated October 6, 2026

Overview

Product sourcing insights & recommendations

18 来源

In 2026, the NVIDIA A100 80GB has transitioned from being the peak industry standard to a "value workhorse" for AI compute. As the market shifts toward Hopper (H100/H200) and Blackwell (B200) architectures, the A100 remains highly relevant for mid-sized model training and stable inference due to its significant VRAM and lower cost of entry. Gmicloud Siliconanalysts

Market Trends & Insights

* Strategic Positioning: The A100 is increasingly favored by startups and researchers for mid-tier AI workloads (13B–34B parameter models). While it lacks the native FP8 support of the H100, its 80GB HBM2e memory still provides a crucial baseline for large-scale data processing that consumer hardware cannot match. Gmicloud

* Secondary Market Liquidity: A high volume of used A100 stock is entering the market as hyperscalers upgrade to newer clusters. This has stabilized pricing but also accelerated depreciation, with units retaining roughly 30–50% of their original MSRP. Hashrateindex Gpunex

* Rental Demand: On-demand cloud pricing is highly competitive, with "Neoclouds" offering rates as low as $1.09/hr, significantly cheaper than the $3.67/hr median found at Tier-1 hyperscalers like AWS or Azure. Thundercompute Jarvislabs

Procurement & Pricing Data (2026)

The market shows a wide range of pricing depending on the form factor (PCIe vs. SXM4) and unit condition:

Channel	Estimated Price (USD)	Notes
B2B Wholesale	$9,180 – $11,900	Competitive pricing for bulk/OEM customized versions. Alibaba
Individual Units	$12,000 – $18,000	Stabilized used market pricing for PCIe/SXM4 cards. Gpunex
Cloud Rental	$0.80 – $5.07/hr	Vast.ai (low-end) vs. Enterprise Hyperscalers (high-end). Thundercompute Silicondata

Key Performance Comparison

* vs. H100: The H100 delivers approximately 4x the performance in specific training tasks and features 67% higher memory bandwidth (3.35 TB/s vs 2.0 TB/s), making the A100 a "false economy" for large-scale FP8-heavy tasks. Gmicloud Acecloud

* vs. A30: The A100 offers nearly 3.3x the memory capacity (80GB vs 24GB), making it the entry-level choice for Large Language Model (LLM) fine-tuning where VRAM is the primary bottleneck. Getdeploying Openmetal

I have compiled a list of current B2B supplier listings for the NVIDIA A100 80GB, including pricing and minimum order quantities, in the deliverable below.

The A100 is now a "value workhorse" in 2026. You can continue with: