When did the A100 come out?
The Nvidia A100 was unveiled in May 2020 and began shipping later that year. This article traces the release timeline, key milestones, and what the A100 delivered for AI and HPC workloads.
Release timeline and key milestones
Below is a concise timeline of when NVIDIA introduced the A100 and when it became available to customers and cloud providers.
- May 14, 2020 — NVIDIA announces the A100 Tensor Core GPU at the GTC 2020 keynote, introducing the Ampere architecture and the GA100 processor that powers the A100 family.
- Mid to late 2020 — The A100 begins shipping to select customers, with 40 GB memory configurations available in both PCIe and SXM4 form factors; early cloud offerings begin to appear.
- 2021 — NVIDIA expands the A100 family with higher-memory options (notably an 80 GB variant) to support larger models and datasets in enterprise AI, HPC, and data analytics environments.
These milestones show the product’s initial introduction, early shipment, and subsequent expansion of memory configurations to support larger workloads.
Variants, memory configurations, and deployment
In its initial launch, the A100 was offered primarily in 40 GB memory configurations across PCIe and SXM4 platforms. A higher-memory variant—80 GB—was introduced later to address demanding training and inference workloads that benefit from larger GPU memory pools. The A100 was designed to accelerate AI training, inference, scientific computing, and data analytics across on-premises data centers and cloud platforms.
What the A100 enabled for users
The A100 brought a new level of performance to AI workstreams, enabling faster model training, more efficient inference at scale, and improved performance for data-heavy workloads in HPC and analytics. Its Tensor Core capabilities and architectural improvements over prior generations helped organizations push deeper into large-scale deep learning and scientific computing tasks.
Context and broader impact
The A100 marked a major step for NVIDIA’s data-center strategy, positioning Ampere as the backbone of AI infrastructure across hyperscalers, research institutions, and enterprise data centers. Its release coincided with growing demand for accelerated computing resources capable of handling increasingly complex models and datasets.
Summary
Launched in May 2020, the NVIDIA A100 was introduced at GTC 2020 and began shipping later that year. The product evolved from an initial 40 GB memory configuration to include higher-memory options such as 80 GB, expanding its suitability for large-scale AI training and inference, as well as HPC workloads. The A100’s release helped accelerate AI and data-centric workloads across cloud and on-premises environments, establishing a new benchmark for tensor-core performance in data centers.
When was the A100 GPU released?
The initial A100 GPU was released on May 14, 2020, by NVIDIA. This was followed by a 40 GB model in a DGX server and later a 80 GB version in June 2021.
- Initial release: May 14, 2020, based on the Ampere architecture.
- Initial package: It was first included in the 3rd-generation DGX A100 server.
- 80 GB model: An 80 GB version was released on June 28, 2021.
Is rtx 4090 faster than A100?
For instance, the A100's memory clock is much lower than the RTX 4090's on paper (roughly 3 Gbps vs. 21 Gbps). However, the A100 uses HBM2e memory with a much wider 5,120-bit interface. This design allows it to deliver around 2 TB/s of bandwidth – double the RTX 4090 – despite the lower frequency.
How much does 1 A100 GPU cost?
A100 pricing from Nvidia
A100 40GB PCIe: around $10,000–12,000. A100 80GB PCIe or SXM: around $15,000–17,000.
Is the Nvidia A100 end of life?
The NVIDIA A100 GPU is end-of-life (EOL), with NVIDIA discontinuing production in early 2024. While the hardware is no longer being manufactured, the CUDA software ecosystem continues to support it, and it can still be suitable for development or testing environments. For mission-critical workloads, organizations are encouraged to look at newer hardware like the NVIDIA H100, H200, or Blackwell platform.
Implications of the EOL status
- Availability: Production has ceased, so availability is limited to remaining stock or refurbished units.
- Technical support: While there is still software support, technical support or replacement options for failed hardware may become difficult to find.
- Workload suitability: The A100 is still viable for less demanding tasks like development or testing, but it should be avoided for mission-critical production systems that require 24/7 uptime.
- Cost-effectiveness: The EOL status can make older GPUs more affordable, potentially making them a cost-effective option for certain use cases, notes Communications Today.
Recommended next steps
- For new deployments: Consider upgrading to newer generations like the H100, H200, or the new Blackwell platform, as explained by AMAX Engineering and Exxact Corp..
- For existing deployments: Continue using A100s as long as they meet your needs, but plan for a future upgrade and be aware of potential limitations in hardware replacement, say Communications Today.
- For development: Existing A100s are still excellent tools for development and testing, according to Communications Today.
