---
description: Meta backs QLC SSDs for data centers, highlighting cost, capacity &amp; power efficiency. Are enterprises ready to adopt QLC at scale?
title: Meta Makes the Case for QLC SSDs in the Data Center—Are Enterprises Finally Ready?
image: https://www.storagereview.com/wp-content/uploads/2025/03/Meta-QLC-Server2.jpeg
---

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[Home](https://www.storagereview.com/) » [News](https://www.storagereview.com/news) » Meta Makes the Case for QLC SSDs in the Data Center—Are Enterprises Finally Ready?

# Meta Makes the Case for QLC SSDs in the Data Center—Are Enterprises Finally Ready?

by Brian Beeler on March 5, 2025

[Enterprise](https://www.storagereview.com/enterprise)

Meta has dropped [a new blog post](https://engineering.fb.com/2025/03/04/data-center-engineering/a-case-for-qlc-ssds-in-the-data-center/) outlining why QLC SSDs are primed for widespread data center adoption. The social media giant is pushing the conversation forward on replacing aging HDDs and even some TLC-based SSDs with high-capacity QLC NAND. The argument? Higher density, better power efficiency, and lower cost per terabyte than TLC SSDs. These are all benefits we’ve seen in enterprise storage, with companies like Solidigm, Pure Storage, Dell, and many others already making moves in this space.

![meta storage server - QLC SSDs for data centers](https://www.storagereview.com/wp-content/uploads/2025/03/Meta-QLC-Server2-1024x497.jpeg)

Meta E1.S Storage Server

### HDDs Are Struggling to Keep Up

For years, HDDs have been the backbone of cold and archival storage, offering a (relatively) cheap way to store massive amounts of data. However, bandwidth per terabyte (BW/TB) drops as data centers scale, making HDDs a bottleneck. Meta highlights how this forces companies to overprovision or shift hot data to TLC SSDs, which are significantly more expensive per TB.

QLC SSDs aim to bridge that gap. Storing four bits per cell, QLC drives cram in more data per NAND package, delivering higher density and improved power efficiency at a much lower price than TLC. Meta believes QLC SSDs offer the right balance between cost, capacity, and performance, so they’re integrating them into their infrastructure. We’ve long been writing about the benefits of QLC SSDs as we attack massive computation problems like [solving Pi to a world record 202 trillion digits](https://www.storagereview.com/news/storagereview-lab-breaks-pi-calculation-world-record-with-over-202-trillion-digits).

### Pure Storage, Solidigm, Dell, and NetApp Are Already On Board

Meta isn’t alone in this push. Pure Storage has been shipping QLC SSD-based arrays for years, and their DirectFlash Module (DFM) architecture has proven that QLC can handle mainstream workloads. Over at Solidigm, the company has made a strong case for QLC SSDs in AI, read-intensive, and even some mixed workloads with [drives that now top 122TB](https://www.storagereview.com/review/nvidia-jetson-orin-nano-super-powering-deepseek-r1-70b-inference-at-the-edge) in capacity.  [Solidigm’s research](https://estimator.solidigm.com/ssdtco/index.htm?_gl=1*4i6tgd*_gcl_au*MTY2Njk5OTk2MS4xNzQxMTkwODY0) shows that swapping HDDs for QLC SSDs can shrink rack space by 3x, cut energy costs by 20%, and lower total storage costs by 31%.

![NVIDIA Jetson Orin Nano Super board]()

Dell has also embraced QLC, with PowerScale storage systems leveraging the tech to improve performance and scalability. Many other enterprise storage providers, like NetApp, have followed suit, including QLC in some of their platforms. These implementations show that QLC isn’t just about cold storage—it’s becoming a real contender for primary workloads.

### Can QLC SSDs Handle AI? Meta Thinks So

One of the biggest questions around QLC has been whether it can withstand AI and ML workloads. Traditionally, AI training workloads have favored high-performance TLC or even ultra-fast SCM, but Meta makes a compelling case for QLC in AI inference and large-scale model storage.

AI inference servers rely on large datasets that must be frequently updated but not necessarily rewritten at high frequency. That makes QLC an ideal fit. [TrendForce](https://www.trendforce.com/news/2024/10/22/news-qlc-ssd-the-game-changer-for-nand-flash/) research backs this up, noting that QLC SSDs are well-suited for read-heavy AI workloads, content delivery networks, and machine learning applications.

Our testing at StorageReview has reinforced QLC’s role in AI storage. A recent deep dive explored how Solidigm’s D5-P5336 QLC SSD performs in [checkpointing workloads for AI model training](https://www.storagereview.com/review/scaling-ai-checkpoints-the-impact-of-high-capacity-ssds-on-model-training). These tests showed that while TLC SSDs still lead in write-heavy environments, QLC SSDs hold their own regarding capacity, efficiency, and read performance—making them a strong option for AI pipelines.

![]()

Meta appears to be increasing its collaboration with Pure Storage, which is driven by a need for scalable, power-efficient, and high-density QLC SSD storage in its data centers. Meta sees Pure’s approach as a more effective way to scale QLC SSD adoption, mainly because DFM technology enables storage capacities of up to 600TB with current NAND packages. Notably, Meta does not see E1.S and E3 form factors as scalable options for QLC SSDs, citing challenges in achieving the required density and efficiency for their large-scale deployments.

### QLC SSDs Are Ready—Are Enterprises?

Meta’s backing of QLC SSDs is a significant milestone in the shift away from HDDs and TLC NAND in data centers. We’ve already seen Pure Storage, Solidigm, Dell, and NetApp make substantial bets on QLC, and as AI continues to drive storage demand, more enterprises are likely to follow. The real question now is how quickly IT leaders will make the jump. If you’re still running traditional HDD-based archives or hybrid storage solutions, it’s time to consider QLC as a viable, cost-effective alternative.

For a deeper dive, check out Meta’s full post [here](https://engineering.fb.com/2025/03/04/data-center-engineering/a-case-for-qlc-ssds-in-the-data-center/) and our past coverage of [QLC storage tech](https://www.storagereview.com/?s=enterprise+qlc).

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### Brian Beeler

Brian is located in Cincinnati, Ohio and is the chief analyst and President of StorageReview.com.

Previous post: [PEAK:AIO Expands AI Infrastructure with 2U 1.5PB AI Data Server With 120GB/sec Performance](https://www.storagereview.com/news/peakaio-expands-ai-infrastructure-with-2u-1-5pb-ai-data-server-with-120gb-sec-performance)

Next post: [Utah’s $2 Billion AI Data Center: A Major Bet on AI Infrastructure](https://www.storagereview.com/news/utahs-2-billion-ai-data-center-a-major-bet-on-ai-infrastructure)

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