Stop underestimating how much SSD storage your PC actually needs


A 1TB drive will still work in a modern PC, but it won’t leave you much room to spare. Once that drive starts to fill up, you’re not only fighting for space, you’re actually making the SSD work harder. That is why you need more than 1TB of storage for a boot drive, especially on Windows.

One terabyte is barely enough

Storage demands aren’t slowing down

Your boot drive has to hold more data than just the OS. It typically stores browser caches, game launchers, Windows updates, and all of your documents, pictures, and downloads, unless you manually move them.

Games are especially demanding. A few modern AAA titles can easily eat up hundreds of gigabytes. Virtual machines, local AI models, UHD video, and RAW photos can also use up a ton of space.

That problem isn’t getting better either—storage needs only ever go up. Games are getting larger, Windows certainly isn’t getting any leaner, and every new generation of phones brings larger photos and videos. Even a software update can use up gigabytes of temporary space just to unpack and replace files.



















Quiz
8 Questions · Test Your Knowledge

SSDs, NAND memory, and interfaces
Trivia challenge

From flash cells to PCIe lanes — see how much you really know about modern solid-state storage.

NANDInterfacesHardwarePerformanceStandards

Which type of NAND flash stores exactly one bit of data per cell?

Correct! SLC stands for Single-Level Cell, meaning each cell holds just one bit — either a 0 or a 1. This makes SLC the fastest and most durable NAND type, but also the most expensive per gigabyte, so it’s mainly found in enterprise and industrial storage.

Not quite — the answer is SLC, which stands for Single-Level Cell. MLC stores 2 bits, TLC stores 3, and QLC stores 4 bits per cell. The more bits per cell, the cheaper but slower and less durable the NAND becomes.

What does NVMe stand for in the context of SSDs?

Correct! NVMe stands for Non-Volatile Memory Express, a communication protocol designed specifically for flash-based storage. Unlike AHCI, which was built for spinning hard drives, NVMe takes full advantage of PCIe’s parallel lanes to deliver dramatically lower latency and higher throughput.

Not quite — NVMe stands for Non-Volatile Memory Express. It’s a host controller interface protocol designed to replace the older AHCI standard, which was originally built with spinning hard disk drives in mind rather than fast flash storage.

Which physical form factor is most commonly used for NVMe SSDs in modern laptops and desktops?

Correct! The M.2 form factor has become the dominant standard for NVMe SSDs in consumer devices. It’s a compact, card-style connector that fits directly onto the motherboard, eliminating the need for data and power cables and saving space inside the chassis.

The correct answer is M.2. While 2.5-inch SATA and mSATA were common in older systems, M.2 has taken over as the go-to slot for NVMe drives. U.2 is also used for NVMe but is mostly found in enterprise servers rather than consumer hardware.

Approximately how fast can a high-end PCIe 4.0 NVMe SSD read data sequentially?

Correct! Top-tier PCIe 4.0 NVMe SSDs can achieve sequential read speeds of around 7,000 MB/s. This is a massive leap over SATA SSDs, which are capped near 550 MB/s due to interface bandwidth limitations, and even outpaces many PCIe 3.0 drives significantly.

Not quite — the answer is approximately 7,000 MB/s. Around 550 MB/s is the ceiling for SATA-based SSDs, while 1,200 MB/s is typical for older PCIe 3.0 drives. 20,000 MB/s exceeds even PCIe 5.0 NVMe drives available at time of writing.

What does 3D NAND refer to in modern SSD manufacturing?

Correct! 3D NAND, sometimes called V-NAND by Samsung, stacks memory cells vertically in dozens or even hundreds of layers rather than spreading them flat across a wafer. This dramatically increases storage density without shrinking individual cell sizes, which also helps preserve endurance and reliability.

The correct answer is that 3D NAND stacks memory cells vertically in multiple layers. Planar (2D) NAND arranges cells flat on a single layer, but manufacturers hit physical scaling limits, so the industry moved to vertical stacking to keep increasing capacity without sacrificing cell quality.

Which interface protocol were most SATA SSDs designed to use before NVMe became mainstream?

Correct! AHCI (Advanced Host Controller Interface) is the protocol that SATA SSDs communicate over. It was originally designed for mechanical hard drives and supports a single command queue of 32 commands — a major bottleneck compared to NVMe, which supports 65,535 queues each holding 65,535 commands.

The answer is AHCI, which stands for Advanced Host Controller Interface. SCSI and IDE are much older standards largely retired from consumer use, while NVMe is the newer protocol used by PCIe-based drives. AHCI’s single command queue made it a poor fit for the parallelism flash storage can deliver.

Which NAND type offers the highest storage density per chip but typically has the lowest endurance?

Correct! QLC, or Quad-Level Cell NAND, packs four bits into every cell, giving it the highest density of common consumer NAND types. The trade-off is significantly reduced endurance — QLC cells wear out faster because of the precision needed to distinguish between 16 different voltage states per cell.

The answer is QLC (Quad-Level Cell). It stores 4 bits per cell, making it the densest and most affordable NAND type, but it also has the lowest P/E (program/erase) cycle endurance. SLC sits at the opposite end — fewest bits per cell but the longest lifespan.

Which PCIe generation, first adopted widely in consumer SSDs around 2020, doubled the bandwidth of its predecessor?

Correct! PCIe 4.0 arrived in consumer platforms around 2020, starting with AMD’s Ryzen 3000 series and X570 motherboards. It doubles the per-lane bandwidth compared to PCIe 3.0, pushing NVMe SSD sequential speeds from roughly 3,500 MB/s up to around 7,000 MB/s.

The correct answer is PCIe 4.0, which first appeared broadly in consumer hardware around 2020 with AMD’s Zen 2 platform. PCIe 3.0 was the previous mainstream standard, while PCIe 6.0 is a more recent enterprise-focused generation not yet common in everyday consumer motherboards.

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Additionally, you can’t actually use all of that 1 terabyte. Some of it gets used for formatting, and you need to leave a chunk empty for system updates and general SSD health. You aren’t really working with a full terabyte of usable space when you account for what you need to do to make a 1TB drive practically useful.

Moving to a 2TB drive makes many of those problems much more manageable. You can keep more of your game library installed and avoid turning storage management into a weekly chore. You don’t need to worry about freeing up space so Windows will update properly. As long as you exercise a little bit of restraint, 2TB will be a much better experience over 1TB.

Larger SSDs tend to be faster

Writing in parallel speeds things up

TerraMaster's F4 SSD NAS with four different NVMe SSDs installed. Credit: Patrick Campanale / How-To Geek

A lot of an SSD’s speed comes from parallelism, where the controller writes data to multiple locations on the drive simultaneously instead of writing one-by-one. The more NAND cells available, the more the controller can divide the workload up.

WD_BLACK 2TB SSD on a white background.

Storage capacity

2TB

Hardware Interface

PCIE x 4

Compatible Devices

Laptop, Motherboards

Brand

Western Digital

TBW

7300 MB/s

Dimensions

3.15″L x 0.87″W x 0.09″Th

The WD_Black 2TB SSD is great for gaming. It offers read speeds of up to 7,300 mb/s and features an optional heatsink. The drive includes the wd_black dashboard software for monitoring health and customizing RGB lighting on compatible models.


With the extra cells available to work with on a 2TB drive, the controller has more room to write in parallel, which is especially helpful for sustained workloads. You won’t notice your apps opening twice as fast, but there will usually be a difference when installing games or transferring large media libraries.

Bigger drives usually have more cache

Most of the cells in an SSD are found in triple-level (TLC) or quad-level (TLC) configurations, which, in practical terms, just means you can pack more storage cells into a smaller space.


A Samsung 860 EVO SSD.


Multi-Layer SSDs: What Are SLC, MLC, TLC, QLC, and PLC?

On the market for a solid-state drive but confused by all the abbreviations? We’ll help you sort out what things like SLC and TLC mean, and which one is right for you.

Unfortunately, that has a large drawback: they’re usually slower than single-level cells.

To improve the write speeds of SSDs, manufacturers usually force the SSD to treat a small part of its denser TLC or QLC memory as the much faster single-layer cell (SLC) configuration (usually called pseudo-SLC). When you need to write data quickly, it is first sent to the portion that is acting as SLC and then later sent to the slower, denser TLC or QLC storage.

When you have plenty of free space, your pseudo-SLC cache can be larger, so those writes stay fast for longer. If your drive is small or nearly full, that performance drops off much sooner. By choosing 2TB, you ensure you have enough cache to handle real-world without running into a performance wall.

Your SSD can write without waiting

Having extra free space also prevents the SSD from stuttering. When a drive has plenty of empty blocks, it can just write data to a cell and move on. If it’s near capacity, the controller has to spend time moving existing data around and erasing old blocks before it can save anything new.

That background cleanup process is normal, but writing is smoother when the drive isn’t cramped. A 2TB drive holding the same amount of data as a full 1TB drive has more room to write data without stopping to clear cells first, which means you’ll be spared annoying slowdowns during ordinary use.

Larger drives can write more data before they die

Wear-leveling is essential

An 8TB HGST hard drive with a 2TB WD_BLACK NVMe SSD sitting on top of it. Credit: Patrick Campanale / How-To Geek

Finally, there is the issue of longevity. Since SSDs wear out based on how much data is written to the NAND cells, the controller tries to spread that wear evenly across the entire drive, so one cell doesn’t get written to 10,000 times while another goes completely untouched.

It isn’t that a 1TB drive is fragile—modern drives are very reliable—but a larger drive will have a higher total write endurance, allowing you to use it longer.


Storage isn’t getting cheaper any time soon

When a drive costs nears $200 per terabyte, you need to get the most bang for your buck. Even though 1TB SSDs are less expensive, there are too many concessions you have to make, both in terms of performance and ease of use.

It’ll cost more up front, but you’re better off buying a 2TB (or larger) SSD once instead of two 1TB SSDs a few months apart when your first drive is completely filled up. There is usually a cost benefit there too—larger drives are usually less expensive per TB of storage than 1TB drives are. In the era of flash memory scarcity, those cost savings matter.



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In short: Accel has raised $5 billion in new capital, comprising a $4 billion Leaders Fund V and a $650 million sidecar, targeting 20-25 late-stage AI investments at an average cheque size of $200 million. The raise follows standout returns from its Anthropic stake (invested at $183B, now valued near $800B) and Cursor (backed at $9.9B, now reportedly around $50B), and lands in a Q1 2026 venture market that deployed a record $297 billion.

Accel, the venture capital firm behind early bets on Facebook, Slack, and more recently Anthropic and Cursor, has raised $5 billion in new capital aimed squarely at AI. The raise, reported by Bloomberg, comprises $4 billion for its fifth Leaders Fund and a $650 million sidecar vehicle, positioning the firm to write average cheques of around $200 million into late-stage AI companies globally.

The fund lands in a venture capital market that has lost any pretence of restraint. Q1 2026 saw $297 billion flow into startups worldwide, 2.5 times the total from Q4 2025 and the most venture funding ever recorded in a three-month period. Andreessen Horowitz has raised $15 billion. Thrive Capital has closed more than $10 billion. Founders Fund is finishing a $6 billion raise. Accel’s $5 billion is substantial but not exceptional in a market where the biggest funds are measured in the tens of billions.

The portfolio that made the pitch

What distinguishes Accel’s fundraise is the portfolio it can point to. The firm invested in Anthropic during its Series G at a $183 billion valuation. Anthropic has since closed a round at $380 billion and is now attracting offers at roughly $800 billion, meaning Accel’s stake has more than quadrupled in value in a matter of months. Anthropic’s annualised revenue has hit $30 billion, a trajectory that no company in history has matched.

The firm’s bet on Cursor has been similarly well-timed. Accel backed the AI code editor in June 2025 at a $9.9 billion valuation. By November, Cursor had raised again at $29.3 billion. By March 2026, the company was reportedly in discussions at a valuation of around $50 billion. For a developer tool that barely existed two years ago, the appreciation is extraordinary.

Accel’s broader AI portfolio extends beyond these two headline positions. The firm has backed Vercel, the frontend deployment platform; n8n, an AI-powered automation tool; Recraft, a professional design platform; and Code Metal, which builds AI development tools for hardware and defence applications. In March 2026, Accel launched an Atoms AI programme in partnership with Google’s AI Futures Fund, selecting five early-stage companies from what it described as a global applicant pool focused on “white space” opportunities in enterprise AI.

The Leaders Fund model

Accel’s Leaders Fund series is designed for later-stage investments, the kind of large cheques that growth-stage AI companies now require. With an average investment size of $200 million and a target of 20 to 25 deals from the new $4 billion fund, the strategy is concentrated: a small number of high-conviction bets on companies that have already demonstrated product-market fit and are scaling revenue.

This is a different game from traditional venture capital. At $200 million per cheque, Accel is competing less with seed and Series A firms and more with the mega-funds, sovereign wealth funds, and corporate investors that have flooded into late-stage AI. The firm’s argument is that its early-stage relationships and technical evaluation capabilities give it an edge in identifying which companies deserve capital at scale, and in securing allocations in rounds that are massively oversubscribed.

Founded in 1983 by Arthur Patterson and Jim Swartz, Accel built its reputation on what the founders called the “prepared mind” approach, a philosophy of deep sector research before investments materialise. The firm’s most famous prepared-mind bet was its 2005 investment of $12.7 million for 10% of Facebook, a stake worth $6.6 billion at the company’s IPO seven years later. The question now is whether Accel’s AI bets will produce returns of comparable magnitude.

What the market is pricing

The sheer volume of capital flowing into AI venture funds reflects a market consensus that artificial intelligence will be the dominant technology platform of the next decade. The numbers are difficult to overstate. OpenAI raised $120 billion in 2026. Anthropic has raised more than $50 billion. xAI closed $20 billion. Waymo secured $16 billion. These are not venture-scale numbers; they are infrastructure-scale capital deployments that would have been unthinkable outside of telecommunications or energy a decade ago.

For limited partners, the investors who commit capital to venture funds, the logic is straightforward: the returns from AI’s winners will be so large that even paying premium valuations will generate exceptional multiples. Accel’s Anthropic position, where a single investment has appreciated several times over in months, is exactly the kind of outcome that makes LPs willing to commit $5 billion to a single firm’s next fund.

The risk is equally visible. Venture capital is a cyclical business, and the current fundraising boom has the characteristics of a cycle peak: record fund sizes, compressed deployment timelines, and a concentration of capital in a single sector. The last time venture capital raised this aggressively, during the 2021 ZIRP era, many of those investments were marked down significantly within two years. AI’s commercial traction is far stronger than the crypto and fintech bets that defined that earlier cycle, but the valuations being paid today leave little margin for error.

The concentration question

Accel’s fund also highlights a structural shift in venture capital. The industry is bifurcating into a small number of mega-firms that can write cheques of $100 million or more and a long tail of smaller funds that compete for earlier-stage deals. The middle ground, the traditional Series B and C investors, is being squeezed by mega-funds moving downstream and by AI companies that skip traditional funding stages entirely, going from seed round to billion-dollar valuations in 18 months.

For a firm like Accel, which operates across offices in Palo Alto, San Francisco, London, and India, the $5 billion raise is a bet that it can maintain its position in the top tier as fund sizes inflate and competition for the best deals intensifies. Its portfolio of 1,199 companies, 107 unicorns, and 46 IPOs provides a track record. But in a market where Anthropic alone could generate returns that justify an entire fund, the temptation to concentrate bets on a handful of AI winners is strong, and the consequences of getting those bets wrong are correspondingly severe.

The broader picture is that AI venture capital has entered a phase where the funds themselves are becoming as large as the companies they once backed. Accel’s $5 billion raise would have made it one of the most valuable startups in Europe just a few years ago. Now it is table stakes for a firm that wants to participate meaningfully in the rounds that matter. Whether this represents rational capital allocation or the peak of a cycle that will eventually correct is the question that every LP writing a cheque today is, implicitly or explicitly, answering in the affirmative.



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