Gigabyte to Tebibyte

Hard drive manufacturers measure 1 TB as 1,000,000,000,000 bytes (decimal). Windows displays storage in gibibytes (binary) but historically labelled them as "GB" — so 1,000,000,000,000 bytes ÷ 1,073,741,824 ≈ 931 GiB, which Windows displayed as "931 GB". macOS (since 10.6) correctly reports the same drive as "1 TB" using decimal GB. The drive is not lying; the OS was using a binary unit with a decimal label.

8 GB RAM is the current minimum for gaming; 16 GB is the recommended standard for most modern games at 1080p and 1440p; 32 GB benefits heavily multitasking systems or games with large open worlds. Memory-intensive tasks like video editing, 3D rendering, and running large language models locally typically require 32–64 GB or more.

A 4K movie in H.264 or H.265 encoding is typically 50–100 GB on Blu-ray; streaming services compress aggressively to 15–25 GB for 4K HDR content. Netflix's 4K streams average about 7 GB per hour; the downloaded version via the Netflix app for offline viewing is roughly 3–6 GB per hour at high quality settings.

1 GB of mobile data supports roughly: 2–3 hours of music streaming, 1 hour of HD video streaming, 2–3 hours of web browsing, or 30–60 minutes of video calling. Social media apps with autoplay video are heavy consumers — TikTok and Instagram Reels can use 300–600 MB per hour of active use.

AI model sizes vary enormously. GPT-2 (2019) is about 1.5 GB; Llama 2 7B is roughly 13 GB in float16 precision; Llama 2 70B is about 130 GB. GPT-4-class models are estimated at 500+ GB. Quantised (compressed) versions are smaller: a 4-bit quantised 7B model fits in about 4 GB, runnable on a modern laptop. Training requires far more — the training dataset, gradients, and optimizer states for a 70B model can occupy 1–2 TB of GPU memory across a cluster. The trend toward larger models is driving consumer GPU memory from 8 GB to 16–24 GB as a baseline for local AI inference.

TB (terabyte) = 10¹² bytes = 1,000,000,000,000 bytes (SI decimal). TiB (tebibyte) = 2⁴⁰ bytes = 1,099,511,627,776 bytes (IEC binary). TiB is 9.95% larger. The practical consequence: a 1 TB hard drive (decimal) holds 0.9095 TiB. This 10% gap is the primary reason drive capacity appears lower in the OS than on the box.

ZFS and Btrfs are copy-on-write filesystems designed for TiB-scale pools with built-in features that traditional filesystems lack. ZFS supports inline deduplication — a 10 TiB pool with 40% duplicate data might show 6 TiB of logical usage but only consume 3.6 TiB physically. Btrfs offers transparent compression (zstd), where a 4 TiB dataset of compressible log files might occupy only 1–2 TiB on disk. Both support snapshots that initially consume zero extra space, growing only as data diverges. These features make "used space in TiB" surprisingly complex to report accurately.

Yes. Linux tools (df -h, lsblk) display storage in IEC binary units: KiB, MiB, GiB, TiB. df -h output showing "1.8T" for a 2 TB drive is reporting 1.8 TiB. Modern Linux distributions correctly label these as TiB in technical contexts. This is one of the areas where Linux is more technically precise than Windows or consumer storage labels.

RAID arrays lose capacity to redundancy: RAID 1 mirrors two drives (50% efficiency); RAID 5 loses one drive worth of capacity; RAID 6 loses two drives. A 4-drive RAID 5 array of 2 TB drives has 3 × 2 TB = 6 TB raw usable (decimal), ≈ 5.46 TiB, minus filesystem overhead. Enterprise storage also reserves space for spares, snapshots, and wear levelling, further reducing usable TiB.

No. A tebibyte (TiB) = 2⁴⁰ bytes = 1,099,511,627,776 bytes — about 1.1 trillion bytes. Exactly one trillion bytes = 10¹² bytes = 1 terabyte (TB, decimal). The tebibyte is approximately 10% larger than a trillion bytes. "Terabyte" is often casually used to mean "1 trillion bytes"; "tebibyte" is the precise binary equivalent at 1,024 gibibytes.