Gigabyte to Block

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.

Modern hard drives (2011+) and SSDs use 4,096-byte (4 KiB) physical sectors — known as "Advanced Format" or AF. Legacy drives used 512-byte sectors. Filesystems (NTFS, ext4, APFS) typically use 4 KiB logical block sizes to match physical sectors, which avoids the performance penalty of misaligned writes. Enterprise SSDs may use larger block sizes (16 KiB or more) for better parallelism.

Cloud block storage services (AWS EBS, Azure Managed Disks, GCP Persistent Disk) use I/O block sizes typically of 4 KiB or 16 KiB. Performance is measured in IOPS (I/O operations per second) and throughput (MB/s) — both depend on block size. A throughput-optimized workload (sequential video) benefits from large blocks; an IOPS-optimized workload (database random reads) uses small blocks.

Filesystems allocate disk space in whole blocks. On a system with 4 KiB blocks, every file — no matter how small — occupies at least 4,096 bytes. A directory of 10,000 small configuration files (each 100 bytes of content) uses 40 MB of disk space (10,000 × 4,096 bytes) rather than 1 MB (10,000 × 100 bytes). This is called "block slack" or "internal fragmentation".

Disk blocks (filesystem blocks) are typically 512 bytes to 4 KiB. Database blocks (database pages) are the unit of I/O for a database engine — typically 8 KiB (PostgreSQL, SQL Server), 16 KiB (MySQL InnoDB), or 32 KiB (Oracle, configurable). Database blocks usually align to multiples of disk blocks for efficiency. Reading one database page may involve reading 2–8 disk blocks.

RAID stripe size (or chunk size) is the amount of data written to each drive before moving to the next drive in the array — typically 64 KiB to 512 KiB. It should be set to match your workload: sequential large-file workloads benefit from larger stripe sizes; random small-block workloads benefit from stripe sizes closer to the filesystem block size. Mismatched stripe and block sizes cause write amplification and reduce RAID performance.