Google converts kg to lbs. But for color spaces, data formats, encoding schemes, and time zones — you need real converter tools. Here's the complete guide.
Type "5 kg to lbs" into Google and you'll get 11.0231 pounds in about 200 milliseconds. Impressive. Now try "convert this JSON to YAML." Or "decode this Base64 string." Or "what's #3B82F6 in HSL?" Or "what was Unix timestamp 1711152000 in Tokyo time?"
Google will stare at you blankly. Maybe it'll show you a Stack Overflow link from 2014. Maybe it'll hallucinate an answer via its AI overview. Either way, you're not getting what you need.
I've spent the better part of a decade working with converters — building them, using them, cursing at them when they silently truncate my input. And here's what I've learned: the world of unit conversion is vastly bigger than Google's built-in calculator, and most people are stuck using a fraction of what's available.
This is the guide I wish I'd had when I started. Every category of converter you'll ever need, when to use each one, and why having them all in one place changes everything.
Let's give credit where it's due. Google's built-in converter handles the basics beautifully:
For these everyday conversions, Google is fast and frictionless. I use it constantly. If someone asks me how many feet are in a kilometer, I'm not opening a dedicated tool — I'm typing it into my address bar.
But here's the thing: these represent maybe 5% of the conversions I actually do in a typical workweek. The other 95% fall into categories Google either handles poorly or doesn't handle at all.
Google can't convert between data formats. It can't decode encoded strings. It can't translate between color spaces with precision. It doesn't know what a Unix timestamp is. It can't convert between number bases beyond simple decimal-to-binary. It has no concept of typography units. It doesn't do image format conversion.
In other words, Google covers the conversions your grandma might need, and completely ignores the conversions that developers, designers, data engineers, and power users deal with every single day.
Let's go through every category.
Even in the "simple" world of physical unit conversion, there's more nuance than Google shows you.
Meters to feet, sure. But what about:
Google handles the common ones. A dedicated length converter handles all of them, lets you convert between multiple units simultaneously, and shows you the formula — which matters when you're putting this in a report or a codebase.
Kilograms to pounds is Google's bread and butter. But a proper mass converter also handles:
Celsius, Fahrenheit, Kelvin — Google's got this. But a good temperature converter also includes Rankine (used in some thermodynamic calculations) and shows the conversion formula, which is non-linear and easy to screw up by hand.
One thing Google actually does well here: if you type "350°F to C" it correctly gives you 176.667°C. But it won't tell you that this is a common oven temperature and that rounding to 175°C or 180°C is standard practice in metric recipes. Context matters, and dedicated tools can provide it.
Square meters to square feet, liters to gallons — straightforward. But a comprehensive area converter also handles acres, hectares, square rods (land surveying again), and barns (nuclear physics — the unit is literally called a barn, and it's 10⁻²⁸ square meters).
For volume, things get messy fast. US fluid ounces vs. imperial fluid ounces. US cups vs. metric cups vs. imperial cups. US gallons vs. imperial gallons. A good converter makes this explicit rather than ambiguous.
This one drives me absolutely insane, and it trips up even experienced developers.
Here's the problem: is a kilobyte 1,000 bytes or 1,024 bytes? The answer is... both, depending on who you ask and when.
In practice, almost nobody uses "KiB" in casual conversation. Your operating system might show file sizes in binary kilobytes while calling them "KB." Your hard drive manufacturer uses decimal kilobytes. Your RAM is measured in binary. Your network speed is in decimal.
This is why your "1 TB" hard drive shows up as ~931 GB in Windows. It's not fraud — it's two different definitions of "tera."
A proper data storage converter lets you toggle between decimal (SI) and binary (IEC) interpretations. It shows you both values. It handles everything from bits to yottabytes (and their binary equivalents: yobibytes). And it converts between bits and bytes, which matters for network throughput (measured in bits per second) vs. file sizes (measured in bytes).
Google can convert "1 TB to GB" but it won't tell you which definition it's using (it uses decimal, 1 TB = 1,000 GB), and it won't show you the binary equivalent (1 TiB = 1,024 GiB).
This is where Google completely checks out, and where dedicated converters become essential.
The most common color conversion in web development. You've got a hex code like #3B82F6 from a design file and you need the RGB values for a CSS rgba() function (or vice versa).
Google does sort of handle this now — if you search for a hex color, it shows a color picker. But it's buried, slow, and doesn't give you all the formats at once.
A dedicated HEX-to-RGB converter gives you instant results: #3B82F6 → rgb(59, 130, 246). More importantly, it also shows you the HSL, CMYK, and other representations simultaneously.
HSL (Hue, Saturation, Lightness) is criminally underused. It's the most intuitive color model for humans:
Want a darker shade of the same color? Decrease lightness. Want a muted version? Decrease saturation. Try doing that intuitively with hex codes. You can't.
Converting between HEX, RGB, and HSL is something I do multiple times per day. Having a tool that shows all three (plus CMYK for print) in real-time as I adjust values is genuinely transformative for design work.
If you've ever designed something for print and wondered why the colors look different than on screen, welcome to the RGB-vs-CMYK problem. Screens use additive color (RGB). Printers use subtractive color (CMYK). The gamuts don't perfectly overlap.
A good color converter will show you the CMYK equivalent of your RGB color and, ideally, warn you if the color falls outside the CMYK gamut (meaning it can't be accurately reproduced in print).
This is the category where I spend 80% of my conversion time. If you write code for a living, you need these.
Base64 encoding converts binary data into ASCII text. You encounter it constantly:
Akousadata:image/png;base64,...)Google can't decode Base64. Period. You need a tool. And you need one that handles both standard Base64 and Base64url (which uses - and _ instead of + and / — critical for URLs and JWTs).
A good Base64 tool also handles encoding (text → Base64) and lets you toggle between UTF-8 and ASCII input encoding, which affects the output for non-ASCII characters.
Ever seen %20 in a URL and wondered what it means? That's a URL-encoded space. URL encoding (percent-encoding) replaces unsafe characters with %XX hex values.
You need URL decoding when:
I once spent 45 minutes debugging an API call because a parameter was triple-encoded. A URL decoder that shows each decoding pass would have saved me immediately.
& is &. < is <. " is ". You know the common ones. But HTML has over 2,000 named entities, and debugging malformed HTML often requires decoding entities you've never seen before.
A dedicated HTML entity encoder/decoder handles both named entities (♥) and numeric entities (♥ or ♥), and it correctly handles edge cases like malformed entities and nested encoding.
JSON Web Tokens are everywhere in modern web authentication. A JWT looks like three Base64url-encoded segments separated by dots:
eyJhbGciOiJIUzI1NiJ9.eyJzdWIiOiIxMjM0NTY3ODkwIn0.signature
Decoding the header and payload is just Base64, but a dedicated JWT decoder:
exp claim)I decode JWTs multiple times per week. Every developer I know does.
This is the big one. Data format conversion is its own universe.
The most common conversion in the DevOps/infrastructure world. Kubernetes uses YAML. APIs return JSON. Config files might be either. You're constantly going back and forth.
Google can't do this. ChatGPT can sort of do it, but it might hallucinate your data or subtly change types. A dedicated converter does it correctly, preserving types, handling edge cases (null values, multiline strings, anchors), and formatting the output readably.
One critical feature: a good JSON-to-YAML converter handles comments. YAML supports comments; JSON doesn't. Converting from YAML to JSON should warn you that comments will be lost. Converting from JSON to YAML should let you add them.
XML is "dead" in the same way that COBOL is "dead" — it's running in millions of production systems and isn't going anywhere. SOAP APIs, Android layouts, Maven configs, RSS feeds, Office file formats — all XML.
Converting between JSON and XML is tricky because they have different data models. JSON has arrays; XML has repeated elements. JSON has null; XML has... well, various representations of null. Attributes in XML have no direct JSON equivalent. A good converter makes explicit choices about these mappings and lets you configure them.
This conversion comes up constantly in data work:
Edge cases that matter: quoted fields with commas inside them, newlines within fields, different delimiters (TSV, semicolons), and header row handling. A good converter handles all of these.
TOML is gaining traction for configuration files (Rust's Cargo.toml, Python's pyproject.toml). It's more readable than JSON for config, less error-prone than YAML (no significant whitespace). Converting between JSON and TOML is niche but important if you're in these ecosystems.
Time conversion is one of those things that seems simple until you actually have to do it.
A Unix timestamp is the number of seconds since January 1, 1970 (UTC). It's how most systems store time internally. You encounter them in:
"What date is 1711152000?" is not a question Google answers well. A Unix timestamp converter instantly tells you: Saturday, March 23, 2024, 00:00:00 UTC. And it shows you the equivalent in any time zone.
Even trickier: millisecond timestamps. JavaScript uses milliseconds (1711152000000), while Unix tradition uses seconds (1711152000). A good converter detects which format you're using and handles both.
"What time is 3 PM EST in IST?" sounds simple. But:
A dedicated time zone converter uses the IANA time zone database, handles DST transitions correctly, and unambiguously identifies each zone. Google's time zone results are... hit or miss.
Different cultures write dates differently: MM/DD/YYYY (US), DD/MM/YYYY (most of the world), YYYY-MM-DD (ISO 8601, the objectively correct format). Converting between these formats — and into programmatic formats like ISO 8601 or RFC 2822 — is a daily task for developers dealing with international data.
Google can convert "255 to binary" (11111111) and "FF to decimal" (255). For simple one-off conversions, it's fine.
But if you're debugging network protocols, reading file headers, analyzing memory dumps, or working with bitwise operations, you need a converter that:
The signed/unsigned distinction is especially important. In two's complement, the binary number 11111111 is 255 (unsigned) or -1 (signed 8-bit). Getting this wrong causes real bugs.
Unicode has over 149,000 characters across 161 scripts. When you encounter a character you don't recognize — or need to find the code point for a specific emoji or symbol — you need a Unicode lookup tool.
Useful conversions:
€ → U+20ACU+1F600 → 😀€ → 0xE2 0x82 0xAC€ → € or €Seems basic, but I still look up ASCII values regularly. What's the decimal value of A? (65.) What character is 0x0A? (Line feed.) What's the difference between \r\n and \n? (13,10 vs. 10 — the eternal Windows-vs-Unix debate.)
A good ASCII converter shows the full table with decimal, hex, octal, binary, and character representations, plus descriptions for control characters (which are otherwise cryptic).
This is a category where online tools genuinely shine, because the alternative is installing desktop software.
The most common image conversion. PNG is lossless (perfect for screenshots, graphics with text, transparency). JPEG is lossy (smaller files, great for photos). Converting between them is a daily task for web developers and content creators.
Key features in a good converter:
WebP offers both lossy and lossless compression, with files typically 25-34% smaller than JPEG/PNG. Google created it, most browsers support it, and it's the recommended format for web images in 2026.
Converting existing PNG/JPEG assets to WebP is one of the easiest performance wins for any website. A good converter lets you control quality, toggle lossy vs. lossless, and preview the result before downloading.
SVG is fundamentally different — it's vector, not raster. You can't meaningfully "convert" a photograph to SVG (you'd get a traced approximation). But converting simple graphics, logos, and icons between SVG and PNG is common and useful.
Going the other direction — rasterizing SVG to PNG at specific dimensions — is something I do weekly for app icons, social media images, and email templates (where SVG support is still spotty).
If you build websites, you convert between typography units constantly.
The most important conversion in modern CSS. rem units are relative to the root font size (typically 16px). So 1rem = 16px, 0.875rem = 14px, 1.5rem = 24px.
Every experienced web developer has these common values memorized. But for less common values — what's 13px in rem? (0.8125rem) — a converter is faster than mental math.
Points (pt) are a print typography unit. 1pt = 1/72 inch. At 96 DPI (standard screen resolution), 1pt ≈ 1.333px. This conversion matters when you're implementing designs that specify font sizes in points, or when you're designing for both print and screen.
Both are relative units, but em is relative to the parent element's font size, while rem is relative to the root font size. This distinction trips up developers constantly. A good converter lets you specify the parent context for em calculations.
vw, vh, vmin, vmax — these are relative to the viewport size. Converting "I want this element to be 300px wide on a 1440px screen" to vw requires knowing the viewport width. A calculator that takes both values and outputs the vw equivalent saves mental overhead.
Google's currency converter uses reasonably fresh exchange rates and covers all major currencies. For "how much is $100 in euros right now," Google is genuinely the best tool.
But there are limitations:
Google has added some crypto support, but it's inconsistent. A dedicated currency converter with crypto support handles BTC, ETH, and dozens of altcoins with real-time rates.
"What was $100 worth in pounds on March 15, 2020?" Google can't tell you. A tool with historical rate data can.
Google doesn't tell you where its exchange rate comes from or when it was last updated. A good currency tool shows the source, timestamp, and often multiple rate sources for comparison.
The rate you see on Google is the mid-market rate — the midpoint between buy and sell prices. It's not what you'll actually get when you exchange money. Banks, payment processors, and exchange services all add a markup. A good converter shows you this reality and may even show you what providers like banks or services would charge.
Here's the thing that took me too long to realize: having all your converters scattered across different websites is a massive productivity drain.
At any given time during a workday, I might need to:
That's five different websites, five different interfaces, five different sets of ads and cookie banners and newsletter popups. By the time I've found and loaded each one, I've lost my train of thought.
When all your converters live in one place, they share a common interface. You learn the patterns once — input on the left, output on the right (or top and bottom), copy button, clear button, swap button. You don't have to re-learn a new UI for every conversion type.
Many standalone converter websites are ad-supported, and the ad density on free tools is... aggressive. Full-page interstitials, auto-playing video ads, "your computer has a virus" redirects. I've seen converter websites where the actual tool takes up less screen space than the ads.
A consolidated, clean tool collection eliminates this entirely.
When converters are organized together, you discover tools you didn't know you needed. I didn't know I needed a CRON expression parser until I saw one in a tool collection and thought, "Wait, this exists?" Now I use it weekly.
This is underrated: browser-based converters that run entirely client-side work without an internet connection.
Think about it. Most unit conversions are just math. Base64 encoding is an algorithm. JSON-to-YAML parsing is a local operation. Color space conversion is a formula. None of these need a server.
When your converters run in the browser:
That last point is critical. If you're decoding a JWT token from your production authentication system, do you really want to paste it into a random website? With a client-side tool, the data stays in your browser. Nothing is transmitted. Nothing is logged on someone else's server.
Let me leave you with a few converter categories that are niche but incredibly useful when you need them:
Writing in Markdown and need the HTML output? Or vice versa — you've got HTML and want to convert it to Markdown for a README? This conversion is simple in concept but tricky in edge cases (nested lists, code blocks, tables).
Not strictly a "converter," but a regex tool converts your intention into verified pattern matching. Testing a regex against sample input and seeing matches highlighted in real-time is infinitely better than guessing and running your code.
0 */6 * * 1-5 — can you read that? (Every 6 hours, Monday through Friday.) A cron expression tool converts between the cryptic syntax and human-readable descriptions, and shows you the next N execution times.
Technically a formatter, not a converter, but it converts unreadable SQL into readable SQL, and that's a conversion I value enormously.
MD5, SHA-1, SHA-256, SHA-512 — generating hashes of strings or files is a one-way "conversion" that comes up in verification, checksums, and security work.
Google's built-in converter is great for the question "how many feet in a mile?" It's useless for the question "decode this Base64 JWT and tell me when it expires."
The world of conversion is enormous. Physical units are the tip of the iceberg. Below the surface, there are color spaces, encoding schemes, data formats, time representations, number systems, typography units, and dozens of specialized domains — each with their own gotchas and edge cases.
What you want is a collection of 200+ converter tools covering every format, unit, and encoding you'll encounter — all in one place, all with a consistent interface, all running in your browser without sending your data to someone else's server.
That's the future of conversion tools. Not a hundred separate websites with a hundred different ad experiences. One place. Every format. Instant results.
Stop Googling for converters. Find a home for all of them. Your workflow will thank you.