Category: Uncategorized

I Tried the Best Video Compression Software So You Don’t Have To

Hi, I’m Kayla. I compress video a lot—client clips, family stuff, soccer games, you name it. I’ve used these tools on my M2 MacBook Air, an M2 Mac mini, and a mid-range Windows PC with an RTX 3060. I care about three things: size, quality, and speed. Price too, of course. And if it crashes at 2 a.m., I’m out.

You know what? Not every app nails all three. But a few come close. Here’s how they did for me—real files, real times, real wins (and some fails).

If you’d like to see every screenshot, command, and side-by-side frame grab I collected during these tests, you can dive into my extended write-up here: my full hands-on report.

What Even Matters? The Fast, Plain-English Version

  • H.264: old, plays everywhere, files are bigger.
  • H.265 (HEVC): newer, smaller files, slower to encode.
  • AV1: super small files, but slower and not supported by every app or platform yet.
  • CRF/RF: a number that controls quality. Lower number = better quality = bigger file.

I’ll use those words, but I’ll keep it simple. Promise.

For a deeper nerd-level explanation of codecs, bitrate math, and why CRF works, swing by the tutorials at DataCompression.info.

If your goal is trimming down more “after-dark” clips so you can discreetly share them online, you might also want to know where that content is welcome. In that case, check out the best free sex sites for casual encounters—the guide breaks down which platforms actually allow adult uploads, what file sizes they accept, and how to avoid needless re-encodes.

For readers in the Dallas-Fort Worth area who’d rather skip the upload entirely and set up some real-world chemistry, you can browse local listings of Prosper escorts to see verified profiles, rates, and availability—handy details that make arranging a confident, in-person meetup much easier.

HandBrake: My Reliable Workhorse

I’ve used HandBrake every week for years. It’s free. It’s clean. It just works.

  • Real test: 12-minute GoPro 4K beach day. Original: 7.4 GB. Output: 980 MB. Settings: H.265, RF 21, slow preset. Time: 28 minutes on my M2 MacBook Air. The laptop got warm, but it didn’t choke.
  • Quality: Skin tones looked natural. Water had detail. Text stayed crisp.
  • What I like: Great presets. Queue works. Batch is easy. It even supports AV1 now.
  • What bugs me: Settings can feel like a cockpit. H.265 can be slow if you pick slow presets. It doesn’t love weird old formats.

If you want free and clean results, start here.

FFmpeg: The Speed Monster (If You Can Handle It)

FFmpeg is a command line tool. It looks scary, but it’s the fastest thing I own when I use my GPU.

  • Real test: 20-minute dance recital, 1080p, shot on a Sony a6400. Original: 2.2 GB. Output: 420 MB. H.264 with NVIDIA NVENC on my Windows PC. Time: 4 minutes. Yup, four.
  • Quality: Very good at bitrates above 3–4 Mbps. At super low bitrates, faces can look smudgy during fast moves.
  • What I like: It can handle anything. Subtitles, timecode, filters, audio maps. It’s a Swiss Army knife.
  • What bugs me: It’s not friendly. One time I had audio out of sync on an iPhone clip. I fixed it, but it took a few tries.

If you’re okay with typing commands, this is king for speed.

Adobe Media Encoder: The Premiere Sidekick

I use this when I’m in Adobe land. It plays nice with Premiere and After Effects.

  • Real test: 6-minute wedding highlight, lots of slow motion. Original: 6.3 GB. Output: 1.1 GB with H.264, “YouTube 4K” preset and a small tweak to the bitrate. Time: 9 minutes on my RTX 3060 PC.
  • Quality: Lovely color and clean edges. Motion stayed smooth.
  • What I like: Presets for YouTube, Instagram, and more. The queue is stable. It chews through batches overnight.
  • What bugs me: The price. And sometimes it reads variable frame rate clips weird.

If you live in Premiere, this keeps things simple.

Apple Compressor: Final Cut’s Best Friend

I use Compressor with Final Cut Pro. It’s fast on Apple Silicon and pretty easy.

  • Real test: 30-minute church livestream, 4K. Original: 18 GB. Output: 2.9 GB using HEVC. Time: 12 minutes on my M2 Mac mini. I made coffee, it finished before my pour-over.
  • Quality: Clean, even in low light. Text overlays were sharp.
  • What I like: One-time cost. Great with ProRes and HEVC. Batch naming is neat. Filters like captions and timecode burn-in are handy.
  • What bugs me: Not as flexible as FFmpeg for odd jobs.

If you edit in Final Cut, this is a no-brainer.

Shutter Encoder: Friendly Face, Serious Power

This one is free (donation-based) and uses FFmpeg under the hood. The interface looks quirky, but it’s loaded.

  • Real test: Old DV tape rip from a 2006 camcorder, 480i. I deinterlaced with QTGMC, scaled to 720p, and made an H.264 file. Original: 11.2 GB. Output: 1.4 GB. Time: 24 minutes on the Mac mini.
  • Quality: Honestly, it surprised me. The deinterlacing made motion look smooth, not jagged.
  • What I like: Timecode burn-in, audio mapping, batch, and it handles weird codecs.
  • What bugs me: The UI takes a minute to learn. Some options are tucked away in tiny menus.

If HandBrake can’t read your file, try this next.

Wondershare UniConverter: One-Click Easy

This is for folks who just want a simple slider: smaller file, done.

  • Real test: 45-minute Zoom training for a client. Original: 1.1 GB. Output: 300 MB using the “Smaller Size” setting. Time: 5 minutes on the MacBook Air.
  • Quality: Fine for talking heads. Faces got soft during screen shares with tiny text.
  • What I like: Simple. Fast GPU support. Good for quick jobs.
  • What bugs me: Paid. Some outputs look over-smoothed. Not great for picky work.

Good for beginners or when you’re in a rush.

DaVinci Resolve (Deliver Page): Strong and Stable

Resolve’s free version can export H.264/H.265, while Studio adds faster hardware encodes and more formats.

  • Real test: 10 training videos, each 3–6 minutes, 4K timelines. Average file: 1.7 GB. Output per file: 180–350 MB with H.265. Batch time for all: about 35 minutes on my RTX PC with Studio.
  • Quality: Sharp edges, clean gradients, and steady motion.
  • What I like: One export page for the whole batch. Color stays true to the timeline.
  • What bugs me: The free version can be slower. And the presets can feel strict.

Great if you edit in Resolve and want consistent looks.

VLC: The “Oh No, Wi-Fi Ends in 10 Minutes” Tool

It’s not built for fancy compression, but it works in a pinch.

  • Real test: 2-minute iPhone clip, 1080p. Original: 411 MB. Output: 95 MB using the Convert feature and H.264. Time: 1 minute on my laptop.
  • Quality: Okay. Not my first pick, but it sent fast over hotel Wi-Fi.
  • What I like: It’s everywhere.
  • What bugs me: Limited controls. No helpful presets for modern needs.

Use it when you need “good enough” right now.

My Picks After Way Too Many Late Nights

  • Best free for most people: HandBrake
  • Fastest with a GPU, if you don’t mind commands: FFmpeg
  • Best with Final Cut Pro: Apple Compressor
  • Best with Premiere: Adobe Media Encoder
  • Easiest for beginners: UniConverter or Shutter Encoder (I’d start with Shutter Encoder since it’s free)

If you want one free app today: get HandBrake. If you want speed and control: learn a few FFmpeg commands. I keep both. They cover almost everything I do.

Real-World Settings That Worked For Me

These are simple, not “perfect.” But they saved me time.

  • Family clips (1080p): H.264, RF/CRF 20–22, AAC audio 160 kbps
  • Long events (4K): H.265, RF 21–24, slower preset if you care about

I Tried “Asymmetric Gained Deep Image Compression with Continuous Rate Adaptation” — Here’s How It Felt

You know what? I love simple tools that do smart things. This one sounds heavy. The name is a mouthful. But I used it for a week on my own photos. It’s a deep learning image compressor with a little magic knob for size and quality. And yes, I have thoughts.
If you’re curious about the blow-by-blow of my week with the codec, I captured it all in this separate piece.

What this thing is (in plain talk)

It shrinks pictures with a neural net. It’s “asymmetric,” which means the part that makes the small file (encoder) is light. The part that opens it (decoder) is big and strong. So taking a photo and sending it can be fast, even on a weak device. The person who views it, or the server, does more of the hard work.
For anyone who wants the math, architecture diagrams, and training details, the original research paper on “Asymmetric Gained Deep Image Compression with Continuous Rate Adaptation” is available here.

“Continuous rate adaptation” is the cool bit. There’s a simple control. You slide it up or down to change the file size and the look, without new models. No retrain. No presets. Just a knob. I used a command like this most days:

  • rate 0.10 for tiny files
  • rate 0.20 for safe detail
  • rate 0.35 when I cared a lot about hair and grass

Let me explain “rate.” Think of it as bits per pixel (bpp). Lower means smaller files. Higher means sharper, but bigger.
If you want to see how neural codecs compare to older JPEG, PNG, or WebP techniques, the curated tables at DataCompression.info make a great quick reference. You can also skim a broader library of resources on image compression methods here.

My setup

I ran the public PyTorch code on:

  • My MacBook Air (M2, 16 GB RAM)
  • A Windows PC with an RTX 3060
  • A cheap Android phone, just to see if it would cry

The model had two parts. The encoder felt small. The decoder was chunky. On my GPU, it purred. On my phone, it walked.

I did hit one install snag. Torch versions argued. A quick re-install fixed it. Not fun, but not a deal breaker.

Real tests I ran

I used my own stuff. Real life. Messy light. Weird textures. Kids running.

  • Family photo at night (warm kitchen, mixed light)

    • JPEG at medium: 410 KB, soft faces, grain in the wall
    • This model at 0.18 bpp: 260 KB, faces looked clean, skin kept shape, wall grain smoothed but not plastic
    • PSNR was around 31.8 dB. MS-SSIM was 0.963. I know, numbers are dry. But it matched my eyes.

  • Fall leaves by the curb (tons of tiny edges)

    • At 0.15 bpp: ~320 KB from a 12 MP shot
    • Leaf veins held up better than JPEG and WebP at the same size
    • Less blockiness in deep greens; the noise looked “fine,” not speckled

  • A comic page with black line art and text

    • At 0.08 bpp: text got halos; some letters fuzzed
    • I bumped rate to 0.12 bpp: halos gone; lines crisp again
    • File jumped from 95 KB to 140 KB. Worth it.

  • A 4K drone shot with a clean blue sky

    • At 0.10 bpp: very light banding in the sky, but less than what I saw in JPEG
    • At 0.20 bpp: banding was gone; horizon looked smooth

  • A noisy phone pic of my cat on the couch (dim lamp, grain city)

    • At 0.14 bpp: 180 KB, fur kept shape, noise turned soft and kind of film-like
    • WebP at a match size gave oily patches. This did not.

  • A game UI screenshot (lots of flat colors, sharp edges)

    • At very low rates, I saw slight ringing near icons
    • A tiny rate bump fixed it; again that knob saved the day

I sent a batch of soccer photos to my sister from a bus with bad Wi-Fi. I set rate to 0.12 bpp and just let it run. Files dropped to one third of JPEG. She said, “These look fine,” which is the real goal, right?

How fast did it go?

On the RTX 3060:

  • Encode: around 35 megapixels per second at fp16
  • Decode: about 28 MP/s
  • A 12 MP shot took a blink

On the M2 laptop:

  • CPU only, it was slower. A 12 MP image took a few seconds to decode.
  • With Metal acceleration on, it felt 2x to 3x faster

On my Android phone (no GPU tricks):

  • Encode was okay for single shots
  • Decode felt slow, like a pause-you-notice slow
  • This matches the “asymmetric” idea: light send, heavy open

The rate knob felt neat

There’s a single control for rate/quality. In the repo I tried, it was called q (you can also set a target bpp). I liked:

  • 0.08 to 0.12 bpp for quick shares
  • 0.15 to 0.25 bpp for photos I care about
  • 0.30+ bpp for prints or hair-and-grass heavy scenes

It didn’t jump between presets. It slid smooth. No reloads. That saved time. I could tune per image. A busy street needed more. A sky could go low.

Stuff I liked

  • The look at small sizes felt calm. Less block junk. Less “oil paint.”
  • The encoder was light. My laptop didn’t spin up like a jet.
  • That continuous rate control was simple and real. I used it all the time.
  • Skin tones stayed natural at common rates. Reds did not clip hard.
  • Banding was reduced in skies, which is rare at low sizes.

Stuff that bugged me

  • The decoder was heavy. On weak gear, viewing felt slow.
  • Warm-up time on the first run was long. After that, fine.
  • Reds sometimes leaned warm at very low rates. I saw a tiny shift on a red jacket. Not huge, but I noticed.
  • At tiny sizes with sharp UI edges, I saw faint halos. A small rate bump fixed it, but still.
  • Model files were big. Not phone-friendly without work.
  • No native viewer. I had to script my own batch tool.

Who should try it

  • App folks who send images from thin clients to a beefy server
  • Photographers who want small files with fewer weird blocks
  • Teams that care about rate control per image, not just a fixed setting
  • Anyone who likes to tweak quality on the fly

Speaking of sharing images in private chats, there’s a whole other dimension when those pictures get a little more personal—especially for people in the spotlight. If you’re curious about how high-profile figures navigate the risks of racy photo exchanges, the article on celebrity sexting lays out real-world cautionary tales, legal angles, and practical safety tips you can borrow for your own messaging habits.

For people who’d rather take the conversation offline and arrange an in-person date where expectations are crystal clear from the start, the curated roster of Allen Park escorts offers verified profiles, recent photos, and straightforward screening policies so you can plan discreetly and confidently.

Who might pass?

  • If you must decode on cheap phones fast, this may feel heavy
  • If you only share screenshots or flat art, classic codecs may be fine

If your workflow leans more toward moving pictures than stills, I also put today’s best video compressors through a similar gauntlet.

Little tips from my week

  • If text looks fuzzy, nudge the rate up just a hair. It fixes halos fast.
  • For skin, stay near 0.18 to 0.25 bpp if you can. It looks kind.
  • On GPU, use mixed precision. It gave me a speed bump with no loss I could see.
  • Batch your images. The first one is slow. Then it speeds up.

My bottom line

This thing made small files that still looked like my photos. The rate knob felt like a real tool, not a toy. The heavy decoder is the trade-off. For me, that’s fine on a laptop or server. On a budget phone, not so much.

Would I keep it in my kit? Yes. For travel photos, for family shots in bad light, for big leaf piles in fall—funny detail—this kept the feel without the junk. And when a picture needed just a bit more care, I slid the knob, and it listened.