nowfound

Life & fun · July 15, 2026

misa77 - a codec that decodes 2x faster than LZ4 (at better ratios)

I've spent the last few months working on this codec. It has the following characteristics: - SOTA decompression throughput in its ratio class - Decent ratios (comparable to LZ4 at high effort levels) - Slow compression Most of the gains can be attributed to reducing branches and making decompression very friendly to out-of-order cores, by using a smart format. Results on the tarred Silesia corpus on Intel x86-64 follow: codec decode ratio encode misa77 -0 5219 MB/s 42.64% 54.5 MB/s misa77 -1 4274 MB/s 39.65% 51.2 MB/s lz4 2505 MB/s 47.59% 371 MB/s lz4hc -12…

misa77 - a codec that decodes 2x faster than LZ4 (at better ratios) launched on July 15, 2026 with 164 votes, #204 of 24,623 launches that month and more than 95% of that year's launches.

Visit github.com ↗Alternativestop 1% of July 2026

In plain words

misa77 is a data compression codec designed to decompress data significantly faster than LZ4 while achieving comparable or better compression ratios. It targets developers and systems requiring high decompression throughput with reasonable space efficiency. The codec achieves up to 5,219 MB/s decompression speed through a branch-reduced format optimized for modern processor architectures, though compression is slower than alternatives. It works best for applications prioritizing decompression performance over compression speed.

written from the facts on this page · September 2026

From the sources

Ridiculously fast decompression at good ratios. misa77 is 1.5-3x faster than LZ4 for decompression on x86 and ARM (with better ratios!). - welcome-to-the-sunny-side/misa77

misa77 is an LZ-based codec that targets the write-once, read-many niche. In particular, it aims to satisfy the following criteria: Slow compression is the obvious tradeoff that one makes to achieve the above. misa77 has six compression effort levels as of v0.6.0. For most shapes of data, encode time increases and ratio decreases with increasing level, but decompression throughput is not similarly monotonic. In general, level 1 offers the fastest decode throughput. More information about effort levels can be found here . Note: As of now, level 4 doesn't have a safe decompressor. It will be added soon. Let's first see some cross-platform results for the Silesia Corpus . As misa77's…from github.com

In the maker’s words, at launch

I've spent the last few months working on this codec. It has the following characteristics: - SOTA decompression throughput in its ratio class - Decent ratios (comparable to LZ4 at high effort levels) - Slow compression Most of the gains can be attributed to reducing branches and making decompression very friendly to…

Does a similar job

all alternatives →
  • 10-40% faster LZMA decoder using x86 CMOVcc2021 · gist.github.com · ▲205

    Faster LZMA decoder for x86 CPUs (patch for XZ Utils). - faster_lzma_decoder_x86.patch

  • ZXC – Asymmetric, +40% decode vs. LZ4 on ARM (C, BSD-3, Fuzzed)Dec 2025 · github.com · ▲28

    Hello HN, author here. I built ZXC, a lossless compression library designed specifically for "Write Once, Read Many" scenarios (Game assets, Firmware, App bundles). The Concept: Standard real-time codecs (LZ4, Snappy) are designed for symmetry. ZXC explores an asymmetric approach: it spends significantly more CPU cycles at compression time to generate a bitstream specifically structured for modern, wide-issue execution pipelines (maximizing Instruction Level Parallelism). Performance (Verified via lzbench integration): ZXC was merged into the official lzbench repository monday. ARM64 (Apple…

  • Micro LZMA decoder (x86 assembly code golf)2022 · github.com · ▲56

    Micro LZMA decoder. Contribute to ilyakurdyukov/micro-lzmadec development by creating an account on GitHub.

  • OA
    Overfitted a 900KB Transformer to Compress a 100MB CSV into 7MBJun 2026 · ▲112

    I built an experiment that uses an overfitted transformer and arithmetic coding to compress individual files. Instead of training the model to generalize, I train a 900KB transformer to memorize a single file and predict the next byte. Those predictions are fed into an arithmetic coder to produce the compressed output. On a 100MB NYC taxi CSV, it compresses to about 7MB (~0.5 bits/byte). On a 100MB slice of enwik9, it compresses to about 21MB (~1.68 bits/byte). It's pretty slow right now (roughly 20–30 minutes of training and 45 minutes each for compression and decompression on my…

  • Rapidgzip – Truly Parallel Gzip Decompression with 10 GB/s2023 · github.com · ▲35

    I have posted a much earlier version of this over a year ago [0]. Since then a lot has changed. Obviously, the name has changed. This happened for the paper publication [1]. I have also optimized the speed, integrated ISA-L for special cases, limited the compression-ratio-dependent maximum memory consumption, and finally added parallelized CRC32 computation, which adds ~5% overhead no matter the number of cores used. At this point, I am leaning towards calling it production-ready although there are still many ideas for improvements. Redoing the benchmarks of the older Show HN, would look…

  • (bits) of a Libc, Optimized for Wasm2025 · github.com · ▲78

    I make a no-CGO Go SQLite driver, by compiling the amalgamation to Wasm, then loading the result with wazero (a CGO-free Wasm runtime). To compile SQLite, I use wasi-sdk, which uses wasi-libc, which is based on musl. It's been said that musl is slow(er than glibc), which is true, to a point. musl uses SWAR on a size_t to implement various functions in string.h. This is fine, except size_t is just 32-bit on Wasm. I found that implementing a few of those functions with Wasm SIMD128 can make them go around 4x faster. Other functions don't even use SWAR; redoing those can make them 16x faster.…

More life & fun this month

the category →

Source: Show HN post ↗ · launch text quoted in part

Launched alongside, July 2026

the whole month →
  • IR
    I replaced a $120k bowling center system with $1,600 in ESP32s▲2,935

    I might be the only SRE on Earth with his own bowling center. It's a more in-depth gig than you'd think. My family and I bought an abandoned 8-lane bowling center in the rural mid-west. In our small town there weren't many recreation options for families. You've heard of a food desert? This is an R&R desert. It had been abandoned for a good reason. The roof leaks, the electrical system was constantly surging, and my 70-year-old bowling equipment (still) doesn't work perfectly. The system that keeps your score is particularly interesting to me. It's the thing you watch during your game, but…

    Life & fun · Jul 2026

  • Elevators▲1,680

    How elevators push your buttons

    Life & fun · Jul 2026 · john.fun

  • 18 Words▲1,160

    Play 18 Words, the free daily word puzzle. The official home is 18words.com. Tap Play now to open today

    Life & fun · Jul 2026 · 18words.com

  • BA
    Bento - An entire PowerPoint in one HTML file (edit+view+data+collab)▲1,033

    Over the past few months, our team has been building more and more slidedecks using web frontend technologies with coding harnesses like Claude Code, but a common complaint is to make even small edits we need to edit the code either manually or via the harness. To avoid this loop, I ended up creating Bento, a single HTML file with everything you need in a slide tool including animations and shared editing. There's no install or cloud login, everything works offline. The default deck is around 560 KB and it doesn't need to fetch anything once you got it. Open it in a browser and then you can…

    Dev tools · Jul 2026 · bento.page

  • Getting GLM 5.2 running on my slow computer▲937

    A few days ago I found myself trying out GLM 5.2 and was really positively impressed. The capabilities and security I was getting from this LLM are similar to those I've gotten from models like Claude or GPT, and this really surprised me. But then I thought, "I wonder how it would work on a normal computer like mine," and above all, "I wonder if it would work without going into OOM on a computer like mine." So I started working with the help of agents to test this possibility. I started converting the model to int4, understanding MTP usage, and if possible implementing DSA for long context.…

    AI · Jul 2026 · github.com

  • OpenSEO▲928

    Hello! For the last 2 months, I've been building OpenSEO. It's a user friendly UI wrapping the DataForSEO API which has high quality SEO data for keywords, backlinks, AI SEO and competitor research. Instead of paying $100+ per month, you buy DataForSEO credits and pay only for usage. The coolest thing about the project so far has been hearing about what people are building on top of it. People are using coding agents to quickly integrate with Google Search Console, Google Ads and building their own AI SEO and reporting features. Many were already building their own custom solutions around…

    Dev tools · Jul 2026 · openseo.so