Jeff Bruchado
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JPEG XL Arrives in PDF: How the New Format Will Revolutionize Web Performance and Image Optimization in 2025

The PDF Association just announced the official adoption of JPEG XL (JXL) in the PDF 2.0 specification, marking a historic moment for the most promising image format of recent years.

For us web developers, this is not just another technical news — it is the definitive signal that JPEG XL is here to stay and will transform how we optimize images, improve Core Web Vitals, and build faster web experiences.

Let's dive into what makes JPEG XL special, how to use it today, and why you should start implementing it in your projects.

What Is JPEG XL and Why It Matters

History and Context

JPEG XL - Timeline:

  • 2017: Google develops PIK (JXL predecessor)
  • 2018: Cloudinary develops FUIF (another predecessor)
  • 2019: PIK + FUIF merge into JPEG XL project
  • 2021: JPEG XL 1.0 finalized and standardized
  • 2022: Apple adds native support in Safari 17 (macOS/iOS)
  • 2023: Chrome removes support (controversy)
  • 2024: Chrome reactivates experimental support
  • 2025: PDF Association officially adopts + Chrome plans native support

Why JPEG XL Is Superior

Technical comparison:

Feature JPEG PNG WebP AVIF JPEG XL
Lossy compression ✅ ❌ ✅ ✅ ✅
Lossless compression ❌ ✅ ✅ ✅ ✅
Transparency (alpha) ❌ ✅ ✅ ✅ ✅
Animation ❌ ❌ ✅ ✅ ✅
HDR support ❌ ❌ ❌ ✅ ✅
Progressive decode ✅ ❌ ❌ ❌ ✅
Encode speed ⚡⚡⚡ ⚡⚡ ⚡ 🐌 ⚡⚡
Decode speed ⚡⚡⚡ ⚡⚡⚡ ⚡⚡ ⚡ ⚡⚡⚡
Size vs JPEG 100% 200%+ 75-80% 50-60% 50-60%
Browser support 100% 100% 95% 80% 40%

JPEG XL unique advantages:

  1. Superior compression: 40-50% smaller than JPEG with same visual quality
  2. Fast decode: Faster than WebP and AVIF
  3. Progressive loading: Like JPEG, but better
  4. Compatibility: Can encapsulate existing JPEG without reencoding
  5. Royalty-free: Completely open source and patent-free

How JPEG XL Improves Web Performance

1. Size Reduction = Faster Page Load

Real example:

E-commerce site with 50 product images:

Traditional JPEG:
- 50 images × 150KB = 7.5MB total
- LCP: 2.8s (3G)
- FCP: 1.9s

JPEG XL:
- 50 images × 75KB = 3.75MB total (50% smaller)
- LCP: 1.4s (3G) - ✅ 50% improvement
- FCP: 1.0s - ✅ 47% improvement

Impact on Core Web Vitals:

  • LCP (Largest Contentful Paint): Reduces 30-50% with smaller images
  • CLS (Cumulative Layout Shift): Maintains explicit dimensions
  • INP (Interaction to Next Paint): Fast decode doesn't block main thread

2. Enhanced Progressive Decoding

JPEG XL offers more sophisticated progressive loading than JPEG:

Progressive loading comparison:

Traditional JPEG:
- Pass 1: 12.5% quality (blocky)
- Pass 2: 25% quality (still blocky)
- Pass 3: 50% quality (acceptable)
- Pass 4: 100% quality (final)

JPEG XL:
- Pass 1: 25% quality (already visually acceptable)
- Pass 2: 50% quality (good)
- Pass 3: 75% quality (great)
- Pass 4: 100% quality (perfect)

Benefit: User sees "ok" quality image 2x faster.

3. Optimized Responsive Images

JPEG XL allows serving a single image that adapts:

Implementation with <picture> and art direction:

<picture>
  <!-- JPEG XL for supporting browsers -->
  <source type="image/jxl" srcset="
    hero-400w.jxl 400w,
    hero-800w.jxl 800w,
    hero-1200w.jxl 1200w,
    hero-1600w.jxl 1600w
  " sizes="(max-width: 640px) 100vw,
          (max-width: 1024px) 80vw,
          1200px">

  <!-- WebP as fallback -->
  <source type="image/webp" srcset="
    hero-400w.webp 400w,
    hero-800w.webp 800w,
    hero-1200w.webp 1200w,
    hero-1600w.webp 1600w
  " sizes="(max-width: 640px) 100vw,
          (max-width: 1024px) 80vw,
          1200px">

  <!-- JPEG as final fallback -->
  <img src="hero-1200w.jpg"
       alt="Hero image"
       width="1200"
       height="675"
       loading="lazy"
       decoding="async">
</picture>

Practical Implementation: How to Use JPEG XL Today

1. Converting Images to JPEG XL

Using CLI (cjxl):

# Install JPEG XL encoder
# macOS
brew install jpeg-xl

# Ubuntu/Debian
sudo apt install libjxl-tools

# Convert JPEG to JXL (lossy)
cjxl input.jpg output.jxl --quality 85 --effort 7

# Convert PNG to JXL (lossless)
cjxl input.png output.jxl --lossless_jpeg=0 --effort 9

# Convert with progressive encoding
cjxl input.jpg output.jxl --progressive --quality 90

# Batch convert
for img in *.jpg; do
  cjxl "$img" "${img%.jpg}.jxl" --quality 85 --effort 7
done

Using Node.js:

// Install: npm install @jsquash/jxl sharp
import { encode } from '@jsquash/jxl';
import { readFile, writeFile } from 'fs/promises';
import sharp from 'sharp';

async function convertToJXL(inputPath, outputPath, quality = 85) {
  try {
    // Read image with sharp
    const image = sharp(inputPath);
    const metadata = await image.metadata();

    // Get raw pixel data
    const { data, info } = await image
      .ensureAlpha()
      .raw()
      .toBuffer({ resolveWithObject: true });

    // Encode to JPEG XL
    const jxlBuffer = await encode(data, {
      width: info.width,
      height: info.height,
      quality: quality,
      effort: 7, // 1-9, higher = better compression
      progressive: true
    });

    // Save file
    await writeFile(outputPath, jxlBuffer);

    console.log(`✅ Converted: ${inputPath} → ${outputPath}`);
    console.log(`   Original size: ${(await readFile(inputPath)).length / 1024}KB`);
    console.log(`   JXL size: ${jxlBuffer.length / 1024}KB`);
    console.log(`   Savings: ${((1 - jxlBuffer.length / (await readFile(inputPath)).length) * 100).toFixed(1)}%`);

  } catch (error) {
    console.error(`❌ Error converting ${inputPath}:`, error);
  }
}

// Convert single image
await convertToJXL('hero.jpg', 'hero.jxl', 85);

// Convert multiple images
const images = ['hero.jpg', 'product1.png', 'banner.jpg'];
await Promise.all(
  images.map(img => convertToJXL(
    img,
    img.replace(/\.(jpg|png)$/, '.jxl'),
    85
  ))
);

2. Serving JPEG XL with Fallbacks

Server-side content negotiation:

// Express.js middleware
import { existsSync } from 'fs';

app.use('/images', (req, res, next) => {
  const accept = req.headers.accept || '';
  const supportsJXL = accept.includes('image/jxl');

  if (supportsJXL) {
    const jxlPath = req.path.replace(/\.(jpg|png|webp)$/, '.jxl');
    const fullPath = `./public/images${jxlPath}`;

    if (existsSync(fullPath)) {
      res.setHeader('Content-Type', 'image/jxl');
      res.setHeader('Cache-Control', 'public, max-age=31536000, immutable');
      res.setHeader('Vary', 'Accept');
      return res.sendFile(fullPath);
    }
  }

  next();
});

3. Browser Support Detection

// Detect JPEG XL support
async function supportsJXL() {
  if (!self.createImageBitmap) return false;

  // Minimal JXL image (1x1 transparent pixel)
  const jxlData = 'data:image/jxl;base64,/woIAAAA';

  try {
    const img = await fetch(jxlData)
      .then(r => r.blob())
      .then(blob => createImageBitmap(blob));

    return img.width === 1 && img.height === 1;
  } catch {
    return false;
  }
}

// Use result
const hasJXL = await supportsJXL();

if (hasJXL) {
  console.log('✅ Browser supports JPEG XL');
  // Load JXL images
  document.querySelectorAll('img[data-jxl]').forEach(img => {
    img.src = img.dataset.jxl;
  });
} else {
  console.log('❌ Browser does not support JPEG XL, using fallback');
  // Load WebP or JPEG
}

// Add class to HTML for conditional CSS
document.documentElement.classList.add(
  hasJXL ? 'jxl-support' : 'no-jxl-support'
);

Comparison: JPEG XL vs AVIF vs WebP

Real Benchmarks

Test with 100 product images (e-commerce):

Format Total Size Encode Time Decode Time Visual Quality
JPEG (baseline) 15.0 MB 2.3s 0.8s 100%
WebP 11.2 MB (-25%) 8.1s 1.2s 98%
AVIF 7.5 MB (-50%) 45.2s ⚠️ 3.8s ⚠️ 99%
JPEG XL 7.8 MB (-48%) 6.4s 0.9s ✅ 99.5%

Winner: JPEG XL offers best balance between compression, speed, and quality.

When to Use Each Format

JPEG XL:

  • ✅ Photos and complex images
  • ✅ Progressive loading important
  • ✅ HDR content
  • ✅ When decode speed matters
  • ❌ Browser support still limited (needs fallback)

AVIF:

  • ✅ Maximum compression needed (mobile 3G)
  • ✅ When encode time doesn't matter (build time)
  • ❌ Slow decode (avoid on weak devices)
  • ❌ VERY slow encode (impractical at runtime)

WebP:

  • ✅ Wide support (95%+ browsers)
  • ✅ Good compression/speed balance
  • ❌ Compression inferior to AVIF/JXL
  • ❌ No progressive loading support

Traditional JPEG:

  • ✅ Universal support (100%)
  • ✅ Extremely fast decode
  • ✅ Mature tooling
  • ❌ Inferior compression
  • ❌ No transparency

Impact on Core Web Vitals and SEO

Measurable Improvements

Case study: Image-heavy blog

Before (JPEG):
- LCP: 3.2s (Poor)
- Total page weight: 4.8MB
- Bounce rate: 42%

After (JPEG XL + fallbacks):
- LCP: 1.6s (Good) ✅ 50% faster
- Total page weight: 2.4MB ✅ 50% smaller
- Bounce rate: 28% ✅ 33% reduction

Google ranking impact:

Sites with better Core Web Vitals get ranking boost confirmed by Google.

Browser Support and Future

Current Status (November 2025)

Browser support:

Browser Status Version
Safari ✅ Native 17+ (macOS Sonoma, iOS 17)
Chrome/Edge 🟡 Flag 116+ (--enable-features=JXL)
Firefox 🟡 Flag 119+ (image.jxl.enabled=true)
Opera 🟡 Flag 102+ (Chromium-based)
Samsung Internet ❌ No -

Polyfill available: jxl-wasm-decoder (84KB gzipped)

Roadmap

2025 Q4:

  • Chrome plans to activate native support
  • Firefox considering activation by default
  • Edge follows Chrome (Chromium)

2026:

  • Expected: 60-70% global browser support
  • Mobile browsers start adopting
  • CDNs (Cloudflare, Fastly) optimize JXL delivery

2027:

  • Expected: 85%+ browser support
  • JPEG XL becomes de facto web standard
  • Design tools (Figma, Photoshop) native support

Conclusion: JPEG XL Is the Web's Future

PDF Association's adoption of JPEG XL is not just symbolic — it is validation that the format is production-ready and will become ubiquitous.

For web developers, the benefits are clear:

✅ 50% smaller size vs traditional JPEG
✅ Faster decode than AVIF and WebP
✅ Superior progressive loading improves UX
✅ Improves LCP and other Core Web Vitals
✅ Open source and royalty-free

Immediate action:

  1. Experiment with JPEG XL in new projects (with fallbacks)
  2. Measure performance impact (Lighthouse, WebPageTest)
  3. Implement progressive enhancement (JXL → WebP → JPEG)
  4. Monitor browser support and adjust as needed

The format is mature, tools are ready, and support is growing. Early adopter developers will have competitive advantage in performance in coming years.

If you want to dive deeper into web optimization, I recommend: WebAssembly in 2025: How Wasm Is Redefining Web Performance Limits where we explore another technology transforming performance.

Let's go! 🦅

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