mozjpeg vs libjpeg-turbo: Which Encoder Should You Use?

Summary: mozjpeg and libjpeg-turbo are two popular JPEG encoders. Choose mozjpeg when you want smallest file sizes for web delivery and don't mind slightly higher CPU costs. Choose libjpeg-turbo when speed and real-time encoding are crucial, such as camera pipelines and server-side image processing where latency matters.

Why encoder choice matters

The JPEG standard describes how images are decoded, but encoders have significant leeway in quantization tables, optimization passes, and entropy coding. These choices affect three key metrics:

• Visual quality: How natural or artifact-free images appear at a given file size.
• File size: Bytes on disk or sent over the network.
• Encoding speed: CPU time and throughput for batch or real-time workflows.

libjpeg-turbo: speed and compatibility

libjpeg-turbo is optimized using SIMD instructions (SSE2, ARM NEON) and focuses on fast, correct encoding and decoding mostly compatible with the baseline JPEG standard. It is an excellent choice when throughput matters:

• Performance: Exceptional, especially on servers and mobile devices.
• Compatibility: Near-universal support in browsers, editors, and platforms.
• Quality: Good results, but less aggressive size reduction compared to mozjpeg at equivalent quality settings.

mozjpeg: better compression for web images

mozjpeg originated from Mozilla with the aim of reducing file sizes while preserving perceptual quality. It adds several optimizations:

• Improved quantization tables: Tuned to human perception.
• Progressive scan optimizations: Better initial image fidelity.
• Advanced entropy optimization: Improved Huffman tables and additional post-processing that shrink files.

Benchmark methodology

We ran a benchmark with a diverse 200-image set (landscape, portrait, high ISO, low light, synthetic textures). Each encoder was run with comparable nominal quality settings and the outputs compared by:

• Peak Signal-to-Noise Ratio (PSNR)
• Structural Similarity Index (SSIM)
• Perceptual metrics like LPIPS
• Encoding time on a mid-range server (8 cores)
• Resulting file sizes

Key findings

1. File size: mozjpeg yielded 10-20% smaller files on average at similar perceptual quality when compared to libjpeg-turbo.
2. Encoding time: libjpeg-turbo was 2-4x faster in our tests, making it better for high-volume pipelines.
3. Quality: Visual differences at common web quality settings (80-90) were subtle; mozjpeg tended to keep better fine detail in textured areas while libjpeg-turbo preserved smoother gradients.
4. Edge cases: For high-ISO noisy images, mozjpeg's optimizations sometimes preserved noise more vividly, which can be desirable or undesirable depending on aims.

Recommendations

Choose mozjpeg if:

• Your main goal is minimizing bandwidth for web images.
• Encoding time is not a bottleneck (offline export, scheduled jobs).
• You want progressive JPEGs with optimized scanning.

Choose libjpeg-turbo if:

• You need real-time encoding or very high throughput.
• Your stack relies on minimal CPU usage or is constrained on-device.
• You prefer a widely tested and stable library for production.

Practical settings and hybrid approaches

Many teams use a hybrid approach: libjpeg-turbo for on-the-fly thumbnails and mozjpeg for final web-optimized assets. You can also feed libjpeg-turbo output into a mozjpeg recompression step with tools like jpeg-recompress to gain size reductions with modest extra CPU time.

"Optimization is about trade-offs. Evaluate based on your traffic profile, compute budget, and visual priorities."

Conclusion

Both encoders are excellent; the right one depends on operational constraints. For modern web delivery pipelines seeking maximum bandwidth savings, mozjpeg is often the winner. For latency-sensitive services and massive throughput, libjpeg-turbo remains unmatched. We publish detailed scripts and benchmarks in the companion repository linked below.