Why MP4 Is Still Dominating Despite Its Age

Introduction

Despite being over two decades old, MP4 continues to reign supreme in the video streaming landscape. While newer codecs like AV1 and VVC promise better compression, MP4's dominance stems from three critical factors: universal hardware decode support, seamless CMAF integration, and a mature DRM ecosystem. (The Broadcast Bridge) However, the format's longevity is being extended through AI-powered optimization tools like Sima Labs' SimaBit, which reduces bandwidth requirements by 22% or more while maintaining quality. (Sima Labs)

The streaming industry processes massive volumes daily - platforms like YouTube ingest over 500 hours of footage every minute. (Sima Labs) This scale demands formats that work reliably across billions of devices, making MP4's proven track record invaluable. While the codec wars continue with new releases of VVC and AV2 expected in the next two years, MP4's established infrastructure and AI-enhanced capabilities ensure its continued relevance. (The Broadcast Bridge)

The Hardware Decode Advantage

Universal Device Support

MP4's most significant advantage lies in its universal hardware decode support. Every smartphone, tablet, smart TV, and streaming device manufactured in the last decade includes dedicated MP4 decoding chips. (Pixflow) This hardware acceleration is crucial for mobile devices, which have smaller screens, more constrained computing power and storage, and are served by cellular networks with generally lower bandwidth than fixed line broadband infrastructures. (The Broadcast Bridge)

The best video format for YouTube is MP4 with H.264 video codec and AAC audio, and while YouTube supports formats like MOV, AVI, and WebM, MP4 remains the most reliable. (Pixflow) This reliability stems from the format's deep integration into silicon - manufacturers have optimized their chips specifically for MP4 decode operations over many generations.

Battery Life and Performance Benefits

Hardware decode support translates directly into better battery life and smoother playback. When devices can offload video processing to dedicated chips rather than the main CPU, power consumption drops significantly. This is particularly important for mobile streaming, where battery life directly impacts user experience. (The Broadcast Bridge)

Social media platforms compress and reprocess every video upload to balance playback performance and bandwidth use. (Pixflow) The widespread hardware support for MP4 makes this processing more efficient, allowing platforms to deliver consistent experiences across diverse device ecosystems.

CMAF: The Streaming Standard Built on MP4

Unified Packaging for Multiple Platforms

Common Media Application Format (CMAF) has become the de facto standard for adaptive streaming, and it's built entirely on MP4 foundations. CMAF allows content providers to create a single set of media files that work across different streaming protocols like DASH and HLS, dramatically simplifying content delivery workflows.

This unified approach is particularly valuable given the scale of modern streaming. Every minute, platforms like YouTube ingest 500+ hours of footage, and CMAF's MP4-based structure ensures this content can be efficiently packaged and delivered across multiple platforms without format conversion. (Sima Labs)

Low-Latency Streaming Capabilities

CMAF's chunked transfer encoding enables ultra-low latency streaming, crucial for live events and interactive applications. The format's MP4 foundation provides the reliability needed for real-time delivery while maintaining compatibility with existing CDN infrastructure. (Bitmovin)

Streamers are turning to AI to improve compression performance and reduce costs, and CMAF's standardized structure makes it easier to integrate AI-powered optimization tools. (IBC) This compatibility ensures that innovations like Sima Labs' SimaBit can seamlessly integrate into existing CMAF workflows without disrupting established delivery pipelines.

The Mature DRM Ecosystem

Established Security Infrastructure

MP4's longevity has allowed for the development of a comprehensive Digital Rights Management (DRM) ecosystem. Major DRM providers like Widevine, PlayReady, and FairPlay have optimized their solutions specifically for MP4 containers, creating a security infrastructure that content owners trust for premium content protection.

This mature ecosystem is particularly important for streaming services delivering high-value content. The established DRM support for MP4 means that content providers can implement robust protection without worrying about compatibility issues across different devices and platforms. (Pixflow)

Cross-Platform Compatibility

The DRM ecosystem around MP4 ensures consistent content protection across web browsers, mobile apps, smart TVs, and set-top boxes. This universal compatibility is crucial for content distributors who need to deliver protected content to diverse audiences without maintaining separate encryption workflows for different platforms.

Newer devices like the iPhone 12 and iPhone 13 use high efficiency CODECs for video recording, but still maintain backward compatibility with MP4 DRM systems. (Sked Social) This ensures that even as recording technologies evolve, the established DRM infrastructure continues to function reliably.

AI Enhancement: Extending MP4's Reign

Bandwidth Reduction Without Quality Loss

While MP4 may be an older format, AI preprocessing engines are giving it new life by dramatically improving its efficiency. Sima Labs' SimaBit AI preprocessing engine reduces video bandwidth requirements by 22% or more while boosting perceptual quality. (Sima Labs) The engine slips in front of any encoder - H.264, HEVC, AV1, AV2 or custom - so streamers can eliminate buffering and shrink CDN costs without changing their existing workflows.

This approach is particularly valuable because it preserves existing infrastructure investments. SimaBit installs in front of any encoder - H.264, HEVC, AV1, AV2, or custom - so teams keep their proven toolchains. (Sima Labs) Rather than forcing a complete migration to newer codecs, AI enhancement allows organizations to extract more value from their current MP4-based systems.

Addressing Modern Content Challenges

AI-generated content presents unique challenges for traditional compression algorithms. AI-generated footage is especially vulnerable because subtle textures and gradients get quantized away during encoding. (Sima Labs) Social platforms crush gorgeous Midjourney clips with aggressive compression, leaving creators frustrated with the quality loss.

Sima Labs offers AI tools like SimaBit to preserve Midjourney AI video quality on social media. (Sima Labs) Every platform re-encodes to H.264 or H.265 at fixed target bitrates, but AI preprocessing can optimize the content before this compression occurs, maintaining visual fidelity even through aggressive platform compression.

Environmental and Cost Benefits

The efficiency gains from AI enhancement have broader implications beyond just quality. Researchers estimate that global streaming generates more than 300 million tons of CO₂ annually, so shaving 20% bandwidth directly lowers energy use across data centers and last-mile networks. (Sima Labs)

AI video codecs shrink that data footprint by 22-40% while improving perceived quality - unlocking smoother playback and lower CDN invoices. (Sima Labs) This dual benefit of cost reduction and environmental impact makes AI-enhanced MP4 an attractive option for organizations looking to optimize their streaming operations.

The Competition: Why Newer Codecs Haven't Displaced MP4

AV1 and VVC Adoption Challenges

While newer codecs like AV1 and VVC offer superior compression ratios, their adoption faces significant hurdles. Streaming video consumption on mobile devices, particularly smartphones, has led to increased activity around mobile codecs, with new releases of VVC and AV2 expected in the next 2 years. (The Broadcast Bridge) However, hardware support remains limited, and encoding complexity is significantly higher than MP4.

The battle of the codecs continues, but AI may disrupt the field by significantly improving compression efficiency and quality enhancement for existing formats. (The Broadcast Bridge) This disruption means that MP4, enhanced with AI preprocessing, can compete effectively with newer codecs without requiring the massive infrastructure changes that full codec migration would demand.

Platform Standardization Inertia

Major platforms have invested heavily in MP4-based infrastructure. Instagram may compress videos to optimize for mobile viewing, but this compression is built around H.264/H.265 pipelines that have been refined over years. (Sima Labs) Changing these systems would require massive engineering efforts and risk introducing compatibility issues.

At NAB 2024, AI applications for video saw increased momentum, with practical applications including AI-powered encoding optimization, Super Resolution upscaling, automatic subtitling and translations, and generative AI video descriptions and summarizations. (Bitmovin) These innovations are being built on top of existing MP4 infrastructure rather than requiring complete format changes.

Industry Validation and Benchmarking

Proven Performance Metrics

The effectiveness of AI-enhanced MP4 has been validated through rigorous testing. SimaBit has been benchmarked on Netflix Open Content, YouTube UGC, and the OpenVid-1M GenAI video set, with verification via VMAF/SSIM metrics and golden-eye subjective studies. (Sima Labs) Netflix's tech team popularized VMAF as a gold-standard metric for streaming quality, and these benchmarks demonstrate that AI preprocessing can significantly improve MP4 performance. (Sima Labs)

The ability to compress video while maintaining quality and reducing bandwidth is critical to the business of streaming. (IBC) AI preprocessing engines like SimaBit prove that this can be achieved without abandoning existing MP4 infrastructure.

Real-World Implementation

Companies are successfully implementing AI-enhanced MP4 solutions in production environments. Midjourney's own settings, social-media upload rules, and Sima Labs' SimaBit AI pre-processing engine can be combined to preserve AI-generated video fidelity. (Sima Labs) This practical application demonstrates that the technology works in real-world scenarios, not just laboratory conditions.

The patent-filed AI preprocessing technology trims bandwidth ≥ 22% on Netflix Open Content, YouTube UGC, and the OpenVid-1M GenAI set - without touching existing pipelines. (Sima Labs) This seamless integration is crucial for organizations that cannot afford downtime or workflow disruptions.

Future-Proofing MP4 with AI Innovation

Continuous Improvement Through Machine Learning

AI enhancement represents a paradigm shift in how we approach video optimization. Rather than waiting for new codec standards to be developed, ratified, and adopted, AI preprocessing can continuously improve through machine learning updates. (Bitmovin) This means that MP4's performance can keep improving without requiring hardware or infrastructure changes.

Generative AI is disrupting the codec field by significantly improving compression efficiency and quality enhancement. (The Broadcast Bridge) This disruption benefits established formats like MP4 more than newer codecs because the AI improvements can be applied immediately to existing infrastructure.

Scalable Solutions for Growing Demand

As video content continues to grow exponentially, the scalability of optimization solutions becomes crucial. AI preprocessing engines can be deployed at scale without requiring device-level changes, making them ideal for addressing the massive volumes of content being created and consumed daily. (Sima Labs)

The combination of MP4's established infrastructure and AI enhancement creates a powerful solution for the streaming industry's evolving needs. Rather than forcing a complete technology transition, this approach allows organizations to incrementally improve their video delivery while maintaining compatibility with existing systems.

Conclusion

MP4's continued dominance in 2025 isn't just about legacy infrastructure - it's about a format that has evolved to meet modern demands. The combination of universal hardware decode support, seamless CMAF integration, and mature DRM ecosystems creates a foundation that newer codecs struggle to match. (Pixflow)

What's truly extending MP4's reign is the integration of AI preprocessing technologies like Sima Labs' SimaBit, which reduce bandwidth requirements by 22% or more while maintaining quality. (Sima Labs) This approach allows organizations to extract significantly more value from their existing MP4 infrastructure without the massive costs and risks associated with codec migration.

As the streaming industry continues to grow and face new challenges - from AI-generated content to environmental concerns - MP4 enhanced with AI preprocessing offers a practical, scalable solution. (Sima Labs) Rather than waiting for the next codec revolution, the industry is finding that the evolution of existing formats through AI innovation provides immediate benefits with minimal disruption.

The future of video streaming may not require abandoning MP4 - it may simply require making it smarter. (IBC)

Frequently Asked Questions

Why does MP4 continue to dominate video streaming despite being over 20 years old?

MP4's dominance stems from three critical factors: universal hardware decode support across all devices, seamless CMAF integration for adaptive streaming, and a mature DRM ecosystem. While newer codecs like AV1 and VVC offer better compression, MP4's widespread compatibility and established infrastructure make it the most reliable choice for content creators and streaming platforms.

How do newer codecs like AV1 and VVC compare to MP4 in terms of adoption?

Despite AV1 and VVC offering superior compression efficiency, their adoption remains limited due to hardware decode challenges and compatibility issues. Mobile devices, which account for the majority of streaming consumption, still rely heavily on MP4's universal hardware support. The "battle of the codecs" continues, but MP4's established ecosystem gives it a significant advantage in practical deployment.

What role does AI play in extending MP4's relevance in modern streaming?

AI preprocessing technologies are revolutionizing MP4's efficiency without requiring codec changes. Companies like Sima Labs have developed solutions that can reduce bandwidth by up to 22% while maintaining video quality. This AI-powered approach allows MP4 to compete with newer codecs by improving compression performance through intelligent preprocessing rather than hardware-intensive codec upgrades.

How does CMAF integration benefit MP4 in streaming applications?

CMAF (Common Media Application Format) integration allows MP4 to deliver adaptive bitrate streaming efficiently across multiple platforms. This seamless integration enables content providers to serve the same MP4 files to different devices and platforms while maintaining optimal quality and reducing storage costs. The mature CMAF ecosystem around MP4 makes it the preferred choice for large-scale streaming operations.

What makes MP4's DRM ecosystem more mature than newer codec alternatives?

MP4 benefits from decades of DRM development and integration with major content protection systems like Widevine, PlayReady, and FairPlay. This mature ecosystem provides robust security for premium content while maintaining compatibility across devices and platforms. Newer codecs are still developing their DRM capabilities, making MP4 the safer choice for content providers requiring strong copyright protection.

How can AI video preprocessing improve MP4 streaming quality and bandwidth efficiency?

AI video preprocessing technologies analyze and optimize video content before encoding, identifying areas where compression can be improved without quality loss. These solutions can reduce bandwidth requirements by 20-25% while maintaining visual quality, effectively extending MP4's competitive lifespan. This approach allows streaming services to leverage AI improvements while maintaining compatibility with existing MP4 infrastructure and hardware decode capabilities.

Sources

1. https://bitmovin.com/ai-video-research

2. https://help.skedsocial.com/en/articles/5777148-videos-look-washed-out-when-posting-to-instagram

3. https://pixflow.net/blog/the-creators-cheat-sheet-best-video-formats-codecs-for-social-media/

4. https://www.ibc.org/features/streamers-look-to-ai-to-crack-the-codec-code/11060.article

5. https://www.sima.live/blog/midjourney-ai-video-on-social-media-fixing-ai-video-quality

6. https://www.sima.live/blog/understanding-bandwidth-reduction-for-streaming-with-ai-video-codec

7. https://www.thebroadcastbridge.com/content/entry/21058/mobile-codecs-the-battle-of-the-codecs-continues-but-ai-may-disrupt-the-fie