How New Smartphone Upgrades Could Cut Video Data Usage in Half

2026-10-09 companies

San Jose, Thursday, 8 October 2026.
Six major smartphone makers, controlling 62% of the global market, are adopting new video compression technology that cuts streaming data usage by up to 50%, dramatically lowering network costs.

Market Consolidation and Licensing

On 8 October 2026, Access Advance reported that six major smartphone brands are now licensees of the VVC Advance Patent Pool, representing a significant shift in the mobile hardware landscape [1]. These manufacturers—Honor, Huawei, OPPO, Samsung, Vivo, and Xiaomi—collectively account for approximately 62% of the global smartphone market, signaling a transition from early-adopter to early-majority phase for Versatile Video Coding (VVC) [1]. This consolidation resolves long-standing ecosystem interdependencies, allowing streaming providers to move toward mainstream deployment of the technology [1]. The Access Advance patent pool includes essential patents from nearly 50 licensors, providing a centralized mechanism that facilitates this rapid adoption across the industry [1].

Licensing Mechanisms

The VVC Advance Patent Pool currently contains over 6,000 patents, with recent additions from Samsung and Sharp bolstering the available volume for licensees [1]. Dylan Zhou, Executive Vice President and Head of Licensing Asia at Access Advance, noted that hardware-based encoding and decoding improve the practicality of deploying advanced codecs on consumer mobile devices [1]. This is particularly critical for smartphones where processing performance and power consumption are primary constraints [1]. If VVC-capable smartphones reach consumers in meaningful volumes by the end of 2026, the installed-base barrier constraining content deployment is expected to diminish rapidly [1].

Efficiency Metrics

Industry experts position VVC as the successor to High Efficiency Video Coding (HEVC), offering compression improvements that allow organizations to reduce data transport requirements significantly [2]. Aytac Biber, Director of Product Management at Qualcomm, stated that VVC can reduce bitrates by up to 50% over HEVC while maintaining equivalent video quality [5]. In parallel developments for AI infrastructure, Chips&Media launched a Data Compression IP on 6 October 2026 that achieved bandwidth reduction rates of 35.2% for FP16, 45.7% for BF16, and 53.5% for INT8 in testing [4]. The average bandwidth reduction across these data formats is 44.8 percent, highlighting the tangible efficiency gains available through hardware-level optimization [4].

Hardware Constraints

Despite the efficiency benefits, VVC requires significantly more compute power than previous standards, with estimates suggesting a 5–7x increase over HEVC [3]. This complexity leads to higher infrastructure costs for live operations unless hardware acceleration is utilized [3]. Eric Deniau, Senior Vice President of Research and Development at VITEC, emphasized that efficient silicon implementations can reduce energy consumption beyond the gains achieved through compression algorithms alone [2]. Consequently, the industry is treating energy efficiency as a key business metric and total cost of ownership factor rather than just a corporate social responsibility initiative [2].

Future Outlook

Smartphone manufacturers are preparing products with hardware-based VVC support in silicon, with commercial launches anticipated in the fourth quarter of 2026 [1]. Looking further ahead, Chips&Media intends to complete hardware implementation of its new compression IP by Q1 2027, expanding the roadmap to include static weight compression for large language models [4]. As AI-generated content and higher-resolution media drive global network traffic, these compression technologies serve as a strategic lever for managing infrastructure costs and energy consumption [2]. The objective remains to reduce energy consumption throughout the video lifecycle without limiting innovation or demand [2].

Sources

Semiconductor Technology Versatile Video Coding