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Seagate Mozaic 4+ Hits 44TB HDD Record

Seagate Mozaic 4+ Hits 44TB HDD Record
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💡44TB HAMR HDD breaks records, powers AI data center scale-up

⚡ 30-Second TL;DR

What Changed

Mozaic 4+ certified by two hyperscale cloud providers for production.

Why It Matters

This capacity leap reduces storage costs for massive AI datasets in cloud environments. Hyperscalers can now scale exabyte-class AI training infrastructure more efficiently.

What To Do Next

Benchmark Mozaic 4+ against current HDDs for your next AI data center procurement.

Who should care:Enterprise & Security Teams

Key Points

  • Mozaic 4+ certified by two hyperscale cloud providers for production.
  • 44TB capacity record from 10 platters at 4+TB per platter.
  • Features vertical photonics integration and new cantilever architecture.
  • Improved SoC enhances density while preserving reliability.

🧠 Deep Insight

Background and context from public sources — not the original article. 9 sources cited.

🔑 Enhanced Key Takeaways

  • An unnamed hyperscaler is deploying Mozaic 4+ at scale, marking the industry's first HAMR-based platform in volume production.[1]
  • Mozaic 4+ delivers 47% infrastructure efficiency improvement in a 1-exabyte deployment versus 30TB drives, reducing data center footprint by 100 sq ft and saving 0.8 million kWh annually.[1]
  • Seagate plans to advance from 4TB per platter to 10TB per platter, targeting up to 100TB drive capacities.[1]

🔮 Future ImplicationsAI analysis grounded in cited sources

HAMR drives will reduce data center energy costs by up to 0.8 million kWh per exabyte annually
Mozaic 4+ achieves this through 47% efficiency gains over 30TB drives in hyperscale deployments.[1]
Seagate will ship 100TB HAMR drives by late 2020s
Roadmap targets 10TB per platter from current 4TB, enabling 100TB capacities with multi-platter designs.[1]

Timeline

2024-01
Unveiled Exos Mozaic 3+ with 30TB+ HAMR drives
2025-11
Launched Exos 4U100/4U74 JBOD systems supporting Mozaic HAMR
2026-03
Released Mozaic 4+ with 44TB capacities shipping to hyperscalers
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Original source: IT之家

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