Gelsinger-backed Nagare Labs’ Z2RAM promises SRAM speed at DRAM density
- ID
- 43763
- Status
- summarized
- Published
- 06 Nov 2026, 7:00 PM
- Fetched
- 06 Nov 2026, 8:26 PM
- Provider
- Tom's Hardware
- Category
- technology
- Original URL
- https://www.tomshardware.com/tech-industry/semiconductors/gelsinger-backed-nagare-labs-capacitorless-z2ram-promises-sram-speed-with-dram-density-latest-published-cell-retains-data-for-over-300-seconds-at-85-c-but-further-figures-are-projected
- Source URL
- https://www.tomshardware.com/feeds/all
Summary
- Score
- 3.0
- Created
- 06 Nov 2026, 8:26 PM
- Tags
- Audience
- developersai_ml_learners
What happened
Nagare Labs, a Georgia Tech spinout backed by Pat Gelsinger, published cell data for its capacitorless Z2RAM claiming SRAM-class speed at DRAM density, with a cell that holds data for over 300 seconds at 85°C — up from 0.1 seconds in the founders' earlier papers. Testing stops at 85°C, and the headline specs are projections: Gen 1 is claimed at 5x SRAM density via six stacked layers, 14x DRAM speed, and 3x lower read energy than SRAM, pitched as memory stacked directly on AI chips to relieve HBM bandwidth and yield pressure.
Why it matters
The only measured number here is retention (300+ seconds at 85°C); the 5x/14x/3x figures are projections with no endurance, write-energy, or above-85°C data disclosed. If you are sizing AI inference or training infrastructure, do not plan around Z2RAM — nothing is in production, priced, or dated, and HBM remains the near-term constraint on accelerator bandwidth.
Discussion angle
Which number would actually change your hardware plans — the 300-second retention at 85°C, or the projected 14x DRAM speed — and what missing data (endurance cycles, write energy, behavior above 85°C, stacking yield) would you need before taking a capacitorless cell seriously for AI accelerators?