GPU Temperatures Drop 22°C: Diamond Thermal Management Moves From Lab To AI Data Centers

On October 8, US thermal-management company Frore Systems launched LiquidJet Diamond, a liquid cold plate purpose-built for high-power GPUs in AI factories. The standout design: embedded in the bottom of the cold plate, directly above the GPU's hottest region, sits a 7 mm × 7 mm diamond wafer - acting like a tiny heat-spreading patch that first flattens the heat and then hands it off to the microchannel coolant below. The product is being read as a milestone moment for diamond thermal management moving from lab samples toward volume deployment in real data centers.

(LiquidJet Diamond Liquid cooled cooling plate)

1. How it works: spread the heat first, then carry it away

Heat in AI chips is not evenly distributed; it concentrates in a few extremely small regions, and conventional cold plates struggle with these "hot spots." Diamond's role is to use its exceptionally high in-plane thermal conductivity to turn a sharp point heat source into a flat surface source - shaving the peak heat-flux density before the coolant takes over.

Frore's existing LiquidJet cold plate already uses a 3D ultra-short-loop, multi-channel design that delivers coolant according to each GPU's power map, flushing hot spots first and the rest second. LiquidJet Diamond stacks a diamond heat-spreading sheet on top of the hot spots, forming a two-stage structure: diamond spreads the heat, microchannels then snatch it away.

2. The numbers: 16–22°C cooler, 35% better tokens per watt

The vendor's published figures are striking:

• Compared with conventional milled cold plates, heat-transfer efficiency rises by 75%;
• GPU temperature drops by 16–22°C overall;
• It can handle extreme hot spots up to 770 W/cm²;
• No change to chip packaging or existing liquid-cooling infrastructure is required for an upgrade.

On efficiency, the original LiquidJet already cut GPU core temperature by 12°C and improved tokens-per-watt by 25%. With the diamond sheet added, hot-spot temperature falls another ~10°C, pushing the tokens-per-watt improvement to 35%. The product has been customized for the NVIDIA GB300 platform and, according to the company, will also cover future Rubin Ultra and Feynman platforms. All of these figures come from the vendor's internal testing; real-world performance varies with accelerator model, water temperature and flow rate.

3. Who is Frore?

Frore Systems was founded in 2016 by two former Qualcomm engineers, initially building solid-state air-cooling solutions for consumer electronics. Public reports indicate that after NVIDIA CEO Jensen Huang saw a demo of the technology, he suggested the company pivot to liquid cooling. Frore subsequently bet fully on AI data-center thermal management, and closed a US$143 million Series D in March 2026 at a US$1.64 billion valuation. The company planned a live demonstration at the OCP Global Summit (October 12–16), showing LiquidJet Diamond cooling a 2,300 W NVIDIA Rubin GPU.

4. China's diamond thermal track is moving in parallel

While overseas products are reaching the market, domestic Chinese players are accelerating on the same track:

• Sugon Digital: the C8000 V3.0 megawatt-class phase-change immersion liquid-cooling rack is the first large-scale deployment of diamond–copper thermal material, dissipating more than 200 W/cm² with thermal conductivity up 80%.
• Worldia: has developed diamond–copper composites for cold-plate heat spreading and is currently sampling downstream customers.
• Huanghe Whirlwind: its self-developed diamond–silicon-carbide composite reaches a thermal conductivity above 700 W/(m·K), with a coefficient of thermal expansion closely matched to silicon substrates; its 8-inch diamond heat-sink production line went into operation in February 2026.
• Sifangda: CVD diamond heat spreaders have passed customer testing and received small-batch trial orders; the company is building a base with annual capacity of 25,000 heat spreaders.

Closing

From Frore's diamond cold plate to domestic diamond–copper and diamond–SiC composites, and from 8-inch heat-sink lines rolling off production to small-batch CVD orders, the diamond thermal track is crossing the key stretch from "sample testing" to "small-batch orders" to "real data-center deployment." As power density in AI chips keeps climbing, a superhard material once seen as an expensive laboratory curiosity is becoming a must-have component of AI compute infrastructure.

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Disclaimer: This article is adapted and rewritten from publicly available reports on the Chinese Internet, provided for industry reference only. The vendor performance figures cited herein come from Frore Systems' internal testing and public disclosures of the companies mentioned; real-world performance varies with application conditions. We make no representation as to their completeness, accuracy or timeliness, and this article does not constitute investment or procurement advice. For republication or citation, please contact huicetools and credit the original source.