Peryn @perynai

Maximize your GPU yield. Serve inference. Earn $PRL. Same compute, paid twice. Built for neoclouds, inference providers and miners. peryn.ai Joined October 2026

Tweets

15
Followers

242
Following

29
Likes

44

Peryn @perynai

4 days ago

Our Pearl FP8 miner on Hopper is now within 2% of the hardware's theoretical limit under Pearl's mining rules. 29% faster than Pearl's open-source miner. Even faster than NVIDIA's cuBLASLt on mining workloads. And it runs alongside live inference, delivering over 50% of its full mining hashrate during prefill-heavy serving with zero loss in inference throughput.

6 10 84 13K 27

View Details

Peryn @perynai

6 days ago

FP8 fork will transform Pearl mining. We've built the world's most efficient duplex mining infrastructure for clouds. Serve inference, secure Pearl, earn pearl-2:native. All with the same compute. AI unit economics will never be the same. x.com/aliomerhorzum/…

Ali Ömer Horzum @aliomerhorzum

a week ago

x.com/i/article/2110…

0 4 36 3K 17

1 5 19 3K 8

View Details

Ali Ömer Horzum @aliomerhorzum

a week ago

x.com/i/article/2109…

7 4 32 5K 13

View Details

Pearl Safe @pearlsafewallet

2 weeks ago

Pearl Safe 1.1 is live on Google Play. bitcoin:native and zcash:native , next to pearl-2:native In one self-custody vault. Safe by design. Simple by nature.

9 4 35 3K 5

View Details

Latespoon @Latespoon

2 weeks ago

Dear $PRL enjoyers; please note that the copycat project Vearl (vearl.org) is NOT being developed by Idan Sugarman (Pearl Labs). This is a lie. It's a fake github account created yesterday. Thank you for your attention to this matter!

2 5 33 2K 0

View Details

Peryn @perynai

2 weeks ago

pearl-2:native miners, get ready to double your income. Same compute, paid twice. pearl-2:native 矿工们，准备好让收入翻倍吧。同一份算力，两份收益。

3 4 13 927 2

View Details

Peryn @perynai

2 weeks ago

$17B a year to mine math nobody needed. $700B a year on GPUs for AI. Pearl made it one computation. Peryn makes it pay twice. peryn.ai

0 1 3 77 1

View Details

Peryn @perynai

2 weeks ago

Marketplaces & enterprises: wholesale AI capacity, mining-subsidized. → Volume pricing → Choose where requests run → Private deployments, never mined [email protected]

1 0 3 90 0

View Details

Peryn @perynai

2 weeks ago

Bitcoin miners earned $17B last year doing math nobody needed. AI data centers are spending $700B this year on GPUs. Pearl (pearl-2:native) made them the same thing: the AI work is the mining. We built the rails between them. This is Peryn. 🧵

1 3 9 1K 1

View Details

Pearl Research Labs @prlnet

7 months ago

It is becoming increasingly clear that the future economy will be denominated in compute cycles more than in human labor. In a world where AI drives the majority of electricity consumption and GDP, compute is the natural collateral for money: an open, auditable, AI-native currency, produced directly through inference and training. Since the inception of Bitcoin, an outstanding open problem in distributed systems was whether it is possible to implement Proof-of-Work consensus on top of real-world computation, as opposed to useless random hashing. While long considered impossible, last year we answered this question affirmatively. Pearl’s mathematical breakthrough enables every GPU cycle powering AI systems to simultaneously produce a native digital currency: ¶PRL. What this means is that the hundreds-of-billions (and soon trillions) of dollars of compute being deployed for AI workloads will double--for effectively free--to secure Pearl's Proof-of-Work chain; All the properties of Bitcoin, but secured as the by-product of AI inference and training, i.e., by the native operation of GPUs: matrix-multiplication (GEMM). Pearl changes the unit economics of LLMs, which are are fundamentally non-fungible, and will shift a portion of the wealth generated by AI back to users – who drive production, model improvement and demand, yet currently capture none of the upside of the AI era. We’ve spent the last year turning this “2-for-1” breakthrough into a working infrastructure, building from the linear algebra down to the CUDA kernels, alongside world-class mathematicians and low-level engineers. Today, we’re excited to announce that the Pearl Network is ready, and will soon support state-of-the-art LLM serving, through vLLM and SGLang plugins. Running AI workloads on Pearl transforms AI compute from a sunk expense into an AI-native asset, anchored directly to the production of intelligence. If you’re interested/skeptic or ideally both – we’ve published our next tranche of open problems as a collaborative Polymath challenge – containing math, systems and economics questions we’re grappling with next. We invite you to tear it down, prove it or propose better implementations: pearlpolymath.com. #AIMoney #ProofOfInference