Only index provider at NVIDIA’s GTC analyst Q&A, so of course I asked @JensenHuang about GPU residual values. 😆 His take: newer is better, but older GPUs matter when everything is sold out. He knows exactly what we do. Then he asked: “How did you get your data, and how can we help?” Surreal. 💚 Also love running into Alison!

Love @TMobile merch! Exciting partnership for @computeexchange :)

@computeexchange is hosting an event on Oct 28th, will be a cocktail party with some food I’ll be sharing more about it soon, but if you’re going to be in the city, and want to join us - send me a DM

Heading to Berlin next week for @NVIDIA GTC! Excited to join the Capital Providers Panel on October 22, 3:45–4:30 PM, to discuss GPU financing, compute markets, and how pricing transparency is shaping the future of AI infrastructure. See you in Berlin! Pin @josephcompute if you want to meet up for beers.

What a turnout at the Compute Trading Happy Hour for #SFTechWeek. 850+ people requested a spot and the Chotto Matte rooftop was packed. Thanks to everyone who came, and to @silicondata and @robotventures for hosting with us.

Buying is the cheaper path on paper. In practice, physical servers are scarce and lead times are long. Plenty of teams rent because they can't wait.

Come join us :)

We're hosting a panel at SF Tech Week on how compute and tokens actually get priced. Every Token Has a Price, Oct 7 in SF, co-hosted with @blank_vc and @silicondata. @carmenli moderates, with @radhikam24 , @svonava and @wAIeedatallah . Limited seats 👇 partiful.com/e/TCbzFycPMc8s5… #SFTechWeek

Sourcing compute has historically been slow Last night we had a large block of Blackwell GPUs hit our marketplace. Within hours, multiple qualified off-takers had placed bids We're working to make our platform the fastest way for you to acquire the compute your business needs

compute exchange is one of the reasons I got into this, we were not able to close business yet, but yes, I love the product

We see, hear, and live this everyday There are so many new entrants in the broker space, it’s too noisy and hard to know who’s legitimate That’s why we’re building a neutral marketplace that has validated supply and vetted buyers. Buyers and partners communicate directly with one another. No intermediaries If that resonates with you, use our platform for your next compute deal ✅

Join the event next week in SF and let's talk about compute.

So happy to have you on our team, Nick!

The institutional marketplace for compute procurement— independent, neutral, and purpose-built for professional market participants.

Today we're launching Live Inventory: a second way to buy GPU capacity. Providers post their clusters directly — model, count, location, term, price per GPU/hour, and go-live date. 31 clusters listed today: 32x H200, US Northwest, $2.81/GPU/hr, Sep 30 48x H100, Asia Pacific, $2.70, Nov 24 256x B200, Europe West, $4.68, Nov 30 72x B300, US, $3.95, Jan '27 1,152x GB300 NVL, US West, $6.50, Feb '27 Every listing comes from a verified provider, with transparent pricing and specs. Live now on the Compute Exchange Marketplace. Try it out: compute.exchange

the more I reread this post, the more I become convinced this is NVIDIA's manifesto of becoming the "central bank of compute." some thoughts on this econ model + nvidia's role: > econ101 tells us a central bank has several goals - (1) anchor inflation, (2) full employment/utilization, (3) lender of last resort. Commercial banks on the other hand "create money" in the economy by lending and thus increasing GDP > the loan in GPU financing world is datacenter buildout (of NVIDIA factories), the "GDP growth" is essentially token/inference spend. The primary "commercial banks" are neoclouds (Coreweave, Nebius et al.) that contract with the labs/inference platforms, which manufacture tokens and allow for "GDP growth". This is the first layer of compute. Lets call it C1. > in addition to directly "lending" to the giants as C1, wholesale compute can also get unbundled into PAYG/short-term duration markets. this is the whole "GPU marketplace layer" - the world of SF compute/Vast AI/compute exchange that sell bare metal. We can call this C2 > all the orderbooks on C1 and C2 can then get bundled into a bunch of synthetic financialization tools on the outside layer, which we can label as C3. Indexes, cash-settled exchanges, residual puts, insurance stuff all belong here. so why is nvidia a central bank? going back to econ101 - (1), the "inflation" in compute land is actually depreciation curves. NVIDIA can control the depreciation curve by deciding when to release a new series of chips (eg. Vera Rubin). (2) NVIDIA's goal is to enable full utilization in the economy of their GPUs (which spurs more demand + higher prices etc.) and so will let the financing stack go faster. (3) NVIDIA has the balance sheet and resources to "bail" failing neoclouds/marketplaces out that don't see the inference demand growth as the lender of last resort. this is where the 25% underwriting comes from.

Diffusion models are outrunning the infrastructure that serves them. So we're partnering with @tensorwave and @DecartAI to dig into the gap. AI Research Paper Club #002 brings together a technical crowd around what's next for diffusion and multimodal models — training costs, inference latency, and the architecture decisions that are still genuinely open.