Compute Capital Markets with Lucas Tcheyan

Summary

Galaxy Brains — "Compute Capital Markets with Lucas Tcheyan"

Podcast: Galaxy Brains / Galaxy Digital Research
Episode Date: July 16, 2026
Host: Alex Thorn
Guests: Bimnet Abibi (Galaxy Trading), Lucas Tcheyan (VP of Research, Galaxy)
Main Theme: The financialization of compute resources (especially GPUs) at the intersection of AI and crypto; the emergence of capital markets for AI inference and related products; and a macro market update touching on rates, inflation, hardware, and crypto asset behavior.

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Episode Overview

This episode revolves around two core discussions:

1. Macroeconomic and Crypto Markets Update:
   Alex Thorn and Bimnet Abibi analyze recent inflation and rate data, the impact of energy/geopolitical events, sector rotations in equities (particularly tech and AI hardware), and the current dynamics in crypto (emphasizing Bitcoin performance and ETF flows).

2. The Rise of Compute Capital Markets:
   Alex interviews Lucas Tcheyan about his new Galaxy Research report, "Inference Capital Markets." They explore how markets are emerging around compute resources (GPUs), both off-chain (TradFi) and on-chain (crypto/DeFi), considering tokenization of GPU hours, futures products, and innovative financial primitives tied to AI inference.

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Key Discussion Points & Insights

1. Macro Update: Inflation, Rates, Energy, and Tech (01:46–19:17)

U.S. Inflation and Fed Outlook ([02:24]–[04:51])

• Recent Data: Headline CPI declined by 0.4% MoM (first decline all year); PPI also came in soft ([02:24]).
• Rate Market Reaction: Odds of July Fed hike fall to near zero; September repriced to 50/50 ([03:05]), but further hikes still expected late 2026.
• Caution on Extrapolation:
  • “One data print should be viewed in the context of what we’ve been doing for the past six months. … The market is probably a little too optimistic right now in terms of inflation.” — Bimnet ([04:22])
  • Warning against relying on one soft number; points to continued inflation risk from capex surge and energy prices.

Energy Prices and Geopolitics ([04:51]–[07:23])

• Surge in Oil/Diesel: Energy prices rising sharply since June, with diesel near prior highs and inventories low ([05:22]–[06:12]).
• Geopolitical Risks: Ongoing Middle East (Strait of Hormuz) and Ukraine/Russia tensions could further constrain supply and fuel inflation ([06:22]–[07:18]).
  • “The risk is for a really prolonged process… every day that passes is less stuff that flows through the strait and commodities are a function of demand and supply.” — Bimnet ([07:18])

Equity Markets: AI Hardware, Sector Rotation, and Volatility ([07:23]–[13:13])

• AI Hardware Drives Rotation:
  • Market frenzy in memory/CPU stocks and hardware over software, as companies hedge against future price hikes ([08:43]).
  • “Part of the rally has been driven by AI hardware. Some of the most popular names are the memory names.” — Bimnet ([10:54])
  • Price spikes being felt tangibly: “Apple announced $200+ price increases… Most of these companies are following suit.” ([09:02])
• International Equities: Korean Kospi’s wild volatility linked to levered ETFs ([12:40]–[13:13]).
• Advice: “Caution is definitely warranted if you’re trying to play these equity rotation themes. You have to be nimble.” ([13:13])

Bitcoin & Crypto Market Dynamics ([13:13]–[19:17])

• BTC Recovery & Seller Exhaustion:
  • "Death flywheel" risk from MSTR removed; seller exhaustion noted as a support for current price action ([13:54]).
  • “If you hadn’t sold by the time you got to 58, 59, 60, you’re probably not going to sell anytime soon.” ([13:54])
  • ETF outflows abating; market grinding higher.
• Range-bound Expectations:
  • Support at 58–60k seems durable, absent new major catalysts ([15:31]); expect sideways or grinding action rather than strong rallies unless clarity emerges.
  • “The only real catalyst for bitcoin in the next 30–90 days is clarity.” ([17:02])
• Speculation vs. Store of Value:
  • Shift in market sentiment towards highly speculative assets (100x perps, prediction markets) over traditional ‘store of value’ narratives for gold/bitcoin ([19:17]).
  • “People want speculative assets, not fundamentally store value assets… [now] that’s just the moment we’re in.” — Alex ([19:17])

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2. Compute Capital Markets & the Financialization of AI (20:53–42:59)

Setting the Stage: The New Report ([21:47]–[22:03])

• Lucas Tcheyan’s Report:
  • "Inference Capital Markets" surveys the emergence of financial primitives/practices for AI compute—especially GPUs—both off-chain and on-chain.
  • Build-up parallels seen between crypto innovation and adoption in TradFi markets ([22:03]): “Crypto is always a really good place for frontier markets to emerge. If those frontier markets are successful, they usually get adopted in the tradfi world.”

GPU Market Financialization: Mechanisms & Challenges ([23:21]–[29:32])

• Tokenized GPU Hours:
  • On-chain and off-chain attempts to create spot and indexed markets for GPU rental hours ([23:37]):
    • “The primary ones… are basically tokenizing actual like GPU hours.” ([23:54])
    • Indices aggregate rental prices across providers but face fungibility challenges due to differences in GPU specs, location, and connectivity ([24:56]).
• Liquidity and Delivery:
  • Market still largely OTC with spot markets available but thin; futures are cash-settled for now ([25:25])
    • “Most of the actual deals are not happening... just happening OTC.” ([27:05])
• Adoption & Demand:
  • Big-tech (MAG7, hyperscalers) dominate long-term contracts, but persistent spot markets expected for excess capacity ([28:03]).
  • Key question: Will true hedging (as opposed to speculation) develop as a market use-case? ([28:53])
• Counterintuitive Pricing:
  • Contrary to expectations, legacy GPUs have held or gained value due to supply constraints—a dynamic familiar to Bitcoin miners ([29:02]–[30:14]).

The Tokenization of Inference and AI Usage ([30:42]–[37:59])

• AI “Tokens” as Financial Primitives:
  • New forms of “tokenization” in AI represent both model usage tokens (not crypto) and “inference access” tokens:
    • E.g., Venice’s “diem” token grants users $1/day inference credits on their platform ([31:32]–[33:51])
    • “It’s like a gift card of inference.” — Alex ([32:58])
• Financial Engineering Implications:
  • Diem resembles an access perpetual but means holding the token exposes users to price risk; only part of daily allocation is actually used (suggesting a speculative/financial, not just utilitarian, role) ([35:49]).
  • Secondaries and resale markets for inference credits are appearing; composability in DeFi could allow for lending against or monetizing unused credits ([36:33]).
    • “You have diem… you can go onto a platform and you can resell your inference you have through diem on that platform and recoup some of those costs, hold diem, but resell the inference hours…” — Lucas ([36:17])

GPU-backed Loans & Financialization Layers ([37:59]–[41:31])

• GPU as Collateral — RWA Analog:
  • Crypto platforms are beginning to extend loans collateralized by physical GPUs, mirroring the rise of real-world asset (RWA) markets in DeFi ([39:16]):
    • “We have this great product, a stablecoin and we have a global audience… We’re going to lend to these GPU markets.” ([39:59])
  • Growth here is likely to benefit from increasingly liquid/transparent GPU price indices and futures ([40:32]).
• Potential Dominance in Financial Primitives:
  • Crypto may not “win” the core model or application layer of AI, but could dominate the financialization layer by enabling composable liquidity, lending, and marketplaces ([41:31]):
    • “I think you would want to see… big lending markets [like Morpho or AAVE] being huge sources for people to borrow against GPUs… and to be able to borrow against tokens and stuff.” ([41:37])

The Future: Token Subsidized Inference & On-chain Frontiers ([42:00]–[42:51])

• “Tokenizing inference production,” analogous to Bitcoin mining: “If you provide inference, you get a reward… that token subsidy pushes down the price of inference… drives demand.” — Lucas ([42:51])
• Frontier production/mining models may further reduce costs and deepen these markets.

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Notable Quotes & Memorable Moments

• On Market Over-optimism:

  • “The market is probably a little too optimistic right now in terms of the inflation.” [Bimnet, 04:22]

• Hardware Price Inflation:

  • “Apple announced $200+ price increases on a bunch of different stuff. … That AI spend is going to cause like real inflation.” [Bimnet, 09:02]

• BTC Market Psychology:

  • “If you hadn’t sold by the time you got to 58, 59, 60, you’re probably not going to sell anytime soon. So you got to a seller exhaustion point.” [Bimnet, 13:54]

• Tools for the Coming Era:

  • “Crypto is always a really good place for frontier markets to emerge. If those frontier markets are successful, they usually get adopted in the tradfi world.” [Lucas, 22:03]

• Tokenized AI Access:

  • “They have a specific product basically where you can buy a token called diem. And what that does is a crypto token… it gives you access to $1 of inference on their platform perpetually.” [Lucas, 32:30]

• On Lending and Secondary Markets:

  • “You have diem… but you now know for the next week you don't need to use that diem. … You can resell your inference through diem on that platform and recoup some of those costs.” [Lucas, 36:17]

• Frontier Market Emergence:

  • “Because the composability of the ledgers are so composable.” — Alex ([36:59])
  • “I think in two to three years you see [these types of financialization] really emerge.” — Lucas ([41:37])

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Important Segment Timestamps

• 01:46 — Macro update begins with Bimnet Abibi: inflation, Fed rates, energy
• 06:22 — Middle East/Ukraine geo risk and energy inflation
• 08:43 — AI hardware, supply chain shocks, and tech sector rotations
• 13:13 — Bitcoin market structure, MSTR, ETF flows, range-bound outlook
• 20:53 — Transition to Lucas Tcheyan and the AI compute capital markets discussion
• 22:03 — High-level overview of Inference Capital Markets report
• 23:37 — How GPUs (hours, futures, spot) are being financialized
• 31:32 — Inference access tokenization (Venice and “diem”)
• 35:49 — Resale, lending, and DeFi market for AI inference tokens
• 39:16 — GPU-backed loans and RWA parallels
• 41:31 — Crypto’s opportunity to lead in financial primitives for AI compute
• 42:51 — The Bitcoin mining analogy for inference production tokenization

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Summary & Takeaways

• Macro Uncertainty Remains: Despite a soft CPI print, inflationary pressures (energy, capex, geopolitics) persist. Markets remain reactive and possibly over-optimistic.
• AI Hardware—New Asset Class: Surging demand and constrained supply for GPUs/memory has created price spikes, volatility, and the emergence of financialization in what were formerly pure commodities/operating costs.
• Emerging Computation Markets: Crypto-native and TradFi worlds are both moving toward standardizing, tokenizing, and trading GPU capacity, with secondary markets and derivative products in early-stage development.
• On-chain Innovation Advantage: Crypto primitives (tokens representing compute/inference, speculative and utilitarian, secondary markets for “credits,” lending against GPU assets, etc.) are forming the first truly global, programmatic compute capital markets. If the pattern holds, these approaches could become standard TradFi tools for AI.
• No “Winner” Declared, but Crypto as Financial Rails: While crypto may not control the AI model/application layer, it’s poised to become the settlement and financialization rails for AI resource markets—if it succeeds in liquidity, risk, and adoption.

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This episode is a dense, forward-looking tour of both near-term and long-term intersections between macro drivers, crypto/AI infrastructure, and the marketplace of compute. It provides a layered view into the emerging world where GPUs, tokens, and financial products become the oil, money, and markets of AI’s future.

Transcript

[A]

Welcome to Galaxy Brains. An infinite amount of cash. Cash. I'm your host, Alex Thorne. The US banking system is sound and resilient. Bitcoin made a new all time high. If you're not long.

[B]

If you're not long, you're short. Satoshi is going to come on there, laugh hysterically. Go quiet. All bitcoin's gonna be erased.

[C]

Bitcoin. Bitcoin's the best crypto.

[B]

Bitcoin is going to zero.

[A]

Welcome back to Galaxy Brains. As always, I'm your host, Alex Thorne, head of firmwide research at Galaxy. Bitcoin not zero. We have a great episode for you this week. Lucas Chayan, VP of research at Galaxy, is our guest. He just published a great report called Inference Capital Markets about developments in the financialization of AI, some of it involving crypto. Plenty of it. Not. It's a very interesting, comprehensive report and we'll get into it with Lucas and of course we'll check in with our good friend Ben Bimnet, a BB from Galaxy Trading. As always, talk about soft inflation numbers, what the impact on equity markets and rate expectations might be. Bitcoin's rally to about 65k as we record this. Is it durable? What do we expect over the next coming months from this moment? Before we get to any of that, I need to remind you to please refer to the link to the disclaimer in the podcast notes. And note that none of the information in this podcast constitutes investment advice or an offer, recommendation or solicitation by Galaxy or any of its affiliates to buy or sell any securities. We had a good vacation. I hope you had some time off over the July 4th holiday. America, 250. We're ever flawed but ever striving for more in America and you know, happy birthday, America. Right, Finneas, let's hop right into it with Bimnet ab. Let's go now to our friend Bimnet Abibi from Galaxy Trading. As always, Bimnet, welcome to Galaxy Brains.

[B]

Thanks for having me.

[A]

It's been a few weeks. I was off last week. We did no episode and the week before you were off and I did a solo episode. So it's been, I guess. What would that make it, Phineas? Like the last week of June, I think was the last time we talked here. Has a lot happened. A couple things have happened. Right. We're talking about CPI numbers, came in soft. We're talking about its impact, I think, on Fed rate expectations. Yeah, a little bit about bitcoin. The block clock is offline right now. We're gonna get it fixed up but you know we're like the 65k zone. I don't know if is that, that's a rally from the low, but absolutely. And then let's talk a little bit about the equity markets. But let's start with CPI.

[B]

That was yesterday headline CPI declined by 0.4 month on month. That was the first decline all year.

[A]

Basically the decline in the growth.

[B]

No, it was, it was negative. The headline number. Yeah, the core number was unchanged and you had PPI come out today. That was also a bit on the softer side. So you repriced the July meeting from like a high of like 1213 basis points break then almost 50, 50 for the July meeting to effectively like 2 1/2 basis points now no hike, no hike in July. And then the September meeting got repriced from you know, call it a full hike to a 5050 chance and then

[A]

the rest of the back half of the year, the end of the year is still hiking.

[B]

Still hiking.

[A]

Yeah.

[B]

And I think that is appropriate in terms of a reaction to the inflation data that you.

[A]

Little bit less urgency to hike rates to tamper inflation a little bit less.

[B]

In my head the market really should be focused on is not backward looking data but what the forward looks like. And energy prices since June 30, which is the period that the inflation figures cover is up a lot. You've gone from $70 or $68.69 at the end of June and in WTI to 80 and you have this Middle east conflict resuming. And in theory the traffic through the Strait of Hormuz is still well off the pre war levels. And so there is still the risk of a greater inflationary impulse that the market needs to consider. And at the same time one data print, it does not establish a trend. One data print should be viewed in the context of what we've been doing for the past six months. And in theory inflation was above target for every single print except this one. And so I think the market is probably a little too optimistic right now in terms of like the inflation.

[A]

They're reacting to just this one data point. You. So you're.

[B]

It sounds like and, and a slightly more dovish war since. Since fomc.

[A]

Yeah but you're sort of saying like, you know, if you got like July and August, maybe we're a little soft too, then you might be able to start say wow, maybe it really isn't maybe that the new. Maybe there's a new trend of softening.

[B]

Correct.

[A]

But we really aren't at that point in your mind yet?

[B]

I, I, I just don't think so. And you know, like, like there's some really huge components of, of inflation that are moving, you know, in good directions. Like she, but at the same time like we have one of the largest capex moments in the entirety of like American history happening right now. These guys are spending on everything from generators to wiring to services, electricians, plumbers,

[A]

like you know, less plumbers, like excavators literally. There's a lot of building going on

[B]

and there's a lot more building coming.

[A]

Yeah.

[B]

And so that's an inflationary impulse. And the question is, you know, when do you get that inflationary impulse? And then you also just have, you know, refined energy products that are trading at really elevated levels. Like take a look at like diesel prices. Like diesel is, is very close to like the war highs.

[A]

Yeah.

[B]

And you know, inventory levels are also very low across, you know, less, you know, SBIR is pretty filling it up

[A]

a little, it looked like. Right. But it's, it's, they got pretty low.

[B]

I don't know if they've started filming but it's, yeah, the reserves, reserves are low.

[A]

So what we've been leading a little bit in order to sort of buttress the increased gas prices basically is what was happening.

[C]

Yes.

[A]

Yeah, a lot.

[B]

Not, not a little. And then you also just have like, you know, an escalation in the Ukraine, Russia situation where there's specifically targeting container ships as well as refining sites. And so refining capacity is decreasing, not increasing. And who knows about the Iran Middle east tensions. I'm still optimistic about the left tail scenario not happening. I think all out kinetic warfare. The entire region still feels like jockeying

[A]

now more than a full re escalation.

[B]

Correct. And I would place the odds of that type of left tail scenario are probably sub 10%. But I think there's a really high chance that the negotiating period is a lot longer than the 60 day potential

[A]

longer term low grade simmer that hangs over markets.

[B]

Correct. And every day that passes is less stuff that flows through the strait. And commodities are a function of demand and supply and if there's just no supply, the prices are going to go up unless demand goes down. And so what I think that the market isn't really fully appreciating is just how drawn out this negotiation process is going to be. In theory, the first 30 days were meant to establish freedom of navigation and the following 30 days were meant to establish the nuclear stuff. And right now you haven't Done the freedom of navigation stuff. And so I just think the way that these two, the US and Iran are going is your risk is for a really prolonged process. And so I think the market's kind of under appreciating that. And then you've had some other kind of themes pop up here and there in equities that have caused a ton of rotation. Yesterday IBM was down like 25, 25%. Yeah, correct. And effectively, you know, what they highlighted in their earnings was companies are spending on hardware and not enterprise software because they're more concerned with the prices of the hardware shooting higher.

[A]

So they're buying what, memory, hard drives, servers and servers because they just think the forward pricing is going to be so bad and they.

[B]

Yeah, and there's a supply constraint as well.

[A]

This is, this kind of like, this is a little like, you know, retail and personal, but like when the new iPhones come out or the new Samsungs, are they gonna be way more expensive?

[B]

They are, yeah. New anything that requires memory, from your Xbox, your PlayStation to your phone, iPad, et cetera. And you're talking about like Apple announced like $200 plus price increases on a bunch of different stuff. Yeah, they already did. And most of these companies are following suit. And so yeah, that supply, that AI spend is gonna cause like real inflation.

[A]

That's gonna cause. Yeah, I was gonna say that's, you know, it's only, you know, people don't buy a phone every day. Right. But pretty much everyone buys in some form or another, whether on a plan or whatever, a phone every two years, two, three years. Most people, depending on what part of

[B]

the world you're in.

[A]

So like that's going to be one that people see. They're going to feel even if by it's going to trickle, right? They're going to say, oh my God, I got to spend so much more on my phone now. Like, yeah, maybe I'll cut back in other places too.

[B]

But it's also basic things like polyethylene is used to make a bunch of like plastics. Right. Like the, the food that you eat is transported on diesel trucks.

[A]

I'm sure there's some oil, some plastics made with oil in like the Lulu, the stretchy clothes.

[B]

Right, Absolutely. You know, and a ton of different stuff. And so like, I think that that's probably the risk that that is most underappreciated by the market, which is just like a prolonged negotiating process, just petroleum prices. And just think about like how long most of these types of things take.

[A]

Yeah, yeah, right.

[B]

Like negotiations to like end war. Like don't really aren't supposed to take 60 days. Like I don't know how long the original nuclear deal took, but I'm guessing

[A]

you mean with Obama.

[B]

With Obama that was like at least a six month process.

[A]

Yeah, probably behind the scenes. I forget who he had minimum. Yeah, like I think they were negotiating privately for a while for super long time.

[B]

And now there are missiles flying. Yeah, right. People dying.

[A]

Like it really doesn't help negotiations.

[B]

I mean maybe that's the, you know, and so, you know, so cautious.

[A]

But stocks, you said they're back near highs.

[B]

Yeah, I mean you're talking about like the indexes, the indices are trading at you know, very elevated levels. You know I, it's tough to make a call one way or the other on them right now, but I think the story is really underneath the hood. And you know, I was talking to like a strategist out of Asia the other day and he brought up an interesting point. Part of the rally has been driven by AI hardware. Some of the most popular names are the memory names as we talked about. And he came back to Nvidia analogy where two years ago in Nvidia everybody discovered the story. If you look at the Nvidia chart once it had this crazy parabolic move, it spent a really long time doing absolutely nothing simply because everybody already found out about the story. You already had this huge glut of speculation, et cetera in the name. You're at the point now where everyone knows the story, some of the valuations have caught up to the story, but nobody's hearing it for the first time. And so given that lack of discovery element, that new catalyst discovery, it might be a period where you go sideways for a while, particularly in some of these high flying memory names or high flying CPU names like Dell's off 13% today, Marvel technologies like Hewlett Packard, all these guys that got this huge boost. People didn't know the stories. Now people do. And then at the same time, you know, the, the coast be price action over the past handful of weeks, like over the last month has been absolutely insane.

[A]

This is Korea, right?

[B]

Korea, yeah. Like you had, you were quoting the figure.

[A]

Something was like a million margin accounts were like called on like over the weekend because of the, I mean they had huge moves higher than they had big corrections and it's been very volatile, very volatile.

[B]

And part of that is just a market structure where you have a tremendous amount of trading in these levered ETFs.

[A]

Right, right.

[B]

Like some insane portion of Volume of the Cosby is driven by these levered ETFs. Stuff is

[A]

a little wacky.

[B]

Little wacky. I would just say that caution is definitely warranted if you're trying to play these equity rotation themes. You have to be nimble. Taking a step back, what does this all mean for bitcoin? I think, you know, bitcoin is doing its own thing right now. The main story that caused the move lower was kind of this, you know, death flywheel that MSTR was undergoing. That tail risk has been eliminated by the market. Now that they have $3 billion worth of cash on, on their balance sheets. That left tail scenario of like, oh my God, how much bitcoin is he going to have to sell and start selling? Like, does the market like nuke the price and then he's got to sell

[A]

more and yeah, that whole thing.

[B]

That whole thing and you know, debated stretch, like recover in price. Price terms. What I think you got to in the market was a point where if you hadn't sold by the time you got to 58, 59, 60, you're probably not going to sell anytime soon. So you got to a seller exhaustion point.

[A]

I think that's fair.

[B]

And then you had a little bit of a short base. And so what you've seen happen, I think is just some of that short base has gotten squeezed out. The, the magnitude of ETF outflows has slowed. In fact, some days you're actually getting inflows. ETH is quite a low.

[A]

I think we had eight consecutive weeks of bitcoin ETF outflows, by far the longest streak in bitcoin etf.

[B]

And so that's abated. And so when there are just not that many sellers in the market and there's not that many concerns near term at least, it just tends to grind higher, which is kind of what you're seeing now. And so I wouldn't be surprised if, you know, you approach 70. Yeah, yeah, yeah. You know, somewhere around there doesn't feel like a rally.

[A]

It's just sort of. It does feel like a.

[B]

It's a bear market.

[A]

Right. It just couldn't go lower at that moment. So it kind of went sideways and then it drifted higher.

[B]

Yeah. And I think it's perfectly appropriate within a downtrend to see 20, 30% bear market rallies off the lows.

[C]

Right.

[A]

Which we. We went to 82.5, I think, as recently as April. Right. Was that April? April, May.

[B]

Yeah, yeah, it might have. Yeah, exactly. It was like around 80ish.

[A]

Yeah. I think we got up to the

[B]

low and then 60 in like two weeks.

[A]

Like 57.

[B]

Yeah, yeah, exactly.

[A]

But I will say too, you know, we, you and I have debated this many times on this show since like October of last year. But you know, 58, 60 seems somewhat durable at the moment. You know, it.

[B]

I think if you were to retest those levels like today, it would probably hold.

[A]

Yeah, I mean it has now held three or four times. Yeah.

[B]

The bible for, for me this year is the bitcoin cycle and the evidence is pretty clear. You've written a tremendous report highlighting some of the on chain metrics and some of those cyclical dynamics. But it suggests you bottom somewhere in like late September Oct. We're getting close though.

[A]

We're starting to get close. I agree with that. And we put out the. I sometimes tweeted the bottom scorecard from that report that shows like the 10 or 13 metrics that very reliably mark the bottom in the prior cycles. Part of that report is also about how the very reliable top signals also mostly didn't fire this time. And I talk about the compressing amplitude of the tops and bottoms in this cycle. So I wouldn't be surprised if we don't go much if the bottom is somewhere we may have even already seen or not or near it. And you know. Yeah, I mean it would suggest like Sept. Or Oct for the. If it literally mirrors prior cycles. But you know, August is close to that. Like so it's kind of like you're within spinning close. I mean I feel like. And, and you know. Yeah, I mean right now it's just like 58k gang. If it can't break 58k lower.

[B]

I mean the other way to think about it is like the only real catalyst for bitcoin in the Next, you know, 30 to 90 days is clarity. Yeah, right.

[A]

I think we're calling it a toss up still at the moment.

[B]

Toss up. And so there's no way bitcoin breaks below the bottom end of the RA like before you have clarity.

[A]

I think that's right. And the other thing we were talking, I think you know, and to the

[B]

flip side, you're not breaking 70 without like probably not.

[A]

And also, even if, let's see, somehow get the most bullish outcome of clarity. I don't know, it's passed and signed into law, but it's passes by way out performing margins for let's say 90 senators vote. I don't know, whatever. The most bullet, which will not happen. I still don't think that gets us back to A hundred like you need more after that. But it does feel like if clarity passes you see a pretty decent response in bitcoin and and then maybe the bottom will have been in at that point it's not clear. Obviously we don't know anything but I agree like in the next month for sure. That's I think the only thing anyone's really watching there is a contentious soft fork brewing in Bitcoin has very low amount of interest but that'll be in mid to late August. We'll learn about VIP110 bit110 I think it's extremely, extremely low likelihood of affecting anything. But I mean that's literally the next most important thing I can come up with to be watching as a bitcoin specific catalyst.

[B]

Again mostly sleepy, sleepy brains bound like tough to play for. Vols are super low and so the market's not expecting much of anything to happen. I think the one thing I'll leave with as well is you know, gold. Gold has been under pressure for the past several months. It is testing this 4K area. But I think what's notable is in this environment you have so many alternatives in terms of like yield bearing assets, speculative assets. It's similar to the bitcoin narrative and it's also the flows have slowed down from central banks buying. In fact you've had some central banks selling but something to watch. Bitcoin's closest tradfi proxy isn't trading that well.

[A]

Yeah, well and it kind of makes again like you know everyone's like well it didn't trade like gold because gold kept going up after bitcoin started to come down. But of course we've pointed this out Obviously Bitcoin like 6x yeah. And so like its rally was before gold and now. Yeah I mean now if you look at the two they're trading kind of similar. I mean now I think everybody wants like beta up price up, not beta up price down, price sideways. But yeah, I think it makes sense. I mean people are in the. We haven't talked about this much you and I but you know we will. Owens on my team put out a great report called the race to trade. Everything about the hyper financialization that prediction markets and perps and stuff are all bringing in and you know it's the gambling that American men in particular do. A lot of none of this is conducive to something like gold or bitcoin. You know we really are in a pretty hyper speculative time and people want speculative assets not fundamentally store value assets. Obviously bitcoin is traded like a speculative asset in the past as well. But I think there's an interesting dynamic there. Like people that are using crypto want to go trade 100x levered perps and gamble on or bet on prediction markets. Not like work hard and stack bitcoin. Right now, that's just the moment that we're in. It's interesting. It's a summer. We got more. This was a good one. My friend, Bimnet Abibi from Galaxy Trading. Thank you for having me. Let's go now to our guest, Lucas Cheyenne, Vice President at Galaxy Research. Lucas, welcome back to Galaxy Brains.

[C]

Gm gm. Thanks for having me.

[A]

You've been hosting our other great podcast, Galaxy Grid. How's that been going?

[C]

Galaxy Grid Monday, you know, trying to learn from you. Trying to speed up how fast I say the disclaimer. No, it's been fun. I mean, it's awesome to cover what's happening every week. We've been doing it only in a bear market so far, so I tweeted this week, I'm super pumped to do it in a bull market. But yeah, I mean, we're looking at kind of more of the, I would always say crypto native stories that are happening every week and trying to keep track of what's going to be exciting in the years to come.

[A]

Yeah, it is fun. It's a four box, like style pod. You guys move quickly through topics. I join sometimes, but mostly with the Galaxy Research team. Had one external guest, right?

[C]

Yeah, we had Kareem, former Galaxy Research Helmy. Probably have some guests on in the future too.

[A]

That'll be cool. It's fun. It's an entertain pending podcast right now. I think we just still just put it on YouTube and X. Right.

[C]

We have Spotify. No, you can get on Spotify. Audio feeds are up.

[B]

Yeah.

[A]

Good job, Phineas and team, let's talk about your new report. That's why I wanted you to come on.

[C]

Yeah.

[A]

Your report was called Inference Capital Markets. That sounded like the overlap between crypto and AI when I hear that. Or I guess AI and financialization.

[C]

Yes. Yeah.

[A]

What. What was the overall report about?

[C]

Yes, definitely. So I would say it's part of this broader coverage that we've been doing here. Just looking at crypto and AI and how they are integr. This one's a little bit broader and what it's trying to see is, all right, if AI is becoming a part of everyday use for everyone around the world and there's this huge input for it, which is, you know, there's GPUs, there's energy, there's memory. Are these things going to become financialized? Because they're becoming a massive part of our economies and they're going to continue to grow. And so it started, the idea originally started because I saw a lot of cool on chain primitives starting to pop up. Things that were tokenizing access to inference, tokenizing inference production, tokenizing credit so that you could lend to Data Centers and GPUs. But as I dug deeper into that, I also saw that off chain there is this much bigger market that's already emerged, which is on GPU futures, GPU price indexes. And so the report gives an overview of first kind of what's happening off chain on the GPU side. Then it dives deep into kind of the on chain primitives are starting to emerge. For me, crypto is always a really good place for frontier markets to emerge. And if those frontier markets are successful, they usually get adopted in the tradfi world. And so especially during times like this in the market, I think it's really good to look at like what those markets might be. And so those are the three that I identified. I would guess in a year from now there's a lot more.

[A]

Yeah, it's super interesting. You know when you say inference capital markets and you were mentioning the GPU forwards and indexes, like what exactly is being financialized? Is it the, the full gpu, the full machine? Is it like the GPU hours, the tokens and the models?

[C]

Like there's a lot of different models that are coming out there, but the, the primary ones that are live right now by companies like ornn, Galaxy's investor in them, Silicon Data is basically tokenizing actual like GPU hours. And so you're saying for the price of rent, how much is it to write rent a GPU for one hour.

[A]

I see.

[C]

And so it's an index of that price. There's a lot of issues with that right now. Right, because like depending on what the GPU specifics are, there can be a lot of changes. Right. Where is the GPU located? What's the interconnects for the GPUs, what is the memory the GPU has? So right now they're providing index. They also have partnered with like ice, with cme. So we should see like actual futures go live and trade it at some point. But. And if you look at some like on chain exchanges, you can actually do that. Kalshi has a prediction market where you can trade GP price. But yeah, right now it's mostly just an index that's aggregating across all of the order flow that these companies see and trying to create like one price point for different GPUs. So H1 hundreds, H2 hundreds, B3 hundreds.

[A]

Yeah, it's interesting because I was going to ask that. Like there's, I feel like obviously in commodity markets, like there's different types of oil. You got WTI and other. Other. Yeah, Brent refined versions. Brent crude. Right. But there's not that many. And like, you know, like gold, like there's. Most people are pricing like a troy ounce or something.

[C]

Yeah, yeah.

[A]

Like there seems like there's a lot more differentiation in the GPU market. So like, can they. I guess the fungibility is a question I have. And then also, you know, for these futures, whether it's on GPU hours or just like the, you know, just the price of an H100, like don't we need a big avail, I guess on the GPU hour, tokenization, financialization. Don't we need like an available spot market to actually settle this? Is there like neo clouds where. I mean, I guess there must be. Where you can just like rent a GPU hour?

[C]

For sure there are spot markets. So like you can just go on like aggregators and providers and rent a spot hour. Okay. A lot of this is actually happening. Like the big deals are happening otc. Right. And like there's a. There's a great quote by this guy, the founder of Base10, which is a really large inference provider saying like for actually like getting GPUs in size, like it's kind of like doing a drug deal right now. Like you have a guy that you know and just has like access because they're so supply honest.

[A]

Right now, kind of like a 6 on Bitcoin feel similar if you're a

[C]

broker in that market right now. It's like an incredibly competitive but lucrative market to be in right now. On the differentiation side. Yes. So I think that is kind of where the issue is right now in terms of the. Besides just the market being young, but in terms of getting broader adoption of these types of products is figuring out like, how do you handle the differentiation? And they have looked at markets like oil and stuff where there's different types of oil and then you kind of like have an aggregated price that's representative of a basket of them. And I think where the real issue will come in the future is on like having to actually deliver GPUs. So right now a lot of the focus is on the cash settled futures, right? So like there's not an underlying you need to deliver. So you can aggregate pricing and then you can say like this H100 index is representative of like these categories of H1 hundreds. But in the future if you want to buy that as an actual hedge to then get a delivery of that gpu, you have to probably be a lot more specific.

[A]

Yeah, that makes a lot of sense. And you just referenced the, the cash settled nature. But you're in the report, you also, you noted that the indices that exist today are so thin, like they're, they're not liquid enough to definitely to be, you know, resistant to manipulation or other dislocations. Like.

[C]

Well, because most of the, most of the actual deals are not happening, you know, like most of the actual deals are just happening otc.

[A]

And that's kind of what I mean because I mean again I don't know a lot about, I learned a lot from the report but and so I encourage people to read it. I still need to learn a lot more about this market. I think everybody does for sure. You know the big deals that we read about in the news on the Bloomberg terminal, like these are not open platforms for anyone to go and price a GPU hour, right? They're multi year deals between, you know, power providers like a Galaxy and a NeoCloud or a Mag 7 firm and like you know, SpaceX and, or whatever. And like those GPU hours are not like public market GPU hours. So like.

[C]

Exactly. There's a huge pricing discrepancy. Like a spot market hour of a GPU versus a long term contract is going to be very different. Right. So that'll all be like is the

[A]

Mag 7 though and like the big hyperscalers, are they going to not. Is there still going to be a public accessible one or are they going to gobble it all up?

[C]

Because they need so much like there will always. Because there's always going to be some capacity that something goes wrong and excess capacity frees up and you want to monetize that. So you're going to want to have spot markets. They've been around in crypto for a long time. You know, you go to Amazon, is there any of that? They do have spot markets. Yeah, yeah, I think, I think like the real issue or not the real issue, but the is the question is like is there going to be demand that materializes to actually use these types of hedging products for real actual like hedging mechanisms instead of just speculation. Right. And so we are Starting to see some early inklings of that. There was a Reuters report actually yesterday that talked about how Core Weave is looking into potential hedging mechanisms. And so they haven't done anything yet. And it didn't say exactly what it would be, but you would assume, you know, with cme, ICE all coming online with GPU futures, that's probably going to be one very viable mechanism.

[A]

Yeah. And there's so many big, you know, whether it's sort of the intermediary providers or the MAG seven themselves or the open eyes and anthropics.

[C]

Yeah.

[A]

And whatever is like they, this is a very big market. Like hedging.

[C]

Yeah, for sure. And like the very interesting thing is everyone basically the price of GPUs has gone the opposite of what most people thought. A lot of people thought, you know, a lot of new, every year new GPUs come out, they're much better and efficient than the old ones. So you think the old ones become obsolete. But actually there's such a supply constraint right now and there's so much demand that, you know, gpus that came out a year or two ago are either maintaining price or going up in price.

[A]

Interesting.

[C]

So that actually makes it a better market. Right. Because it allows you to have a two sided market. If the price is just going down, it's hard to find a lot of buyers.

[A]

This is something that bitcoin miners faced consistently and it was the same thought that why would you run the S19 from Bitmain when you could run the S21? But then it was like, well I can't get my hands on an S21. The S19s might have traded cheap. So then you bought a bunch of those and then difficulty actually goes down at some point so they become more viable. Again that was probably much more constrained than this is because hashing does get a lot, lot better. But anyway, similar dynamic, similar dynamic.

[C]

And like there is kind of a similar dynamic I guess to like the difficulty adjustment which would be like, Even though older GPUs can't process the new models as fast, there is still a lot of like the shift to open source models that have smaller parameters and can run as fast on these older GPUs. GPUs means that there is continued demand for it. So you know, it's not necessary that even though new ones are coming out, older ones are going to go obsolete as long as demand overall just continues to pick up quite a bit.

[A]

And let's talk about that because one of the reasons the older models are being used Is the newer models are so expensive in tokens. You know, I know a lot of companies have started defaulting to like Sonnet 4.6 for trying not to get them. Don't use, you know, Opus 4. Eight all the time, you know, especially if you're not like coding something essential like if you're asking it questions. So the older models are still getting used, let alone the smaller open source. Like where do you see like tokens? Like, how do tokens fit into this? Are they going to we tokenizing tokens?

[B]

I guess.

[A]

I guess. And it's so funny that like tokens are now this like giant like international tech token term. And they're not talking about crypto tokens, talking about, you know, inference tokens, I guess, model usage tokens. And also where does something like Venice play in?

[C]

Yeah, definitely. So actually it's funny, like when I was writing the report, like our editor Mark kept being like, you need to differentiate between crypto tokens and AI tokens because the reader is not going to understand the difference, especially if you're talking about both in the same report, which it does. Yeah. So that I think is going to be the next evolution probably is that we start to see financialization of the actual tokens themselves. Once again, this is a really challenging issue because not no 2 tokens are really the same.

[A]

Right.

[C]

Like, these models are very different in terms of how they price tokens, whether it's a frontier lab, open source, the size of the model. So that's a challenge. What we are starting to see emerge on chain is yes, the tokenization of inference access. So it's not yet at the token level, but something like Venice, for example, which is a just. It's an inference provider. You can use it for private inference. They have a specific product basically where you can buy a token called diem. And what that does is a crypto token. A crypto has a crypto token called Diem.

[A]

Yeah.

[C]

And what that does is it gives you access to $1 of inference on their platform perpetually. So it's a totally different way about thinking of how to financializing inference access now. You know, there's a lot of questions about, all right, like is that the optimal instrument, like do for them? It's a liability. Right. They're now having to $1 that previously would have been bought on spot every day. They're now giving away essentially for free.

[A]

In the future.

[C]

Yeah, in the future.

[A]

It's like a gift card of inference.

[C]

Exactly. But for them it was a very good way to basically like Bootstrap early demand and get people interested. And I would expect in the future they probably change some of the mechanics around it or introduce other ways of tokenizing the inference. The cool thing about it now though is like let's say you own DM, so you get every day you get $1, 1 API dollar access to Venice models.

[A]

But so they, they're, they drip it to you as well.

[C]

Or it's just like you hold the token and then every day you're like account.

[A]

You could use it.

[C]

Yeah, every day your account resets and you have $1 that day. So if you hold it 100. Oh, so DM.

[A]

So DM gives you one hour, one. $1, $1 of token for every day. Every day I see $10,000 of DM.

[C]

Yep.

[A]

Or 10,000. Then I have $10,000 of DM of Venice spend. Per day.

[C]

Exactly. Per day, yes. So and I think right now it's like priced at basically like almost like four years worth of.

[A]

Well, that's the other thing that I'm thinking here is one. Like are people thinking that the dollar cost of inference will go down? So actually they're access will go up. Kind of like it's deflationary.

[C]

Exactly.

[A]

But also Frontier models use a lot more tokens, so they don't go down.

[C]

And.

[A]

Yeah. And then separately like does it's $1 of. To your point about tokens? Like the prices of the tokens vary for sure. Is. But is it actually of tokens or is it of access to Venice's platform?

[C]

It's of access.

[A]

So like they could change how much the price is.

[C]

That's exactly. That's one of the issues I bring up is. Right, so like you're not actually really like hedging anything. You're more just like saying. But here's, here's like how they say why it's maybe an advantage. So let's say it costs $1200 or so. So like you're almost getting like four years of inference. And after you use after four years, if you're still holding it, four years

[A]

of $1 a day.

[C]

A day. So after that, every $1 a day is basically free. Right now, obviously there's like huge. There's like capital costs and everything. So it's not that simple of a calculation.

[A]

Yeah.

[C]

The other thing here is, this is an example. They like to give a lot. They say, all right, let's say you buy one diem and diem costs $100 that day. You use it and the next day Diem costs $105 and you sell it back on the market. You just got a dollar of inference for free and you made $5 by holding the diem right Now I'm always like, well, the opposite is true. Let's say you buy it and it drops $5. You've now lost. You paid more for that $1 reference that you would. So like, it introduces this financial element. I, if you look at the actual usage of DM right now, I think like on a daily basis, less than 50% of it actually gets used, right. So if they have like $40,000 of inference credits, they have to give out for diem. Like less than 20,000 is being used every day. And so it shows. I think for now it's mostly being seen as like a speculative vehicle for betting on Venice itself.

[A]

I see.

[C]

But I think, I think beyond just diem, like, the cool thing is there are these defi platforms that are starting to come out on which diem can be used, right? So let's say you have diem, you bought it because you actually use it for inference. But you now know for the next week you don't need to use that diem. You don't want to resell it back into the market because you're worried about what happened to the price. You can go onto a platform and you can resell your inference you have through diem on that platform and recoup

[A]

some of those costs, hold the diem, but you resell the, the inference hours

[C]

or time or so if you go on like some of these like marketplaces that are emerging, you could buy like Fable Access or like some like GLM 5.2 access for like 40 discount. Because the DM guy is just saying, like, I'm just trying to recoup somebody.

[A]

Like I would get zero.

[C]

Yeah, exactly. So like you're seeing a discount market emerge there. We have actually quite interesting. It's kind of cool. We, we haven't yet seen like lending markets emerge, but I imagine very soon

[A]

we'll start to see like lending out your.

[C]

Take your dm, like borrow against it.

[A]

You know, this is one reason that this, this is a great example of your point you made earlier about how the frontier markets can emerge in crypto because the, I guess because the composability of the financial.

[C]

Exactly.

[A]

The ledgers are so composable. That's interesting that the idea. Because I'm using Fable 5 on my Claude code max plan. And right now it's like you have session and weekly limits and then they have the. You can use 50% of your total weekly limit on Fable 5. Currently they're, you know, dripping it to testers in the wire.

[B]

Testers?

[C]

Yeah, for now.

[A]

But you can't, I can't trade it. If I don't use it, I literally lose it.

[C]

Exactly.

[A]

So of course me and everyone else, we all try to use it.

[C]

Exactly.

[A]

But it'd be interesting if I could sell it or rent it or I guess lease it to you.

[C]

Exactly. Some other way to monetize it and. Yeah, and if, if you expect that like everyone's going to be using inference for everything every day, like you kind of want to have more efficient markets where you can start to do this. Right. Especially if you have a supply constraint where like people can't get access to inference because there's just not enough GPUs and things like that. So I, I, I don't know if the Venice form factor is the perfect form factor, to be honest.

[A]

I think it's the first sort of big one.

[C]

Yes. But it's a good experiment and I think it points to where we're going to move in the future. I did see there's Exchange Architect that has GPU futures and they actually put out a post today talking about how they, they also want to have token futures in the future. So trade like a GLM 5.2 token and let's say there's tons of Demand for GLM 5.2 but there's not enough GPUs that are like actually servicing it. Suddenly like that token price goes up in value which is the opposite of what we would expect. We would expect that they all just go down.

[A]

I love these words like we're going to have token crypto, tokenized AI, token futures, derivatives, futures. It's going to get wild in the future. I want to ask you about GPU backed loans. A lot of people own. Some people, but also, you know, certainly the, the big companies and data centers own a lot of GPUs and you know, you talked about excess capacity. Maybe they can fill those with Bittensor training or Venice, I don't know, or running a local model and releasing it to somebody else or whatever. But maybe they, even if they can or can't, while they're spinning, can they borrow off the value of them? You talked about how this is like already commercially viable and people are doing GPU backed loans. Like what does that look like?

[C]

Yeah, well, so, I mean the GPU financing complex is just insane.

[A]

Like is it really?

[C]

I can imagine outside of crypto, just in general, right? That's what I mean, we've seen it explode. What's happening on crypto is, you know, there's projects that are basically saying like, all right, well like there's, it's still a slow process outside of crypto and there's not enough capital I think yet to service all the demand. And so the crypto markets are going after, I would say like the smaller to medium sized data center build outs where they might not have the same access or partnerships to get the type of capital they need from banks. And so the crypto products are basically saying, all right, well we have this great product, a stablecoin and we have a global audience where anyone with a stablecoin can lend to us. So we're going to aggregate all of that capital and we're going to lend to these GPU markets.

[A]

So it's like tokenizing the GPU as like an rwa.

[C]

Exactly.

[A]

And then they like get it on board into like an A pool.

[C]

Exactly. Now there's obviously like this is all off chain ultimately so like there's issues like, you know, what happens if there's legal or like they go bankrupt. And we haven't yet seen an incident like that emerge. We'll be very interested to see it stress test once it does, presumably with

[A]

the right legal structures should work. Yeah, it should be much different than like a tokenized money market fund. Except that of course in this instance the underlying is a physical object rather than a financial instrument. But I mean I can see it

[C]

being possible and you can also see like a very interesting, like I don't know, not partnership, but I guess like ecosystems start to emerge where, what do these lenders need really well to, to underwrite a lot of these loans they need really good accurate pricing of like what GPUs cost now and what they're going to cost in the future. Like how much is a GPU going to provide in terms of cash flow for a data center in the future? And how do you get that with GPU indices, GPU future curves, GPU curves, GPU futures. And so you could see how like the development of this separate GPU indices and futures is probably going to help create more efficiency in the lending markets for companies that are trying to do this type of stuff.

[A]

Before we wrap, you have a broader conclusion. In the report you talked about how crypto may not win the model application or sort of inference layer, whether it's the training or the inference tensor or a Venice or something like that, but it might have a chance to win the Financialization layer.

[B]

Yeah.

[A]

What would I fast forward a few years. Like, what would you see that tells you that thesis is correct?

[C]

I think you would want to see like, Morpho and AAVE and these big lending markets being like, huge sources for people to borrow against, like GPUs or to also, like, be able to borrow against like, tokens and stuff, you know, and. And I think you want to be seeing a lot of these interesting, like, primitives pop up that enable you to take your access to inference, which you rent right now. Right. You can't own that, own it, and then monetize it when you're not using it. And so I would expect in two to three years we see that really emerge. It's going to be really dependent on companies like Venice, to be honest, which like being successful because ultimately you need to have a successful underlying inference business to make this work. We haven't seen a lot of those pop up in crypto yet. Venice, I think, has been the best example. The only other thing, and this is just one of the other aspects I talk about is like tokenizing inference production and basically would be it's like Bitcoin, but instead of like mining a block, what you're doing is you're providing inference. And if you provide inference, you get a reward. And so I think that's like, maybe another area where we'll start to see growth. Because ultimately what it does is it just like that token subsidy pushes down the price of inference. And so it makes. That's what drives demand for those types of products. You're just providing the cheapest inference.

[A]

I like that. That's very interesting. Well, check out the report on galaxy.com research. Lucas Chain, VP of research at Galaxy. Thank you so much, my friend.

[C]

Thanks for having me.

[A]

Thank you for listening Galaxy Brains, the weekly podcast from Galaxy Research. I'm Alex Thorne, head of Firmwide Research at Galaxy. Follow me on X at Intangible Coins. Follow Galaxy Research on X at GLXY Research. Read our written [e-mail] research and don't forget, if you like Galaxy Brains to like and subscribe on your favorite podcast platforms like YouTube, Spotify, Apple Podcasts and more. We'll see you next time.