Prof G Markets - Gas Is Back Above $4 — And Could Keep Rising

Episode Date: July 21, 2026

Ed Elson is joined by Matt Smith to break down how the latest developments in the war with Iran are affecting oil prices and where he thinks gas prices could be headed next. Then, Charlie O'Neill joins the show to discuss China's new AI model, Kimi K3, why open-source models are gaining momentum, and what that shift could mean for the broader AI race. Matt Smith is the Director of Commodity Research at Kpler. Charlie O’Neill is the Co-Head of Model Training at Baseten.  Subscribe to the Prof G Markets Youtube Channel  Check out our latest Prof G Markets newsletter Follow Prof G Markets on Instagram Follow Ed on Instagram, X and Substack Follow Scott on Instagram Send us your questions or comments by emailing [e-mail] Learn more about your ad choices. Visit podcastchoices.com/adchoices

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Money markets match. If money is evil, then money, then that building is hell. The show goes up. Welcome to Profits and never watch the show. Welcome to Profite Markets. I'm Ed Elson. It is July 21st. Let's check in on yesterday's market vitals.

The S&P 500 and the Dow declined as conflict in the Middle East escalated. The NASDAQ was flat. Oil was volatile. More on that in a moment. The yield on 10-year treasuries rose. SpaceX stock hit a new low of $120 per share and finally, Warner Brothers shares fell nearly 4%

after a judge temporarily halted its deal to get acquired by Paramount. The judge said the sale likely violates antitrust laws and scheduled a hearing for next month. Okay, what else is happening? Conflict over the Strait of Hormuz keeps escalating, and now it is spreading to Saudi Arabia. As of Monday, the US had bombed Iran for nine consecutive nights

in response to Tehran's attacks on oil tankers, and Iran had retaliated with strikes across the region. But yesterday, Iran's Houthi allies in Yemen declared a naval blockade against Saudi Arabia. This blockade stands to threaten the primary way in which oil has been able to get around the Strait of Hormuz through a Saudi pipeline to the Red Sea. These developments immediately shot the price of oil back up.

Crude is now about $89 a barrel and the national average for a gallon of gasoline has yet again hit $4 in America up 15% in just the past week. So to discuss what is happening in the Middle East and also how it's affecting the price of oil, we are speaking with Matt Smith, Director of Commodity Research at Kepler. Matt, great to have you on the show. A lot happening here. if you could just give us your initial reactions and a quick rundown, what has unfolded and how is it being reflected in oil prices right now?

We're tracking those tankers that are passing through the Strait of Hormuz here. Our job has become increasingly more difficult as there's been different routes to try and traverse the strait. And so what you've essentially got is you've got the Iranian route, which is right at the top, kind of the north. And then you have the pre-conflict hybrid. way, which was straight through the middle, and then at the bottom, you've got the Omani route, which is the kind of the southern corridor. As we've seen escalations increasing here, and you've

seen some of the tankers being hit that were passing the Omani route, all we're actually seeing now is essentially traffic grinding to a halt again, except for those Iranian tankers and friendlies that are passing the Iranian route. So it's been undulating, right, over the last few months, you know, March, April, and even into May, the traffic was very, very slow. And then, you know, just over the last month or so, we've really seen it pick up because of the signing of the memorandum of understanding between the US and Iran. Now that has basically been, you know, dissolved. And we're seeing an escalation here in attacks, as you mentioned.

It's been nine consecutive nights. We'll probably have the 10th today. And so this is causing all prices to, to, to, you know, to, to start to kick back higher again. Just looking at what happened with Saudi Arabia and that blockade, it seems as though oil supply was figuring out a way to kind of reroute itself away from the Strait of Hormuz or around the Strait of Hormuz. I guess my question is, to what extent was that successful,

and to what extent has that now been kind of blocked now that we've got this? new development. It was working pretty successfully and so it was able to reroute about three and a half million barrels a day of Saudi crude across to the Red Sea. And so Saudi was exporting about seven million barrels a day out of the Middle East Gulf prior. So it was able to reroute half of that crude. So that put them in a better situation more than most. So that has definitely helped somewhat cushion the supply shock because all of that crude was then going across to the Red Sea and was heading into the likes of India, China, South Korea, these countries that were otherwise getting their crew from the Mideast Gulf and it had stopped. And so it was definitely providing some support

there and helping, you know, in terms of support in terms of supply and then helping to keep prices in check somewhat. Now, the Houthis are threatening to do that blockade. They're not actually doing it yet. We're not seeing tankers or anything being being hit. But this essentially is the ace that Iran has in its pocket because we've had this escalation that's been happening over the last few months here. And some have said, oh, we know they could close Babar Mandib, but they've kind of held that back until the point where the US would essentially start perhaps attacking, attacking infrastructure, energy infrastructure bridges. And that's kind of the point that we've got to. So then it's for Iran to up the ante here. And that's basically bringing Bab al-Mand-Dab into play. And so

it's really just a sign that essentially Iran is getting to the point where they've really got nothing left to lose or, you know, they're just a sign. just getting to the point where they're willing to do this kind of scorched earth tactic. And so we'll have to see how this plays out. But the threat of stopping these flows will definitely have a bullish impact on prices. So the memorandum of understanding has been dissolved. We are now fully at war striking Iran on multiple consecutive nights. Now they are, as you say, playing their ace card. They are trying to block any of the other supply room. that have been resorted to over the past several months.

I mean, it doesn't look good. And we're at $89 a barrel. Gas in America has gone back up to $4. Why should we believe that that number is going to come down within the next, I don't know, several weeks? Yeah, no, we shouldn't. And actually, what has developed, over the last few months here, or essentially since the beginning of March when this has happened,

is everyone's been watching that oil price, and you haven't felt the biggest impact on that oil price. And the reason for that has been a number of different reasons. You know, China has really come out of the markets. China has just stopped buying oil. They've stopped, they dialed back on their imports by about five, five and a half million barrels per day. So that has been hugely helpful. You've also had essentially a lot of these refineries dialing back on their activity, so they haven't taken that crude. And that has largely offset the production loss we've seen from the Middle East. But what that has meant is that the pain has essentially been transferred from the oil price across to the products. And so when you talk about gasoline at $4 a gallon on the

national average, we see diesel at $5, breaking above $5, and that's going to be really pushing higher because in barrel terms, it's about $170 a barrel for a barrel of diesel. And so that's where that pain is coming through is in the products because we're not seeing those produced, whereas the crude market is somewhat remains somewhat in balance because of this rerouting and because of this lack of refining. When you look at that number, $89 a barrel, to you, does that say that investors are feeling optimistic about the current state of affairs or pessimistic. I mean, does that number hold any biases inside of it?

One huge bias that it holds is that even if you are bullish on oil markets, you're not going to go and buy a paper barrel because you could have President Trump tweet something in five minutes time and oil prices could drop by 10, 15%. So I'm not saying prices are manipulated per se, but they are definitely under the influence here of things other than fundamentals. And so because of that, you've got some that are simply not getting involved in the oil trade. And that has been happening for a good number of months here.

There's a lack of liquidity there. The flip side of that, that's why I point to the diesel market again, is because the US administration is fixated on the oil price, super fixated on prices at the pump. It's not necessarily paying that much attention or putting that much emphasis at all on diesel prices. and so that's perhaps the least influenced market out of all of the petroleum complex, and that's the one that we're seeing absolutely ripping here. I mean, this is essentially the most important question for the US economy right now, which is what's going to happen to the price of oil,

what's going to happen to the price of fuel, as we saw in the previous inflation report, it was lower oil prices as a result of the memorandum of understanding that made the number go down more than the previous month, but now we know that whatever pricing was being priced into the market at the time was incorrect, because the memorandum of understanding is over. We're now back at war. Some would argue we continue to be at war the entire time. I won't get into it.

But it seems that what we have seen over the past week is going to have material impact on U.S. consumers and the U.S. economy, and perhaps that isn't being fully reflected or appreciated. or priced in by investors and traders right now, how impactful and how bad do you think it will be going forward? Well, we could just continue in the status quo, right, in that there's this back and forth between the U.S. and Iran in terms of the attacking of tankers by Iran, the attacking of infrastructure by the U.S. And then in the background, there is talks and whispers of diplomacy,

which helps keep oil prices in check here, which in turn helps keep. prices of the pumping check. But you know, when we came into this thing, there was the expectation you can't close the Strait of Hormuz for two, three weeks it will cause like Armageddon. Yet here we are four and a half months in. And so it's really realistic to try and consider the scenario. Could this still be closed in November and December? Yes, there are workarounds. There's medium-term plans here to reroute crew, but we really could be just continuing to scramble over the next four or five months here. And that's a reality. If that happens, you're not going to be an environment where prices at the pump and diesel prices are moving lower.

What kind of price do you think that that would result in if we find ourselves in the same situation that we're in today? And to be clear, I mean, it seems like a couple chips are making their way through the Strait of Hormuz. I mean, is that right or is it just zero? There was like a week or so ago, or even just before the week. weekend where you were seeing some getting through there, but the Iranians have turned their focus to targeting those because they were going through the Armani route, they were getting like a U.S. naval escort. And so those, they're trying to deter any kind of traffic. So the only traffic that we're seeing going through right now is related to Iranian or Iranian. And it's just

empty tankers. And so, but to your point, we were seeing over the last month this increase in traffic going through, increased confidence, increased risk taking. And, and And that really helped the oil market, not necessarily on the oil price, but in the differentials, you really saw the air being let out of the tires there, the pressure taken out, as we saw the stranded cargoes in the Mideast Gulf getting out of there. But then again, it's one step forward, two steps back here, where we're back to essentially the doors being shut again. So I'll return to my question, which is if we find ourselves in the same position that we are in today, four or five months from now, what would you estimate the price of oil will look like?

It's got to be higher. You know, I'll hold up my hands here. In March, if you'd ask me that question, or you may have done, absolutely. But like, you know, all prices should be $120, $130, $14040 if you close the straight for months and months. And so perhaps I've been burned by saying that, right? But maybe if we're going to be pushing above 100 here, that doesn't seem unrealistic at all if we're in the same scenario that we're in now in four or five months

time. If we're in the same scenario that we're in now, and it isn't above $100 a barrel, what would have had to have happened to get it lower than that? What would what truths would need to exist in the world for oil to not

be more than 100? Well, we'd be drawing down inventories at everywhere that we could. You'd be having tankers sneaking out of the Strait of Hormuz, however that was possible, rerouting of crude as much as possible too. But it's just difficult to see a scenario where you're not pushing into triple digits if this is still the situation in four, five months time. All right. Matt Smith is Director of Commodity Research at Kepler. Matt, appreciate your time. Thank you. Thanks, Ed. After the break, why investors are so worried about the latest Chinese model.

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is a must see. FX's The Shards, streaming August 5th on Hulu on Disney Plus. Sign up now at Disney We're back with Profi Markets. China just gave Wall Street its second deep-seek moment. Chinese startup moonshot AI released Kimmy K3, the world's largest open source model on Thursday. On some benchmarks, including front-end coding, K3 beats the best models from open-AI and

Anthropic, but the biggest story may be the price tag. Running K-3 costs roughly a third of what anthropic charges for its flagship model and businesses are starting to notice on open router, a marketplace for AI models. Chinese open weight models now occupy the top five spots by weekly global token usage. The NASDAQ fell about one and a half percent on Friday as US tech stocks sold off following the release of Kimmy K3. So we wanted to speak with an expert who works hands-on with both open and closed models. So joining us is Charlie O'Neill.

co-head of model training at base 10. Charlie, thank you for joining us. So this Kimmy K3 model that was just released has everyone kind of with their hair on fire. We obviously saw the NASDAQ erased 1.5% ship stock sold off. A lot of people saying that it was a problem, David Sacks, the former AI czar called the release quote concerning. What do you make of Kimmy K3? Yeah, I think the big story here is not necessarily Chinese models versus American models. I think the big story here is open source versus closed source. So obviously the story we've been sold for the last, you know, several years is that closed source is going to continue to dominate.

The American frontier closed source labs are going to continue to pull ahead, and open source will never catch up to that. And I think what we're seeing with Kimmy, with, you know, other Chinese models like GLM, GLM cores a very, very big wave. It may not have done the rounds in the same way that Kimmy did, but it was certainly a great model. And even like releases like inkling from thinking machines, which is an American company,

what we're seeing is that basically the recipe to build these things, there's no secret source. The big labs, they don't have anything that the open source labs don't have. And open source is going to continue to improve the capabilities and intelligence of the models they release as we scale up the size of these models and the amount of data and compute that goes into them. And so, yes, from one kind of aspect,

it's concerning that this is like a Chinese model that is leading the charge with this sort of open source versus closed source debate. But I think there's really promising signs for the open source ecosystem in general. And I think a lot of people are starting to realize that that's potentially a better world to end up in, compared to where you have maybe a duopoly with open-air and Anthropic having these models that pull away from everyone else, and they dictate all the terms of access and control that intelligence. Just for the uninitiated, what is the difference between an open-source model and a closed-source model? Anthropic, Open AI, Google, their flagship models are what we refer to as closed source in the sense that I can ask it a question.

That question gets sent off over the internet, goes to their GPUs, which run the model, they do the number crunching, and then they send the answer back to me. I never get to touch the model weights, which you can think of with this big collection of numbers that do a bunch of multipliers to give me my answer. Whereas with open source, I can actually download those numbers. Not only can I host that on my own GPUs, I can also do things like continue to train it myself, for specific tasks. So it's really about being able to download the actual weights of the model rather than just being able to send a question to it. So you can think of this as like, you know,

owning the disk for an Xbox game versus like having that Xbox game installed through the cloud on your particular Xbox. I can actually like see the physical disk. What would be the pros for developing a closed source model instead of an open source model? Why would Open AI and Anthropic pursue those methods instead. I guess there's two answers here. The first answer is the one that Open Air

Anthropic will tell you, which is that, you know, these things, as they become increasingly intelligent, we have to think very carefully about how they're applied in society. There's obviously real safety concerns, there's cybersecurity concerns, there's biological weapons development concerns, and so we should really think about who we trust to build and control this intelligence. And Anthropic and Open AI's argument is you should trust us. Like, we are the best of developing this intelligence and hence we should be the ones to dictate how it's used and how it's applied, basically in perpetuity. There should be a very small number of actors who can choose what we do with LMs and intelligence.

And I think the real argument is that obviously this stuff is so lucrative that if you do manage to prevent anyone else from developing it, you can capture insanely high margins on the tokens that you're producing. So Anthropics are rumored to have margins north of 80%. I think when there is a case where a world where there's only two major players and you end up into Juopoli, that is a very real possibility to continue. And I think that's obviously very, very lucrative to open-anthropic. So open-source is a threat to them in the sense that those margins are going to remain at 80% for long.

Of course, there are security concerns. We have to really think carefully about how these things are used. But at the moment, it doesn't seem like open-source versus closed-source. The intelligence ceiling that we've gotten to hasn't led to any increased concerns around, you know, can I use this model through open source or close source? Like the risk of developing a bioweapon, for instance, is about the same in either case. It seems that there has been kind of a shift

towards both Chinese models, but also open source models. Most of these Chinese models are open source or open weight. Why is that happening, do you think? What is the value proposition that developers are deciding is greater when they use these types of models as opposed to one offered by Open Eye or Anthropic. I think there's developers who have a very, you know, inelastic demand for the frontier intelligence

that will always want to use the most intelligent models. And then there's the ecosystem and the economy in general. The way I like to think of it is that for all the economically valuable tasks that we could plausibly use in LLM for, there is some intelligence threshold at which below that it's very difficult to do the task. And above that, you're getting very diminishing returns to having more and more intelligent models. and usually intelligence is correlated with cost. So the obvious argument here is that there is margin pressure on all these startups, all these companies,

even Enterprise now who are doing this particular task with LLMs. They've hit the threshold of intelligence probably even a while ago with open source. Open source has been accelerating rapidly, and you just don't need a fable or mythos-level model in order to do some of these things, and you get exactly the same performance if you use a model that's a tenth of the size

or even a 50th of the size. Post training is also really important here because it means you can teach a much smaller, to do one thing really, really well, as opposed to taking an off-the-shelf open-source or closed-source model and trying to prompt engineer your way to doing that task. So post-training really changes the economics here. And of course, you can only post-trained on open-source models because you can actually touch the weights as opposed to close source.

And so I think margin pressure is a big one. Another one is like, Anthropic and Open AI, I think are realizing that the recipe is the same amongst all these companies. Like, there is no secret source. Yes, there's probably a long tail of optimizations, small optimizations, that arethropic and open-hour have that the rest of the ecosystem doesn't have, but their moat is no longer in there being, them being the only ones who can post-trained, or sorry, train these very, very large multi-trillion parameter models. Their moat now is starting to shift towards, okay, well, if we

have a little bit of a head start, what if we try and, like, hit particular verticals? And so Anthropic is very clearly doing this. They're going after the verticals of, you know, finance and legal, open-air as well. And so I think companies are really feeling this pressure. If you're a startup or a company in legal or finance and you're using LEM to do these particular things and you have previously just been an anthropic wrapper, you've just got some logic calling anthropic models. You don't have a distinguishing moat for an anthropic between you and anthropic. And so you're starting to think about, okay, what's the one thing I have that Anthropic doesn't

have? And that's a really nice feedback cycle. I have users who love and hate my product for various reasons and they will tell me what they love and hate. And I can use that to improve the intelligence of a model. And again, you do that through training. And the only real way to do that is with open source models. And so I think it's this combination of margin pressure

and companies wanting to develop their own mode to protect themselves against their vertical being eaten by these closed source frontier labs. It seems like a big piece of the story for an enterprise for a company that's trying to leverage AI as much as they can. And Alex Kopp talked about this in his interview with CNBC that has since gone viral is basically just the price.

Anthropic tokens are expensive, open AI. tokens are expensive. Tocons from Chinese model providers are less expensive. So my question is, to what extent is there a relationship between price and being open source? Why is it that these Chinese models and these other models that aren't, you know, frontier lab models, how is it that they can offer a product that does the job pretty well, but at literally a fraction of the cost? The answer to this used to be simply that the Chinese and open source models were much smaller. So the big labs were the only ones that had the compute to be able to train the really large models. And of course, the scaling laws that we have predict that intelligence increases, but with diminishing returns in model size.

And so, yes, of course, the big labs had better and bigger models, but you often could use a much smaller models to do the task. I think now it's more of a case of like, okay, some of these open source models are actually very large. And I think K3 was a massive shifting point because, you know, previously we'd gone into the just forward into the one trillion parameter model range with the previous Kimi models and DeepSeek very, very recently. But this is, you know, almost three trillion parameters. Like, this is a big boy. And so now it's much more about, okay, we're really seeing under the hood that the reason

that anthropic and open AI models are so expensive is because they have great margins, because they were sitting at the frontier and there was no real competitor at the very frontier. And again, a lot of this stuff, like it is inelastic. You do demand frontier intelligence. But now we're really seeing, okay, if we do have, you know, multi-trillion parameter open source models that any company can, you know, host on their own GPUs and can post-train and then host on their own GPUs, then what that's telling us, and a lot of analysis is telling us, is that the frontier labs margins are just massive. And so I think that the shift that's going to happen now is if there is an alternative that is essentially the same,

and to 99.99% of people doing 99.99% of things is indistinguishable, like Kimmy is indistinguishable. like Kimi is indistinguishable from a fable or a GPD 5.6 soul. We're just going to see those margins shift. So instead of being 80% to the person who train the model, they might end up being 40% and the rest of that margin is going to be distributed, one to the consumer and then two to the rest of the ecosystem. So the compute providers and the infants providers

are going to be big wins of all this competition amongst, you know, model trainers. It's no longer the case where there's only one or two players who can do this and capture those massive margins. there's going to be much lower margins for model trainers, and the rest is going to kind of be spread out amongst the ecosystem. It seems to me that these models, Kimmy K3 and plenty of others, that seem to be released practically every month, and then we see all these benchmarks where they're performing either in line

with open-ey-eyes models or outperforming them. It seems like that, combined with the pricing pressure, could literally bring the frontier labs to their knees. If we know that they're already struggling to generate more revenue than they spend, if we know that they're also stacking up billions of dollars in losses, and they essentially need to develop more pricing power if they want to get profitable and get cash flow positive over the next few years, and that's been open-outers' objective.

It seems like this is exactly the kind of thing that we'll get in the way of that. Is this dire to the AI ecosystem? How does this actually play out for the largest names in AI? I've obviously been a big advocate and proponent of open source for a long time and want open source to win in some reasonably significant capacity. I think my honest take here is that this isn't the death knell for Anthropic and open AI. I think ideally and probably most likely now we're going to live in a world where there are a few key core frontier players and then a large diverse ecosystem of open source model providers.

The reason I think that is because of kind of the distribution of tasks in the economy that we're currently trying to tackle with LLMs, and the distribution of tasks in the economy that we should be tackling with LLMs in the next 10 years. I think what we're going to see is a little bit of a bifurcation. I think tasks that we can currently conceive of as being economically useful and all the jobs that we currently do, we are going to rely more and more on open source to be able to do those things. I think very, very frontier things.

for instance, science and math discovery, which, you know, have a longer, they have a lagging period. There's a lot, there's a bunch of labs like periodic labs who are really looking forward to to tackling science over multi-decade horizons with LMs and this new intelligence. I think the frontier labs are going to gain a lot of like, you know, economic benefit from tackling those tasks. I just don't think we're going to live in a world where the labs subsume everything. I think we're going to see this like rising tide of intelligence. open source is probably going to continue to lag behind a little bit to some extent.

I think those are going to be fairly parallel lines that go up together. But, you know, if you're doing frontier science and you are planning these very, very long, you know, scientific endeavors in order to extract economic value from whatever it is you're doing, you are going to be wanting to using the best intelligence. And I think Anthropic and Open AI and other players like them will make, you know, significant profits and contribute significant value on those fronts. It's just that it's not the world we thought it was going to be two years ago where they would also get all the value underneath that of like, you know, current GDP and the things that we

currently conceive of as economically valuable. And I think that's a good, that's a good outcome for everybody. No one player wins. I think we still have significant, you know, capitalistic pressure to advance the intelligence of these models and the frontier levels will feel that at the very frontier. And then that's going to diffuse throughout the rest of the ecosystem as well. All right. Charlie O'Neill, co-head of model training at base 10. Charlie, we appreciate your time. Thank you. Thanks having me. Okay, that's it for today. If you're catching this episode on Tuesday morning,

I hope you'll take the opportunity to join our live stream later today at 1.30 Eastern time. Scott and I are going live on Substack with economist Noah Smith. We'll be unpacking the biggest question marks about the economy with him, and we'll also be exploring China's role in the AI ecosystem further. Head to Profitimedia.com to subscribe. If you haven't already, the live stream is free. and open to all subscribers. This episode was produced by Claire Miller and Alison Weiss and engineered by Benjamin Spencer.

Our video editor is Brad Williams. Our research team is Dan Chalon, Kristen O'Donohue and Mia Solverio, and our social producer is Jake McPherson. Thank you for listening to ProfG Markets from Profg Media. If you liked what you heard, give us a follow. I'm Ed Elson. I will see you tomorrow.