Opinions

The entire US AI capex juggernaut has been threatened by the release of Chinese AI firm Moonshot's Kimi K3 release last week. The Kimi K3 AI model delivers performance on industry benchmarks that rivals top-tier offerings from OpenAI and Anthropic PBC at cheaper costs. Even from a technical perspective, Kimi K3 contains 2.8 trillion total parameters, making it one of the largest open-weight AI models ever released. Though, Claude Fable 5 & Mythos 5 has 6 trillion parameters along with GPT 5.1 Sol between 2-3 trillion parameters, it Kimi K3's ability to do long horizon work rather than simply answering questions which makes it second to Claude Fable 5 at one third the cost. Claude Fable 5 costs $10 per million input tokens and $50 per million output tokens. GPT- 5.6 sol costs $5 per million input tokens & $30 per million output tokens. Kimi K3’ costs $3 per million input tokens & $15 per million output tokens. Kimi K3's native image and video understanding also allows it to revise interfaces, games and other digital content after inspecting its own output. At launch, Moonshot reports 93.5% on GPQA Diamond, the best open-weight score ever published on that benchmark, 88.3% on Terminal-Bench 2.1, and a record 91.2% on Browse Comp for web agents. On Artificial Analysis' private long-horizon knowledge-work evaluation, K3 reaches an Elo of 1547, a massive jump from K2.6 and behind only Claude Fable 5. K3 slots in as the best open-weight agent, just behind Claude Fable 5 on reasoning depth and roughly even with GPT-5.6 Sol on terminal work, at a price between them. Hence Moonshot’s Kimi K3 threatens the very base of US AI Capex. Moonshot looks like a viable alternative, that could upend the business case for its US AI competitors. It might threaten the revenue model and eventually put a doubt in the mind of investors if current AI capex run rate in US is sustainable. Chinese models have already priced their services aggressively, undercutting US rivals. The weighted average cost of performing a standardized intelligence task using Kimi 2.6 or DeepSeek’s V4 Flash model ranges from 33 cents to just 2 cents, compared with $2.75 for the same task on Anthropic’s Claude Fable 5, according to benchmarking site Artificial Analysis. Moonshot’s latest offering is priced at a premium by comparison. Kimi K3’s cost on the same ranking is estimated at 95 cents. Kimi does not have to be the world's single best model to upend the US AI dream run. For companies, governments and developers, a model that performs near the frontier, costs 40% less and can be customized or run in-house may be the more attractive option. Its very existence puts pressure on the pricing power of U.S. labs, the enormous valuations built around their technological edge, and the case for spending hundreds of billions of dollars on large data centers. While US might still have the edge currently, the rest of the world might choose a cheaper alternative & that should be a scary proposition for the US AI community.

Recent advances in artificial intelligence (AI) have raised hopes of a boost to economic growth. Many market participants believe that AI has the potential to be the most important general-purpose technology of our era. The recent inroads of generative AI in everyday applications in particular promise widespread efficiency gains. But we see a different picture. AI boosts GDP by raising productivity and investment, with variable effects on the demand and supply sides of the economy. The output gap is the difference between aggregate demand (GDP) and aggregate supply (potential output). At first, supply exceeds demand in most regions, due to the concentration of early adoption of generative AI (GenAI) in “easy-to-learn” tasks. This leads to a swift increase in productivity that significantly surpasses the initial investment. Subsequently, as AI investment extends to less profitable areas of “hard-to-learn” tasks, the situation evolves with demand outpacing supply. This results in a positive output gap that puts upward pressure on prices. In the widespread AI adoption scenario, the effects on the output gap are twice as large as in a conservative scenario. In short term, AI raises productivity and lowers marginal costs, exerting downward pressure on inflation. But in long term, by nature of AI, intensely dependent on energy & commodity space along with limits on learning skills, AI leads to an uptick in inflation. In a conservative scenario, commodity prices may rise by between 1% and 2% by 2033 due to an AI induced increase in demand. In the widespread adoption scenario, the projected effects are twice as great. A natural starting point in this analysis is the familiar view of AI as a productivity-enhancing general-purpose technology: by improving efficiency, compressing unit costs, and expanding effective capacity, AI can act as a structural disinflationary force. At the same time, the macroeconomic footprint of AI is not confined to productivity. Scaling and deploying AI requires costly complementary inputs and infrastructure, can reshape product-market pricing and market power, and can alter labor-market rents and wage-setting wedges. Moreover, the diffusion of AI has increasingly taken the form of an investment and infrastructure wave—most visibly through rapid expansion of compute capacity and data-center build-out—that operates as a demand impulse as well as a supply-side transformation. The sign, magnitude, and persistence of AI’s effect on inflation therefore cannot be inferred from a single channel or a single dataset; they are joint empirical and quantitative objects that depend on how these mechanisms interact in general equilibrium. The net inflation effect of AI is not mechanically disinflationary even when productivity gains are present. A rise in productivity is a mechanism that exerts a systematic downward force on inflation by reducing unit costs, but it competes with forces that can raise marginal costs or desired markups during diffusion. AI specific input costs arise because the deployment of AI at scale requires scarce complementary resources—compute, energy, cooling, networking, and specialized capital—whose shadow prices can rise when capacity expands rapidly or adjustment is slow. On the employment side, again we do not see any wide spread impact on employment due to AI adoption. Total job postings have been broadly stable, there is limited evidence of a change in the low firing environment across key layoff indicators & WARN indicators show no broad-based impact of AI as layoff remains low. To summarise, AI is still not a threat to US employment in general. In fact, wage growth remains the highest for graduates with bachelor degrees or higher degrees. There is limited relationship between wage growth & AI adoption according to average hourly earnings. So, when the new Fed Chair Kevin Warsh says that he believes AI will lead to marked productivity gains & lower inflation, he is only looking at short term trend. Long term AI is inflationary.

While geopolitical uncertainty has surged since the start of the US-Iran war in late February, unlike last year’s “Liberation Day” shock though, the war has had little impact on a nascent cyclical acceleration. The investment acceleration we had expected to take hold in 2026 arrived ahead of schedule, with 2025 marking the strongest full year of equipment capex growth since the post-GFC recovery. What began as a narrow surge in the tech/AI sectors has broadened to other industries and types of equipment spending. Capex has remained resilient in March and April. Capital goods shipments and imports have continued to accelerate along with domestic production of business equipment. Hyperscalers ramped up their capex guidance for FY 2026 in Q4 earnings calls around $130bn higher than what they forecasted in Q3. This was further pushed up by ~$55bn during Q1 earning announcements, partly due to higher prices amid capacity constraints. Despite the recent rise in interest rates, broader financial conditions appear accommodative, and bank C&I lending has continued to rise at a 15-20% annualized pace in recent weeks. Adding to the tailwinds for capex, tariff refunds have begun to ramp up. A cashflow windfall will likely support spending alongside strong growth in revenue and profits. The only weak spot seems to be consumer spending. Consumption has been resilient since the start of the US-Iran war. This strength is likely unsustainable though, with households relying on one-time stimulus cashflows to offset higher energy costs. We estimate households received ~$45bn in additional tax refunds this year due to the One Big Beautiful Bill Act passed last summer. For comparison, through May, we believe higher gasoline prices will have cost consumers ~$30bn. To summarise, we expect business investment to grow 7.8% in 2026 on a Q4/Q4 basis, driven by strong AI investment demand, expanded expensing provisions, and fading drags from the normalization of factory construction and tariffs. Coupled with last week’s GDP tracking data, this implies 2026 GDP growth of 2.1% on both a Q4/Q4 and full-year basis. It's on the inflation side where we see FOMC members turning hawkish last few weeks. Most notable was the hawkish pivot in an outlook speech by Governor Waller, who has represented the dovish core of the Committee. Waller indicated that his risk assessment had shifted towards inflation, which has replaced the labor market as the “driving force” behind monetary policy in the months ahead. Even household interest rate expectations are building in inflation expectations similar to financial markets. Specifically, the net interest rate expectations indicator from the Conference Board clearly shifted in the direction of foreseeing higher rates over the next twelve months. The current difference between the 2-year Treasury yield and the effective fed funds rate is ~40bps but this week high was 50 bps. Historically, that spread has been a reasonably good leading indicator for future changes in the fed funds rate. For example, over the past three decades, the difference between the 2y yield and fed funds rate leads the year-over-year change in the latter by roughly eleven months with a peak correlation of +66%. To summarise, recent Fed communications are consistent with a Fed that is well positioned near neutral but increasingly concerned that inflation may prove more persistent. While our baseline remains that the Fed is on hold near neutral indefinitely, we now see equal risks of a rate increase compared to a rate cut as the monetary policy outlook continues to be impacted by developments in the Middle East. We still think it is too early to have a convincing view on either a cut or a hike at least till we get clarity on the middle east conflict. We will be soon releasing a detailed piece on AI’s impact on US inflation. We believe while AI’s productivity gains put a cap on long term inflation, short term price impact of AI capex is leading to elevated goods inflation via semiconductor chips prices, computer flash memory & old computers.

Last two weeks were unique because we saw rising bond yields globally along with rising DM equities but falling precious metals. DM yields sold off sharply across jurisdictions last 2 weeks driven by elevated energy prices amid inconclusive headlines on the Middle East from the Trump-Xi summit, a sharp increase in UK political noise and heavy supply across several markets. We now see this trend continuing even if there is a Iran deal. The global economy is in the midst of a cyclical upturn in goods spending, which is putting upward pressure on prices. If our baseline view is realized—that is, that the Strait of Hormuz soon reopens and crude oil prices linger close to $100/bbl—a mix of goods sector cost pressures, tightening labor markets, and firm pricing power could push global core inflation well above 3%. Such an outcome would set the stage for a new round of global monetary policy tightening. Core inflation is now sticky globally because of reduced supply chain resilience, service inflation remaining high, rise in short term inflation expectations & the fact that inflation is not any more range bound. Hence in line of above facts, we see short end yields globally remaining elevated during H2CY26. This does not bode well for precious metals. Higher yields raise the opportunity cost of holding non-yielding assets, and markets are increasingly entertaining the possibility that the Federal Reserve may have to keep monetary policy tighter for longer or even raise rates again. We also looked at correlation of Gold & Silver with DM short end yields i.e. 2-year bonds. As expected, precious metals have a significant -ve corelation with short end DM yields. The more the DM short end yields remain elevated, the more precious metals become unattractive due to lack of carry. For precious metals, the risk-reward setup is becoming increasingly asymmetric. They are vulnerable to a larger correction if markets price in more rate hikes, stronger real yields and a firmer U.S. dollar which is our view too. Rising borrowing costs, persistent inflation, elevated energy prices and deteriorating fiscal dynamics could push markets closer to a breaking point. Hence, we now see Gold testing 4000 levels & Silver testing 65 levels in H2CY26. The stop to this view is Gold at 4900 & Silver at 85. CMP of Gold is 4500 and Silver is 75.

Limited progress on the negotiations between the US and Iran has pushed oil prices modestly higher on the week closing at 109+ for Brent, as persistent physical constraints continue to build pressure amid still limited visibility on the reopening of the Strait of Hormuz. We now expect Brent prices to remain sticky in the low $100/bbl even after the Strait reopening, eventually averaging $95/bbl for CY2026, as the bottleneck will shift from the physical chokepoint of the Strait to tanker availability and strong demand to rebuild inventories. DM rates are pricing in hikes aggressively against our modest expectations. The US money market curve (1Yx1Y OIS minus effective Fed funds rate) is now +vrly sloped with markets pricing ~30bp of hikes by June’27 (against our expectations of a 25 bps cut in Q4CY26), while €STR and SONIA curves are pricing between 2 -3 25bp hikes by the ECB (75bp) and BoE (66bp) before year-end vs. our call for a cumulative 50bp (June and September) and 25bp (July hike) respectively. In Fx, while the broad Dollar is close to flat over the last few months, that obscures larger shifts under the surface and quietly building Dollar appreciation pressure. We have been emphasizing that terms of trade have been a key differentiator for FX returns in this more divided Dollar environment, and it is increasingly clear that two major forces—the energy shock and AI-driven demand—are responsible for the shortages causing that move. As the past week has demonstrated, we think the clearest risk for a stronger Dollar is if a wider energy shock begins to pressure growth, policy, and prospective returns in other developed countries, particularly Europe. In the credit space, the absolute level of defaults has been trending higher from the very low levels that persisted in 2022/23 but remains near historical median levels. Interestingly, in contrast to the prevailing market narrative related to potential disruption of Software-focused firms, the sector composition mix still skews heavily towards capital industries and consumer-facing businesses. None of the metrics we monitor signal a near-term uptick in expected defaults in the US. In Europe, we still envision a modest increase in defaults through year-end, owing to a more challenging growth, inflation, monetary policy mix. To summarise, we are bullish on 10yr Gilts, 10yr Bunds, bearish on Gold & Silver, bullish on DXY specially against EUR & JPY. We like 2*10 US steepeners and like receiving 1yr-1yr forward US SOFR. We are neutral on equities now and on Brent see a range of 95-120 for REMCY26. We like selling IVs in commodities especially crude and buying IVs in precious metals & DM equities.

President Donald Trump will be the first US leader in almost a decade to visit China when he lands in Beijing on Wednesday. His much-anticipated summit with President Xi Jinping delayed from March due to the Iran war offers the leaders of the world’s two largest economies a chance to reset personal ties and look for common ground on trade, technology and a range of other contentious topics. But the timing could not have been worse for Trump or better for Xi. While Trump is lost in how to end the Iran war, Xi is perfectly settled in his new role as the leader of the new world. While Trump is moving from one crisis to another, Xi carries on with the aura of a confident leader. While both US & Chinese economies are doing well in their own core areas, it is the political leadership arena where Trump pales in comparison to Xi. The main issue of discussion might be China's relationship with Iran and it's ability to influence Iran to accept US terms for opening up Strait of Hormuz. We believe China has significant leverage at this point of time. Not only in terms of it's excess reserves of 1.2 billion barrels but also it's ability to shift to new energy resources. In addition it can act as a guarantor for Iran because of their close commercial interests. Trade, tariffs, AI might be other areas of discussion where both Trump & Xi can find common ground. Expectations include major Chinese commitments to purchase soybeans, energy – particularly LNG – and potentially Boeing aircraft. Such deals would help stabilize the US agricultural sector ahead of the 2026 midterms while assisting China in diversifying its energy supply away from the vulnerable Strait of Hormuz. The current effective tariff rate for Chinese goods is approximately 20% including the 11% before Trump 2.0 and around 10% since Trump 2.0. On Taiwan, we believe even if Trump tries, he might not get it past either Congress or Senate. So, we do not expect Trump to commit on the Taiwan issue any more than what the previous US presidents have done. To summarise, Xi goes into the summit with a far superior hand than Trump. China is fairly well insulated from the war’s impact, with a diversified energy system based on coal and renewables and with huge petroleum stockpiles. Before a shortage of oil becomes a problem for China, high gasoline prices will be a bigger problem for Trump. Xi can afford to ignore the Iran issue while he decides what commercial favors to give to it's allies. From a market perspective, any comments from Trump/Xi on Iran conflict will be most sought after. In all likelihood, more trade deals and rare earth co-operation imply upside for both US & Chinese tech companies.