America’s $30 Billion Air Traffic Upgrade Turns Infrastructure Into an Execution Test

The United States wants another $30 billion for aviation upgrades after Congress already approved $12.5 billion. The investment case is compelling, but the bottleneck is execution: replacing radars, communications, software and towers while a safety-critical network keeps operating every day.

Air traffic control modernization has become one of the clearest tests of whether the United States can turn a large public appropriation into reliable operating capacity. Transportation Secretary Sean Duffy is asking Congress for another $30 billion for towers, software and airport improvements after lawmakers already approved $12.5 billion. The case for replacing aging infrastructure is strong. The harder question is whether money, procurement, technology and staffing can be coordinated while the system keeps directing tens of thousands of flights every day.

The latest request is not a completed funding decision. It is a proposal that still has to pass through Congress, program design and contracting. That distinction matters because infrastructure headlines often compress several stages into one number. An authorization is not an obligation, an obligation is not an installed system, and an installed component is not useful capacity until it works with the rest of the network. The gap between those stages is where execution risk lives.

The immediate political argument is about scale. According to Reuters reporting on September 22, the new request would build on the $12.5 billion already approved, with the earlier proposal increased by $10 billion for airport improvements. The economic argument is more demanding. The system needs new radars, communications links, voice switches, software, towers and airport equipment, but those assets must be introduced into a live safety-critical network without creating the disruption they are meant to prevent.

That is why this should not be read as a simple construction cycle. It is a systems-integration cycle. Public capital can buy equipment. Only disciplined sequencing can turn the equipment into more resilient traffic management, fewer delay cascades and a platform capable of handling airlines, general aviation, drones and commercial space activity at the same time.

The latest outage exposed the real architecture

A modern airspace system is often imagined as a set of control towers and radar screens. In practice, it is a network of sensors, communications circuits, automation tools, facilities, procedures and people. A failure in one layer can reduce the capacity of the others even when every aircraft and runway remains physically available.

That dependence became visible when an accidentally severed fiber line and a failed telecommunications switch disrupted operations across the northeastern United States. Reuters reported that the event delayed or canceled around 9,500 flights and led to more than 100 diversions. The government said the planned system would add multiple telecommunications routes and remove single or dual points of failure.

The lesson is not that fiber is unreliable. It is that physical redundancy, logical redundancy and operating procedures must reinforce one another. A second cable provides little protection if it shares the same conduit, switch, power source or routing logic. A backup facility does not add resilience if the transition process is slow or if controllers cannot immediately trust the information it displays. Redundancy has to be designed as an independent operating path, not counted as a second piece of equipment.

This is the first reason the $30 billion headline can mislead investors. The value does not come from how many boxes are purchased. It comes from how many failure modes are removed. Procurement disclosures should therefore be judged against availability, failover performance and recoverability rather than against shipment volume alone.

Modernization layer Problem being solved Economic channel Residual risk
Telecommunications Aging copper, concentrated routes and fragile switches Fewer outage-driven ground stops and less delay propagation Shared conduits, carrier dependence and cutover errors
Radar and surveillance Old equipment, many configurations and difficult maintenance More reliable aircraft tracking and lower support complexity Installation sequencing, certification and vendor integration
Automation software Fragmented data and limited predictive coordination Better traffic flow, routing and use of constrained airspace Bad inputs, model limits and inconsistent facility adoption
Towers and facilities Obsolete physical infrastructure and uneven airport capability Higher local reliability and capacity where demand is binding Permitting, construction interfaces and local readiness
Controller workforce Staffing gaps, overtime and long training cycles More usable capacity from the installed technology Attrition, certification bottlenecks and fatigue

Replacing radar is easier to announce than to integrate

The radar program shows both the opportunity and the challenge. In January, the Federal Aviation Administration announced contracts with RTX and Indra to help replace up to 612 radars by June 2028. The agency said many existing systems date from the 1980s and that the new program would consolidate 14 configurations now used across the National Airspace System.

Standardization can create real value. Fewer configurations mean fewer spare-part inventories, fewer specialized maintenance paths and a simpler training burden. Commercially available components may also shorten procurement compared with bespoke systems that become technically unique before they are widely deployed. Those gains are not automatic, however. A common platform creates concentration. A defect, supply disruption or software problem can affect more sites once variation is removed.

The FAA has selected Peraton as prime integrator, while radar hardware comes from RTX and Indra. That structure gives one organization responsibility for coordinating multiple suppliers and interfaces. It can reduce the ambiguity that often appears when every contractor optimizes its own deliverable. It can also place a large amount of schedule and architecture risk at the integrator.

Success will depend on whether interface standards remain clear enough to prevent vendor lock-in without fragmenting responsibility. The government needs a system that can be maintained for decades, but it also needs suppliers willing to make firm commitments over an accelerated schedule. If technical requirements keep changing, vendors price uncertainty into contracts. If requirements are frozen too early, the program may install technology that is obsolete before the final facility is converted.

This tension resembles the financing problem discussed in Block2Learn’s analysis of AI infrastructure and public-market risk. Large demand does not eliminate construction, customer concentration or interface risk. In both cases, a compelling need can support investment before operating proof is complete. Capital becomes abundant first; evidence about utilization and execution arrives later.

The cutover is the product

A normal business can close a system for maintenance, migrate data over a weekend and accept a temporary reduction in service. Air traffic control does not have that freedom. The network must continue separating aircraft while new equipment is installed, tested and certified. Old and new systems may need to run in parallel, increasing cost and operational complexity before any savings appear.

Parallel operation is not waste. It is insurance against an incomplete transition. Controllers must be trained on the new interface while retaining competence on the legacy system. Data feeds need to reconcile. Voice communications have to remain available. Maintenance teams must support two technology stacks. Each site may require a different cutover plan because traffic, buildings, routes and equipment differ.

This creates an unusual cost curve. Spending rises before capacity does. Contractors are paid, hardware is delivered and training begins, but the operational benefit remains limited until enough connected components work together. Early program reports can therefore look inefficient even when the sequence is rational. The right question is whether milestones reduce risk, not whether every dollar immediately reduces delays.

The same principle explains why a timetable such as June 2028 should be treated as a management target rather than an economic certainty. Accelerated dates can improve accountability and concentrate resources. They can also encourage temporary workarounds or compressed testing. A safety-critical program should be fast where standardization removes needless delay and slow where evidence is required.

The distinction between equipment delivery and usable capacity is central. A radar counts as delivered when it reaches a site. It counts as installed after construction and technical work. It counts as operational only after integration, testing, certification, training and handover. Investors following contractors should separate those recognition points because revenue, cash flow and public value do not necessarily arrive together.

Tariffs reveal how policy can tax its own priority

Modernization also sits inside a broader industrial-policy framework. The administration wants more domestic production, but tariffs can raise the cost of the same equipment the government is trying to buy. Reuters reported on September 17 that tariffs were expected to add about $100 million to the $12.5 billion modernization plan, primarily through radar systems. The cost of telecommunications upgrades had also increased from $4.75 billion to $5.91 billion.

A $100 million tariff impact is small relative to a multibillion-dollar program, but it matters as evidence of policy interaction. Domestic sourcing can improve supply security and political durability. It can also require new factories, supplier qualification and higher near-term costs. RTX and Indra are moving relevant production into facilities in Florida and Kansas, according to Reuters. That may create a more resilient long-term base, but the transition consumes capital and time.

The government is therefore pursuing three objectives at once: modernize faster, source more domestically and control costs. It may not be possible to maximize all three in every procurement. A credible program should make the trade-offs explicit. Domestic capacity can be worth a premium when the component is strategically important and future demand is durable. Paying a premium without securing schedule, quality or availability is simply a transfer.

This is similar to the structure examined in Block2Learn’s critical-minerals offtake analysis. Public policy can identify a strategic need, but bankable contracts, qualified production and operating competence determine whether physical capacity appears. Aviation modernization will reward suppliers that can convert policy support into certified equipment at predictable cost.

Software can improve flow, but it cannot repair the foundation

The FAA has already begun introducing more advanced software. Reuters reported on September 21 that the agency started using an artificial-intelligence tool around Washington, D.C., under a 12-year, $875 million contract awarded to Air Space Intelligence. The system is intended to use predictive analytics to improve flight management and reduce delays, with expansion planned to other regions.

That is potentially valuable because delay is a network problem. A route decision in one region can affect aircraft, crews, gates and passengers elsewhere. Better forecasts can allow traffic managers to act before congestion becomes a queue. Airlines can benefit from more stable schedules, airports can use gates more efficiently and passengers can face fewer missed connections.

Yet software is an overlay on physical and institutional infrastructure. A model cannot create an independent communications route after a cable is severed. It cannot certify a radar or staff an understaffed facility. It can recommend an efficient plan only if data arrive on time and operators have the capacity to implement it.

Model governance also matters. Controllers and traffic managers need to understand when a recommendation is reliable, what assumptions it uses and how to reject it safely. The objective is not maximum automation. It is better human decision-making under uncertainty. A tool that performs well in ordinary traffic but behaves unpredictably during weather, outages or unusual demand may add cognitive burden precisely when the system is under stress.

Block2Learn’s work on AI defense and continuous systems offers a useful analogy. An automated model can examine a changing environment more frequently than a periodic manual process, but its value depends on integration, remediation and trusted operating rules. Detection is not resolution. Prediction is not capacity.

The workforce is part of the capital program

Hardware and software attract procurement attention because they are visible assets. Controller staffing is equally important. In April, Reuters reported that the FAA was proposing to hire 2,300 controller trainees and remained about 3,500 fully certified controllers short of targeted staffing. Many controllers were working mandatory overtime and six-day weeks, while the training academy faced retention problems.

A trainee is not an immediate unit of capacity. Recruitment, academy completion, facility training and certification take time, and not every candidate completes the path. A large hiring number can therefore coexist with an operating shortage. The pipeline must be judged by certified throughput, time to certification and retention, not applications or academy seats alone.

Modern equipment can improve the productivity and reliability of the workforce, but it can also absorb experienced staff during transition. Controllers must help validate procedures, train colleagues and operate parallel systems. Maintenance and engineering teams face the same burden. This creates a temporary labor demand inside a system that is already constrained.

The workforce problem is also a governance test. A modernization plan that assumes technology will compensate immediately for staffing gaps can overstate benefits. A staffing plan that treats technology as irrelevant can lock the system into old processes. The two investments have to be designed together. Interface quality, alert discipline and automation should reduce avoidable workload without obscuring situational awareness.

The FAA says it handles an average of 44,360 flights per day. That scale makes small improvements valuable and small design errors consequential. Saving a few minutes across thousands of movements can create large economic benefits. Adding a confusing workflow across the same volume can create a different kind of systemwide cost.

The economic return is resilience before growth

Supporters will naturally describe modernization as a capacity investment. That is true, but the first return may be fewer failures rather than more flights. Reliability protects capacity that already exists. When communications or staffing constraints force ground stops, the cost spreads through airlines, airports, cargo networks, hotels and business travel.

Aviation has tightly coupled assets. An aircraft delayed in New York may arrive late for a different route in Chicago. A crew can exceed duty limits. A gate remains occupied. Connecting passengers miss departures. The original technical problem may be local, but the economic loss compounds through schedules. Resilience reduces the probability and duration of those cascades.

Additional capacity comes later through more precise routing, better surface awareness, improved traffic-flow prediction and more reliable facilities. Those gains matter as drones and commercial space launches place new demands on shared airspace. The FAA’s own employment page lists hundreds of thousands of registered drones and more than a thousand licensed commercial space launches, illustrating how the network’s user base is broadening.

This is public infrastructure in the same sense that payment settlement is public infrastructure. Block2Learn’s analysis of central-bank settlement rails showed that the deepest value often comes from trusted coordination rather than from one transaction. Air traffic control performs a similar function in physical mobility. It supplies the shared rules and information that allow competing private operators to use scarce space safely.

The economic benefit should therefore be measured across users, not only through FAA accounts. Airlines may gain schedule integrity. Airports may use runways and gates more effectively. Cargo operators may improve reliability. Travelers may lose fewer hours. Suppliers may receive long contracts. These gains can justify investment even when the system itself does not charge a commercial return.

Public finance can fund the build, not guarantee the outcome

Congressional funding reduces financing risk but does not remove cost risk. A multiyear program faces inflation, tariffs, design changes, labor shortages and unexpected conditions at old facilities. An appropriation that appears large today can lose purchasing power before final deployment.

The increase in the telecommunications estimate demonstrates this problem. Some cost growth may reflect better information or expanded scope rather than weak control. Investors and taxpayers should still demand a transparent bridge between the old estimate and the new one. Without that bridge, it is impossible to tell whether the program is buying more resilience or paying more for the same promise.

Budget governance should also separate contingency from scope. Safety-critical infrastructure needs reserves for unexpected work. If every contingency dollar is treated as available scope, the program becomes vulnerable when a real problem appears. Conversely, excessive reserves can hide weak planning. Milestone-based release of funds can create discipline if milestones measure operating readiness rather than administrative completion.

Political time and engineering time are different. Officials want visible progress before elections and budget deadlines. Engineers need tests, certifications and staged cutovers. The prime integrator must translate between those clocks. Too little urgency prolongs dependence on fragile systems. Too much urgency can move risk from the schedule into operations.

What the investment cycle means for companies

The program creates a broad opportunity across radar, telecommunications, software, construction, cybersecurity and airport systems. The opportunity should not be confused with guaranteed margin. Government contracts can provide long revenue visibility, but accelerated schedules, fixed-price terms, domestic-production commitments and certification requirements can absorb that value.

RTX and Indra gain from radar awards, while Peraton gains a central integration role. Telecommunications providers, engineering firms and airport-equipment companies may participate through different layers. The most attractive suppliers will not simply have scarce products. They will have products that meet standards, integrate cleanly and can be delivered with credible service support.

For public-market investors, backlog quality matters more than backlog size. A contract with stable requirements, indexation and realistic milestones can support cash flow. A large contract with uncertain interfaces and aggressive penalties can destroy value even if revenue rises. Working capital is another risk: a supplier may have to hire, build inventory and invest in facilities before customer payments arrive.

Airlines are indirect beneficiaries, but their gains will vary. A more reliable network can reduce delay costs and improve asset utilization. It does not eliminate weather, airport congestion, aircraft maintenance or crew shortages. Airlines also differ in network structure. A carrier with a concentrated hub can benefit greatly from resilience at that hub while remaining vulnerable to one local constraint.

Three scenarios for the modernization cycle

Base case: disciplined progress with uneven local results

Congress provides substantial additional funding, although perhaps not the full requested amount at once. Radar and telecommunications programs advance on a rolling basis. High-traffic and fragile facilities receive priority. Some sites gain measurable reliability while others remain on legacy systems longer. Cost estimates rise moderately as field conditions become clearer. The program delivers value, but national benefits arrive gradually rather than through a single 2028 switch.

In this case, contractors convert backlog into revenue without extraordinary margins. Airlines see fewer disruption events in upgraded regions, but normal congestion remains. The most important evidence is successful cutover at complex facilities and documented failover performance.

Upside case: standardization creates a repeatable deployment engine

The prime-integrator model works. Interfaces are stable, common equipment is certified quickly and early installations generate reusable designs. Domestic radar production scales without major cost pressure. New telecommunications routes remove critical failure points, while predictive software improves traffic flow on top of the stronger foundation. Controller hiring and training improve enough to translate technology into usable capacity.

In this case, later deployments become faster and cheaper than the first wave. Reliability gains reduce delay cascades, and the program establishes an architecture flexible enough for drones and commercial space. Suppliers with proven integration records win follow-on work, while airlines capture productivity from more stable operations.

Downside case: urgency fragments the system

Funding arrives in pieces, requirements change and contractors optimize separate work packages without enough architectural control. Tariffs, labor costs and facility surprises consume contingency. Old and new systems run in parallel longer than planned. Staffing gaps limit training and cutover capacity. A serious outage or failed deployment forces the FAA to slow the schedule.

In this case, spending grows faster than resilience. Political pressure encourages more announcements, but operating evidence remains thin. Contractors face margin pressure or disputes. Airlines continue bearing delay costs, and Congress becomes less willing to fund later phases.

Invalidation and risks

The central thesis is that integration, not equipment volume, will determine the return on this investment. It would weaken if standardized commercial components can be installed with much less local variation than historical programs, if software materially automates certification and cutover, or if the prime-integrator structure proves able to absorb interface risk rapidly. Evidence of repeated on-time deployments with lower unit costs would show that execution is becoming a scalable process rather than the binding constraint.

The opposite risk is that the funding debate overstates how much can be delivered safely within the target period. More money cannot create experienced engineers, certified controllers or domestic production instantly. A compressed schedule can intensify scarcity and raise prices. The program may have to choose between speed and competition if only a few suppliers can meet requirements.

Cybersecurity is a further risk. More connected software and standardized interfaces can improve visibility while expanding the attack surface. Segmentation, authentication, monitoring and recovery must be designed into the architecture. A system that is resilient to cable cuts but vulnerable to common software compromise has moved the single point of failure rather than removed it.

Governance can also fail through measurement. If agencies report contracts awarded and equipment shipped without reporting operational readiness, policymakers may believe the risk has fallen before it has. Transparent milestones should include certified installations, successful fallback tests, trained staffing and observed service performance.

What to monitor

  • Congressional funding: how much of the $30 billion request is approved, over what period and with what restrictions.
  • Telecommunications resilience: route diversity, copper retirement, switch replacement and demonstrated failover at upgraded facilities.
  • Radar deployment: units installed and certified, not merely contracted, and progress toward reducing the 14 legacy configurations.
  • Cost bridges: explanations for changes in telecommunications, radar, tower and airport estimates, including tariffs and scope.
  • Controller pipeline: academy completion, facility certification, attrition, overtime and time required to produce fully certified staff.
  • Software evidence: measured delay or routing improvements from the AI tool, especially during weather and disruption events.
  • Supplier economics: backlog conversion, working capital, domestic-production investment, penalties and margin performance.
  • Operational incidents: whether outages become less frequent, affect fewer facilities and recover faster as upgrades progress.

The B2L interpretation

The additional $30 billion request is best understood as a bid to rebuild a coordination system, not merely to refresh government hardware. The United States needs modern radars, fiber, voice switches, software, towers and airport equipment. It also needs an architecture that connects those assets, people trained to operate them and a cutover process that preserves safety every hour of the transition.

That makes the program economically attractive and operationally unforgiving. The upside is a more resilient network that protects existing capacity, reduces delay cascades and supports new users of the airspace. The downside is a long period of elevated spending in which equipment arrives faster than integration, staffing and certification.

Investors should resist the easiest interpretation. A larger appropriation is not automatically a larger profit pool, and a larger backlog is not automatically a better contract. The durable value will accrue to suppliers that can simplify interfaces, deliver certified systems and support operations after installation. For airlines and airports, the return will appear first in fewer failures and only later in more capacity.

America can buy the components of a new air traffic control system. The decisive test is whether it can assemble them while the old system is still flying the country. To place that execution challenge inside a broader framework for risk, capital allocation and market structure, continue with the Block2Learn Learning Path.

This article is provided solely for informational and educational purposes and does not constitute financial or investment advice, a recommendation, or an offer or solicitation to buy or sell any financial instrument or digital asset. See our Financial Disclaimer.

This article was generated with the support of AI and reviewed by the Editorial Team. For more information, see our Terms of Service.


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OASIS

Oasis is an entrepreneur, investor and founder of Block2Learn, The Investor Intelligence Hub. His work sits at the intersection of financial markets, digital assets, technology and investor education. Through Block2Learn, he develops research, market intelligence and educational frameworks that bring structure to financial information and help independent investors navigate increasingly complex markets with greater knowledge and clarity.

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AIOZ Network (AIOZ) $ 0.120682 3.88%
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Renzo Restaked ETH (EZETH) $ 2,421.84 3.59%
arweave
Arweave (AR) $ 4.50 4.21%
binance-peg-dogecoin
Binance-Peg Dogecoin (DOGE) $ 0.107393 0.17%
arbitrum-bridged-wbtc-arbitrum-one
Arbitrum Bridged WBTC (Arbitrum One) (WBTC) $ 76,200.00 2.99%
starknet
Starknet (STRK) $ 0.039262 2.34%
axie-infinity
Axie Infinity (AXS) $ 1.08 5.01%
wbnb
Wrapped BNB (WBNB) $ 759.61 1.56%
dexe
DeXe (DEXE) $ 1.94 2.41%
decentraland
Decentraland (MANA) $ 0.08849 7.46%
based-brett
Brett (BRETT) $ 0.005609 7.17%
elrond-erd-2
MultiversX (EGLD) $ 4.35 3.29%
beam-2
Beam (BEAM) $ 0.002016 4.81%
aerodrome-finance
Aerodrome Finance (AERO) $ 0.695157 3.92%
usdd
USDD (USDD) $ 0.998426 0.04%
dydx-chain
dYdX (DYDX) $ 0.133394 4.89%
thorchain
THORChain (RUNE) $ 0.638795 4.57%
morpho
Morpho (MORPHO) $ 2.80 8.91%
l2-standard-bridged-weth-base
L2 Standard Bridged WETH (Base) (WETH) $ 2,266.86 3.46%
mantle-restaked-eth
Mantle Restaked ETH (CMETH) $ 2,447.46 3.67%
conflux-token
Conflux (CFX) $ 0.053819 4.69%
reserve-rights-token
Reserve Rights (RSR) $ 0.001723 5.80%
arbitrum-bridged-weth-arbitrum-one
Arbitrum Bridged WETH (Arbitrum One) (WETH) $ 2,265.06 3.52%
zcash
Zcash (ZEC) $ 1,553.66 2.40%
tether-gold
Tether Gold (XAUT) $ 4,263.10 0.54%
ether-fi-staked-btc
Ether.fi Staked BTC (EBTC) $ 76,722.00 4.00%
ai16z
ai16z (AI16Z) $ 0.000441 2.84%
ether-fi-staked-eth
ether.fi Staked ETH (EETH) $ 2,317.47 1.05%
apecoin
ApeCoin (APE) $ 0.15215 2.79%
coredaoorg
Core (CORE) $ 0.023613 3.99%
helium
Helium (HNT) $ 0.505883 3.66%
frax
Legacy Frax Dollar (FRAX) $ 0.992367 0.06%
akash-network
Akash Network (AKT) $ 0.679155 0.65%
compound-governance-token
Compound (COMP) $ 23.81 6.27%
meow
MEOW (MEOW) $ 0.000005 1.64%
usdx-money-usdx
Stables Labs USDX (USDX) $ 0.009108 0.00%
ecash
eCash (XEC) $ 0.000009 3.10%
chiliz
Chiliz (CHZ) $ 0.016427 4.04%
wormhole
Wormhole (W) $ 0.011828 4.95%
amp-token
Amp (AMP) $ 0.000505 4.06%
ultima
Ultima (ULTIMA) $ 1,835.18 2.51%
eigenlayer
EigenCloud (prev. EigenLayer) (EIGEN) $ 0.239807 2.96%
pumpbtc
pumpBTC (PUMPBTC) $ 76,077.00 2.54%
deep
DeepBook (DEEP) $ 0.020407 12.22%
resolv-usr
Resolv USR (USR) $ 0.08926 3.08%
pancakeswap-token
PancakeSwap (CAKE) $ 2.74 6.73%
pax-gold
PAX Gold (PAXG) $ 4,260.69 0.53%
gigachad-2
Gigachad (GIGA) $ 0.002387 2.53%
mina-protocol
Mina Protocol (MINA) $ 0.143703 2.50%
gnosis
Gnosis (GNO) $ 114.45 0.90%
pendle
Pendle (PENDLE) $ 2.58 4.57%
bitcoin-avalanche-bridged-btc-b
Avalanche Bridged BTC (Avalanche) (BTC.B) $ 76,260.00 3.16%
beldex
Beldex (BDX) $ 0.077314 2.15%
echelon-prime
Echelon Prime (PRIME) $ 0.231464 0.04%
zksync
ZKsync (ZK) $ 0.012068 7.65%
paypal-usd
PayPal USD (PYUSD) $ 0.999877 0.01%
havven
Synthetix (SNX) $ 0.254659 9.60%
coinbase-wrapped-staked-eth
Coinbase Wrapped Staked ETH (CBETH) $ 2,539.40 3.57%
true-usd
TrueUSD (TUSD) $ 0.9996 0.02%
stakestone-berachain-vault-token
StakeStone Berachain Vault Token (BERASTONE) $ 2,683.97 0.17%
axelar
Axelar (AXL) $ 0.051978 4.31%
tbtc
tBTC (TBTC) $ 70,942.00 7.49%
apenft
AINFT (NFT) $ 0.000000242058 0.45%
snek
Snek (SNEK) $ 0.00061 10.72%
mog-coin
Mog Coin (MOG) $ 0.000000128516 6.61%
telcoin
Telcoin [OLD] (TEL) $ 0.001639 3.89%
toshi
Toshi (TOSHI) $ 0.000129 2.83%
dydx
dYdX (ETHDYDX) $ 0.133255 4.69%
kava
Kava (KAVA) $ 0.070374 0.64%
polygon-pos-bridged-weth-polygon-pos
Polygon PoS Bridged WETH (Polygon POS) (WETH) $ 2,261.63 3.58%
newton-project
AB (AB) $ 0.000599 0.09%
notcoin
Notcoin (NOT) $ 0.000484 4.14%
chex-token
Chintai (CHEX) $ 0.010939 4.19%
bridged-usdc-polygon-pos-bridge
Polygon Bridged USDC (Polygon PoS) (USDC.E) $ 0.99972 0.00%
vethor-token
VeThor (VTHO) $ 0.000746 5.60%
frax-ether
Frax Ether (FRXETH) $ 2,262.16 2.20%
1inch
1INCH (1INCH) $ 0.100531 2.30%
trust-wallet-token
Trust Wallet (TWT) $ 0.574797 6.79%
quantixai
Quantix Finance (QFI) $ 18.52 1.95%
grass
Grass (GRASS) $ 0.437963 3.75%
stader-ethx
Stader ETHx (ETHX) $ 2,455.55 2.19%
superfarm
SuperVerse (SUPER) $ 0.174439 1.04%
terra-luna
Terra Luna Classic (LUNC) $ 0.000055 4.12%
sweth
Swell Ethereum (SWETH) $ 2,521.55 3.25%
safe
Safe (SAFE) $ 0.11207 6.64%
livepeer
Livepeer (LPT) $ 1.64 0.31%
hashnote-usyc
Circle USYC (USYC) $ 1.14 0.01%
usdb
USDB (USDB) $ 1.00 0.03%
creditcoin-2
Creditcoin (CTC) $ 0.113608 2.79%
theta-fuel
Theta Fuel (TFUEL) $ 0.010755 2.52%
oasis-network
Oasis (ROSE) $ 0.008002 5.62%
super-oeth
Super OETH (SUPEROETH) $ 2,263.65 2.59%
aixbt
aixbt (AIXBT) $ 0.022649 4.41%
kusama
Kusama (KSM) $ 4.58 5.37%
bio-protocol
Bio Protocol (BIO) $ 0.030731 8.70%
layerzero
LayerZero (ZRO) $ 1.44 5.21%
blur
Blur (BLUR) $ 0.020221 4.33%
dash
Dash (DASH) $ 63.34 9.62%
cat-in-a-dogs-world
cat in a dogs world (MEW) $ 0.000501 5.84%
ordinals
ORDI (ORDI) $ 4.61 4.30%
solayer-staked-sol
Solayer Staked SOL (SSOL) $ 112.14 4.30%
io
io.net (IO) $ 0.157855 7.00%
ondo-us-dollar-yield
Ondo US Dollar Yield (USDY) $ 1.14 0.04%
freysa-ai
Freysa AI (FAI) $ 0.002567 3.35%
arkham
Arkham (ARKM) $ 0.12861 5.74%
turbo
Turbo (TURBO) $ 0.001066 5.22%
popcat
Popcat (POPCAT) $ 0.05694 2.06%
binance-peg-busd
Binance-Peg BUSD (BUSD) $ 1.00 0.05%
olympus
Olympus (OHM) $ 20.25 0.00%
dog-go-to-the-moon-rune
Dog (Bitcoin) (DOG) $ 0.001113 1.40%
nervos-network
Nervos Network (CKB) $ 0.001398 9.91%
astar
Astar (ASTR) $ 0.007193 3.71%
just
JUST (JST) $ 0.113568 2.49%
compound-wrapped-btc
cWBTC (CWBTC) $ 1,534.90 2.99%
mx-token
MX (MX) $ 1.85 2.63%
zilliqa
Zilliqa (ZIL) $ 0.003826 5.97%
verus-coin
Verus (VRSC) $ 0.223062 3.31%
melania-meme
Melania Meme (MELANIA) $ 0.107394 3.73%
holotoken
Holo (HOT) $ 0.000433 2.56%
ai-rig-complex
AI Rig Complex (ARC) $ 0.073398 7.95%
origintrail
OriginTrail (TRAC) $ 0.376278 4.58%
liquid-staked-ethereum
Liquid Staked ETH (LSETH) $ 2,406.26 2.78%
polygon-bridged-wbtc-polygon-pos
Polygon Bridged WBTC (Polygon POS) (WBTC) $ 76,130.00 3.08%
0x
0x Protocol (ZRX) $ 0.12163 3.87%
baby-doge-coin
Baby Doge Coin (BABYDOGE) $ 0.00000000041653 4.83%
ether-fi
Ether.fi (ETHFI) $ 0.677089 4.42%
safepal
SafePal (SFP) $ 0.302364 3.06%
staked-frax-ether
Staked Frax Ether (SFRXETH) $ 2,589.68 3.62%
aethir
Aethir (ATH) $ 0.005944 1.47%
golem
Golem (GLM) $ 0.126124 4.17%
basic-attention-token
Basic Attention (BAT) $ 0.090624 3.37%
swissborg
SwissBorg (BORG) $ 0.180563 0.32%
skale
SKALE (SKL) $ 0.004565 5.52%
wemix-token
WEMIX (WEMIX) $ 0.198893 0.57%
mocaverse
Moca Network (MOCA) $ 0.01029 4.16%
xyo-network
XYO Network (XYO) $ 0.003509 1.47%
gas
Gas (GAS) $ 1.45 3.03%
celo
Celo (CELO) $ 0.092285 3.65%
benqi-liquid-staked-avax
BENQI Liquid Staked AVAX (SAVAX) $ 12.58 0.25%
qtum
Qtum (QTUM) $ 1.00 4.62%
spell-token
Spell (SPELL) $ 0.000093 3.75%
would
would (WOULD) $ 0.033815 2.46%
vine
Vine (VINE) $ 0.008192 4.38%
zencash
Horizen (ZEN) $ 7.41 3.07%
woo-network
WOO (WOO) $ 0.012785 4.75%
iotex
IoTeX (IOTX) $ 0.003644 7.77%
bridged-wrapped-ether-starkgate
Bridged Ether (StarkGate) (ETH) $ 2,241.79 5.41%
resolv-wstusr
Resolv wstUSR (WSTUSR) $ 1.13 0.06%
siacoin
Siacoin (SC) $ 0.001007 4.62%
bybit-staked-sol
Bybit Staked SOL (BBSOL) $ 112.08 4.42%
plume
Plume (PLUME) $ 0.017817 14.07%
osmosis
Osmosis (OSMO) $ 0.037305 5.49%
vana
Vana (VANA) $ 1.14 4.60%
griffain
GRIFFAIN (GRIFFAIN) $ 0.015192 1.57%
zetachain
ZetaChain (ZETA) $ 0.050305 2.12%
uxlink
UXLINK (UXLINK) $ 0.0007 1.33%
ethereum-pow-iou
EthereumPoW (ETHW) $ 0.298819 8.23%
ankr
Ankr Network (ANKR) $ 0.00495 2.54%
akuma-inu
Akuma Inu (AKUMA) $ 0.000000062459 0.15%
tribe-2
Tribe (TRIBE) $ 0.409643 0.07%
ravencoin
Ravencoin (RVN) $ 0.002409 6.09%
enjincoin
Enjin Coin (ENJ) $ 0.028052 2.33%
peanut-the-squirrel
Peanut the Squirrel (PNUT) $ 0.054502 3.46%
elixir-deusd
Elixir deUSD (DEUSD) $ 0.000977 0.00%
memecoin-2
Memecoin (MEME) $ 0.000629 6.65%
aelf
aelf (ELF) $ 0.075537 1.43%
anime
Animecoin (ANIME) $ 0.003399 3.08%
constellation-labs
Constellation (DAG) $ 0.006026 0.24%
polymesh
Polymesh (POLYX) $ 0.044212 6.23%
convex-finance
Convex Finance (CVX) $ 2.09 8.19%
drift-protocol
Drift Protocol (DRIFT) $ 0.018967 1.21%
sats-ordinals
SATS (Ordinals) (SATS) $ 0.000000011902 5.60%
venice-token
Venice Token (VVV) $ 30.98 2.36%
qubic-network
Qubic (QUBIC) $ 0.000000407923 1.01%
coinex-token
CoinEx (CET) $ 0.004999 0.03%
peaq-2
peaq (PEAQ) $ 0.042114 22.12%
threshold-network-token
Threshold Network (T) $ 0.005553 2.46%
stepn
GMT (GMT) $ 0.008698 6.35%
usda-2
USDa (USDA) $ 0.967102 0.00%

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