Every crypto app needs data. Very few need the same data.

A portfolio tracker asks what an address holds. A DeFi dashboard asks what a protocol holds. A trading terminal asks what a token trades at right now. Those are three different products.

Picking by brand name is how teams end up paying twice. Picking by question is how they stop.

This guide covers five crypto data APIs. Each one answers a different question well. CoinStats Crypto API leads on wallet, market and DeFi data. DefiLlama covers protocol economics. Codex handles real-time DEX and prediction market data. Glassnode measures the network. Blockscout returns the raw record, decoded.

Our guide to choosing the right crypto API also covers swaps and nodes. This one stays in the data lane.

Not All Crypto Data Is the Same Data

Five kinds of question sit behind the word “data”. Each has its own providers.

Portfolio data answers questions about an address. Balances, positions and value, already priced.

Protocol data answers questions about a protocol. Total value locked, fees, revenue and yields.

Market data answers what something trades at. Prices, candles, liquidity and holder flows.

Network data answers what participants are doing together. Supply distribution, cost basis and exchange flows.

Record data answers what actually happened. Decoded transactions, event logs and verified contract code.

A node gives you none of this. It gives you bytes. This primer on how a blockchain API works explains the gap.

1. CoinStats API (Best Overall)

One API for Markets, Wallets, DeFi and Portfolio Data

CoinStats Crypto API is a unified data layer for developers. It combines market data, wallet data, DeFi positions and portfolio analytics. Token security screening sits in the same schema. Coverage spans 100,000+ coins, 200+ exchanges and 120+ blockchains.

Wallet endpoints return balances and transactions across Ethereum, Solana, EVM chains and Bitcoin. Bitcoin support includes extended public keys (xpub, ypub, zpub). DeFi positions resolve per wallet across 10,000+ protocols. That covers staking, lending and liquidity tied to one address.

Token risk checks flag honeypots, hidden fees, blacklists and unrenounced ownership. Those checks run on EVM chains.

CoinStats API also ships an MCP Server for AI agents. It exposes wallet, DeFi and portfolio data to LLMs. Agents in Claude, Cursor and VS Code query it directly. That portfolio layer is the real differentiator. This best crypto API guide breaks down the endpoints.

Pros

• Market, wallet, DeFi, portfolio and token security in one API
• 120+ blockchains and 100,000+ coins under one key
• Per-wallet DeFi resolution across 10,000+ protocols
• Bitcoin xpub, ypub and zpub support
• Native MCP Server for AI and LLM workflows
• Free tier with credit-based pricing

Cons

• Read-only data layer, so no transaction submission
• REST-first, with no streaming for live event data

Best Use Cases

• Multi-chain portfolio trackers
• DeFi dashboards across staking, lending and LP
• Crypto tax and accounting tools
• AI agents that query data through MCP
• Wallet explorers and embedded widgets

Pricing

Pricing is credit-based with a free tier at signup. Paid plans start at $49 per month. Credits scale with endpoint complexity.

Best suited for: most data-driven builds, from portfolio trackers to AI agents.

Limitation: CoinStats API is a data layer, not a node provider. To broadcast transactions, pair it with RPC infrastructure.

2. DefiLlama

Free Protocol Economics Across Thousands of Protocols

DefiLlama tracks the economics of DeFi itself. It publishes total value locked, fees, revenue, yields and stablecoin supply. Coverage runs across hundreds of chains and thousands of protocols. The methodology is open source, so anyone can audit a number.

The open plan is genuinely free and needs no key. It returns TVL, revenue and fee data plus token prices. Most TVL figures quoted elsewhere trace back to it.

A developer API plan runs $300 per month. It allows 1,000 requests per minute and 1 million calls monthly. Extra calls cost $0.60 per thousand after that. A separate $49 Pro plan covers dashboards rather than API access.

DefiLlama also ships an MCP server plus installable agent skills. Each agent query costs one credit from the same API pool.

Best suited for: yield tools, DeFi dashboards and protocol research.

Limitation: DefiLlama works at protocol level, not wallet level. For per-address positions, pair it with CoinStats API.

3. Codex

Real-Time DEX Data and Prediction Markets in One Schema

Codex is an enriched blockchain data API with two pillars. Do not confuse it with the coding tool of the same name. The first pillar is tokens: real-time prices, OHLCV charts, holder analytics and balances. The second is prediction markets across Polymarket and Kalshi, now at record volume.

Odds, volume, trending events and order books share a single schema. Coverage reaches 70M+ tokens, 700M+ wallets and 80+ networks.

Access runs on GraphQL with WebSocket subscriptions and webhooks. Data freshness sits near one second. TradingView, Coinbase, Uniswap and pump.fun all build on it. A TypeScript SDK, an MCP server and agentic payments cover AI workflows.

The free tier allows 10,000 requests per month with full query access. Growth plans start at $350 per month.

Best suited for: trading terminals, token discovery and prediction market apps.

Limitation: Codex reads onchain markets, not exchange balances or DeFi positions. Pair it with a portfolio layer.

4. Glassnode

Network-Level Metrics for Research Teams

Glassnode measures what a whole network is doing. Its catalogue covers supply distribution, cost basis, profitability and exchange flows. Entity-adjusted metrics strip out transfers between wallets with one owner. That single correction changes most raw onchain numbers.

Coverage spans 1,500+ assets and onchain data from 11 blockchains. The Advanced plan costs $49 per month. It includes 300+ metrics at daily resolution plus API Light access. Professional adds longer history, 10-minute resolution and a credit-based API add-on.

Glassnode ships an MCP server, a CLI and an Excel add-in. Agents can also pay per call in USDC on Base. Metric calls cost five cents with no account required.

Point-in-time metrics never get revised, which keeps backtests honest. That pay-per-call route is new, and it suits research agents well.

Best suited for: research desks, market dashboards and macro-style analysis.

Limitation: Glassnode has no free plan and reads networks, not wallets.

5. Blockscout

Open-Source Explorer Data With a Real Free Tier

Blockscout is the open-source block explorer, exposed as an API. It returns decoded transactions, balances, event logs and verified contract ABIs. One key covers 120+ chains on every plan, free included. Endpoints follow the Etherscan V2 shape, so migrating is mostly a URL swap.

The free plan gives 100,000 credits per day at five requests per second. Builder costs $49 per month for 100 million credits. Pro costs $199 per month at 30 requests per second. Most standard calls spend 20 credits each. Keys come from the developer portal with no card required.

An MCP server runs on the same backend, alongside installable agent skills. The explorer stays open source, so any chain can self-host it. Teams debugging contracts get the same data their users see. Response headers return remaining credits on every call.

Best suited for: wallets, debugging tools and contract-level analytics.

Limitation: Blockscout returns chain records, not aggregated market data.

Side-by-Side Comparison

What You Can Build

Portfolio trackers and wallet apps. CoinStats API returns holdings, prices and DeFi positions in one call.

Yield and treasury dashboards. DefiLlama supplies pool APYs, protocol fees and stablecoin supply.

Trading terminals and token screeners. Codex streams live pair data across 80+ networks.

Prediction market products. Codex normalises Polymarket and Kalshi into one schema.

Research and market reports. Glassnode supplies cost basis, supply and flow metrics.

Contract debuggers and audit tools. Blockscout decodes transactions and serves verified ABIs.

AI financial assistants. Every provider here now ships an MCP server for agents.

One Provider or Several?

Most production teams do not run on a single API. They layer by question.

Start with CoinStats API for wallet, market, DeFi and portfolio data. Add DefiLlama when you need protocol economics behind those positions. Add Codex when live DEX pricing or prediction markets matter. Layer in Glassnode when the question turns to whole-network behaviour. Reach for Blockscout when you need the decoded record itself.

Two providers cover most products. Three is common at scale. Developers publish their own comparisons too. This hands-on developer comparison is worth a read.

Wrapping Up

There is no single best crypto data API. There is only the right answer to your question.

CoinStats API is the broadest starting point for application data. It suits most crypto use cases, from trackers to AI agents. DefiLlama owns protocol economics and stays free. Codex owns real-time DEX and prediction market data. Glassnode owns network-level research. Blockscout owns the decoded record.

Four of the five start free. Test the free tiers with real calls before you commit.

Bitcoin BTC$63,588.88 continues to trade in a narrow price band, and two of its biggest corporate believers aren’t blinking.

Simon Gerovich, CEO of Metaplanet, and Michael Saylor, executive chairman of Strategy, two of the cryptocurrency’s biggest corporate holders, have doubled down on their argument that BTC’s maximum issuance of 21 million coins beats infinite money printing, whatever the price is doing this week.

On Sunday, Gerovich noted that the global M2 money supply has reached an all-time high of over $100 trillion, calling it a bullish long-term tailwind for the cryptocurrency.

“Bitcoin’s price has decoupled from liquidity over the past year. But supply schedules don’t change,” Gerovich said. “21 million will always be 21 million. When the money supply expands forever, you hold the asset that can’t. That’s why we hold hard money.”

Bitcoin’s price has decoupled from broader liquidity expansion over the past year. Even as M2 money supply swelled, BTC has nearly halved to $63,500. The divergence is consistent with previous market cycles, in which bearish trends bitcoin’s price temporarily detached from rising macroeconomic liquidity.

Saylor voiced a similar opinion in a different framing. He said that understanding bitcoin requires first understanding money itself.

Artificial intelligence, Web3, scientific research, gaming, and increasingly sophisticated applications all share one critical requirement: compute.

For decades, computing power has largely been controlled by centralized cloud providers and hyperscale data centers. Companies rent servers, GPUs, and storage from a relatively small number of providers, while those providers manage the infrastructure, pricing, capacity, and geographic distribution.

But a new economic model is emerging: decentralized compute.

Instead of concentrating computing resources in a handful of massive data centers, decentralized compute networks connect independent hardware providers and make unused or underutilized computing capacity globally accessible.

The technology is interesting—but the economics may be even more important.

What Is Decentralized Compute?

Decentralized compute is a model in which computing resources are supplied by a distributed network of independent participants rather than by a single centralized provider.

These resources can include:

• GPUs
• CPUs
• Storage
• Bandwidth
• Specialized AI accelerators
• Gaming hardware
• Data-center capacity
• Edge devices

A decentralized compute marketplace can match compute suppliers with compute consumers.

The basic economic relationship is straightforward:

Providers supply computing capacity → networks coordinate that capacity → users pay for computation → providers earn rewards.

Blockchain and smart contracts can add another layer by enabling transparent accounting, automated payments, reputation systems, and programmable incentives.

The result is potentially a global marketplace where computing power becomes something that can be bought, sold, and coordinated much like other digital resources.

Why Compute Is Becoming a Scarce Resource

The rise of AI has dramatically changed the economics of computing.

Training and running advanced AI models can require enormous amounts of GPU capacity. At the same time, demand is expanding across inference, video generation, autonomous systems, scientific computing, gaming, simulations, and enterprise applications.

This creates a supply-demand problem.

Large centralized providers can invest billions in infrastructure, but building data centers and acquiring advanced GPUs takes time. Hardware shortages, energy requirements, cooling constraints, and geographic limitations can further restrict supply.

Decentralized networks approach the problem differently.

Instead of asking:

“How do we build another massive data center?”

the decentralized model asks:

“How much computing power already exists but isn’t being fully utilized?”

That is a very different economic question.

Turning Idle Hardware Into an Economic Asset

One of the most interesting ideas behind decentralized compute is resource utilization.

A gaming PC may sit idle for most of the day.

A workstation may only use its GPU heavily for a few hours.

A data center may have unused capacity.

A business may own infrastructure that is underutilized during certain periods.

Decentralized compute networks can potentially aggregate this unused capacity and make it available to customers.

This creates a new economic relationship:

Idle capacity → marketplace → revenue opportunity.

For hardware owners, the network creates a way to monetize an asset they already own.

For compute buyers, it potentially creates another source of capacity outside traditional cloud infrastructure.

And for the network itself, every additional provider can increase available supply.

The Core Economics: Supply, Demand, and Price

At the center of decentralized compute is a marketplace.

Compute providers want higher utilization and better returns on their hardware.

Compute buyers want reliable capacity at competitive prices.

The market therefore needs to find an equilibrium between the two.

If demand for GPUs increases faster than supply, compute prices can rise.

If large amounts of unused hardware enter the market, prices may fall.

This dynamic creates an important competitive advantage for decentralized networks: they can potentially respond to demand by aggregating additional supply instead of relying exclusively on centralized infrastructure expansion.

However, cheaper compute is not automatically better compute.

Price is only one part of the equation.

The Real Cost of Decentralized Compute

The headline price of a GPU hour doesn’t tell the whole story.

Providers have to consider:

• Electricity
• Hardware depreciation
• Cooling
• Maintenance
• Internet connectivity
• Hardware failures
• Capital expenditure
• Opportunity cost
• Network fees
• Operational risk

A provider earning $0.50 from an hour of computation isn’t necessarily profitable if that hour costs $0.60 in electricity and hardware depreciation.

This means decentralized compute networks need sophisticated pricing mechanisms.

A sustainable marketplace must eventually answer:

What is the true cost of supplying compute?

That cost can vary dramatically depending on geography, energy prices, hardware generation, utilization rates, and workload type.

GPUs Are Not Commodities

Another economic challenge is that compute capacity isn’t perfectly interchangeable.

A high-end GPU isn’t equivalent to an older GPU.

A GPU optimized for AI workloads isn’t necessarily ideal for gaming or rendering.

Even two identical GPUs can produce different economics depending on electricity prices and network connectivity.

This makes decentralized compute more complicated than a simple commodity market.

Compute marketplaces may eventually develop highly granular pricing based on:

GPU model + performance + availability + location + reliability + workload + duration.

In other words, the market could begin treating compute capacity as a differentiated financial resource rather than a generic commodity.

The Role of Blockchain

Blockchain isn’t required to build a distributed computing network.

But it can provide useful economic infrastructure.

A blockchain-based system can potentially handle:

1. Automated Payments

Providers can receive compensation based on completed workloads.

Smart contracts can automate payment flows without requiring a centralized intermediary to manually reconcile every transaction.

2. Transparent Accounting

On-chain records can make payments, rewards, and certain network activities auditable.

3. Incentive Design

Tokens can be used to coordinate participants by rewarding providers for supplying valuable resources.

4. Reputation

Networks can create reputation mechanisms that reward reliable providers and penalize poor performance.

5. Global Participation

Crypto-native payment systems can make it easier for participants in different regions to interact with the same marketplace.

But tokenization alone doesn’t create a viable economy.

The underlying compute must actually be useful.

That distinction is critical.

The Token Incentive Trap

One of the biggest risks facing decentralized compute networks is excessive dependence on token incentives.

Imagine a network paying providers highly attractive token rewards.

More providers join.

Hardware supply increases.

The network appears to grow rapidly.

But if real customers aren’t paying for computation, the economics may be artificial.

Once token emissions decline, providers may leave.

This creates a crucial distinction between:

subsidized supply and real economic demand.

A sustainable decentralized compute network needs customers who are willing to pay because the compute itself provides value—not simply because participants are speculating on a token.

The strongest networks will therefore be those where revenue from actual compute demand can eventually support provider economics.

Decentralized Compute vs. Traditional Cloud

Traditional cloud computing has several major advantages.

Centralized providers offer:

• Predictable performance
• Standardized hardware
• Professional support
• Established security
• High availability
• Mature developer tooling

Decentralized networks face challenges in each of these areas.

However, decentralized compute can compete in different ways.

Potential advantages include:

• Access to otherwise idle hardware
• More diverse geographic distribution
• Potentially lower prices
• Permissionless participation
• Flexible supply
• Alternative infrastructure for developers
• Reduced dependence on a handful of providers

The future may not be about centralized compute versus decentralized compute.

It could be about a hybrid market where businesses use centralized infrastructure for mission-critical workloads while decentralized networks provide additional capacity for suitable workloads.

The Importance of Verification

There is one major problem with decentralized compute:

How do you know the work was actually completed correctly?

A centralized cloud provider can control the entire execution environment.

A decentralized network cannot necessarily assume every provider is honest.

Providers could potentially:

• Return incorrect results
• Fail to complete workloads
• Manipulate performance reports
• Disappear during computation
• Attempt to exploit workloads

Therefore, decentralized compute requires economic and technical mechanisms for verification.

These could include:

• Redundant computation
• Proof systems
• Reputation scores
• Random audits
• Staking and slashing
• Trusted execution environments
• Cryptographic verification

This introduces another economic layer.

Verification has a cost.

The network must balance security against efficiency. If verifying every computation costs almost as much as performing the computation itself, decentralization loses some of its economic advantage.

Reliability Becomes an Economic Product

Centralized cloud providers effectively sell more than computing power.

They sell reliability.

A decentralized compute marketplace therefore needs to make reliability measurable.

Imagine two providers:

Provider A: cheap but unreliable.

Provider B: slightly more expensive but consistently available.

A rational market may pay Provider B a premium.

This creates the possibility of a compute reputation economy where providers build valuable histories based on:

• Uptime
• Speed
• Accuracy
• Latency
• Successful workloads
• Hardware quality
• Response time

Over time, reputation itself could become an economic asset.

Geography Matters

Compute economics are increasingly tied to geography.

Electricity costs differ dramatically between countries and regions.

Cooling requirements differ by climate.

Internet connectivity varies.

Regulatory environments differ.

Some locations may therefore become natural hubs for decentralized compute.

A network capable of intelligently routing workloads toward economically efficient locations could reduce costs.

For example, compute-intensive workloads might favor regions with inexpensive electricity, while latency-sensitive applications may prioritize geographic proximity to users.

This creates an interesting future possibility:

Compute markets could become geographically optimized in real time.

The Energy Question

Decentralized compute also raises an unavoidable question:

Who pays for the electricity?

Every computation consumes energy.

For AI and GPU-heavy workloads, energy can represent a significant portion of operating costs.

If decentralized compute grows dramatically, networks will increasingly compete not just for GPUs but also for cheap and reliable energy.

This could create new relationships between:

• Renewable energy producers
• Data centers
• Mining facilities
• AI infrastructure
• Compute marketplaces
• Distributed GPU networks

In the long term, energy and compute markets may become increasingly interconnected.

From Compute Marketplace to Compute Economy

The biggest opportunity may extend beyond simply renting GPUs.

A mature decentralized compute ecosystem could develop multiple economic layers.

Hardware Providers

Supply GPUs, CPUs, storage, and other resources.

Compute Aggregators

Combine fragmented capacity into usable infrastructure.

Developers

Build applications that consume decentralized resources.

Verification Providers

Ensure workloads are executed correctly.

Network Operators

Coordinate supply, demand, reputation, and payments.

Investors

Finance hardware deployment and infrastructure expansion.

Users

Pay for applications powered by decentralized compute.

Together, these participants create something larger than a marketplace.

They create a compute economy.

The Future of AI May Be More Distributed

AI is one of the strongest potential drivers of decentralized compute.

Inference demand could eventually become enormous as AI moves into:

• Personal assistants
• Autonomous applications
• Gaming
• Robotics
• Financial systems
• Content creation
• Scientific research
• Consumer devices

Not every AI workload needs to run inside a hyperscale data center.

Some workloads can potentially be distributed across a network of specialized machines.

This creates an opportunity for decentralized infrastructure to become an alternative layer underneath the expanding AI economy.

What Will Determine Success?

The decentralized compute sector won’t be won simply by whoever has the most GPUs.

The winning networks will likely be those that solve the economic coordination problem.

They need to answer five fundamental questions:

1. How do we attract reliable compute supply?

Providers need attractive and sustainable economics.

2. How do we attract real customers?

Demand must come from useful applications rather than speculation.

3. How do we verify computation?

Users need confidence that workloads were executed correctly.

4. How do we price compute efficiently?

Pricing must reflect hardware, energy, reliability, latency, and demand.

5. How do we make the experience simple?

Developers should not need to understand the underlying complexity of the network.

The best decentralized infrastructure may eventually feel almost identical to centralized cloud infrastructure from the user’s perspective.

The decentralization happens underneath the surface.

The Bigger Picture

The economics of decentralized compute are ultimately about turning fragmented resources into coordinated infrastructure.

There are millions of machines around the world with computing capacity that is not being fully utilized. At the same time, demand for computing continues to expand through AI, Web3, gaming, scientific research, and digital applications.

The opportunity is to connect these two sides.

But decentralization isn’t magic.

A successful network must make the numbers work for everyone involved.

Providers need profitable economics.

Users need competitive prices.

Developers need reliable infrastructure.

Networks need sustainable revenue.

And verification needs to remain affordable.

If these pieces come together, decentralized compute could evolve from an experimental Web3 concept into a genuine infrastructure market.

The most important shift may not be the creation of another blockchain token.

It may be the transformation of compute from a centralized service into an open, programmable, globally traded resource.

And in an economy increasingly powered by artificial intelligence, that resource could become one of the most valuable commodities of the digital age.

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Bitcoin cloud mining offers investors an alternative to buying BTC directly, allowing users to access mining power without owning or maintaining physical rigs.

There’s one question every Bitcoin investor eventually asks: Aside from buying BTC directly at market price, are there other ways to earn Bitcoin? The answer is yes — Bitcoin cloud mining.

Cloud mining offers a way for users to participate in Bitcoin mining by purchasing cloud computing power, without having to own or maintain their own mining rigs. This article will explain the basic principles of Bitcoin cloud mining, the equipment and operational barriers associated with home mining, and how ASDeFi uses centralized infrastructure to provide users with a more convenient Bitcoin mining experience.

Part 1: Understanding Bitcoin and mining

Bitcoin is a decentralized cryptocurrency that is not controlled by a central bank or any single entity; instead, transactions are collectively verified and recorded through a global network of computers.

Mining is a crucial mechanism for maintaining network security and the accuracy of the ledger. Miners solve complex mathematical problems through computation; upon successful completion, they can add a new block to the blockchain and receive a Bitcoin reward. Currently, the reward per block is 3.125 BTC, and a new block is generated approximately every 10 minutes on average.

Part 2: Why Bitcoin has a fixed supply — and why it matters

One of Bitcoin’s most important economic characteristics is that its total supply is capped at 21 million coins. This rule is hard-coded into its protocol, and the rate at which new Bitcoins are issued is gradually reduced through a “halving” mechanism that occurs approximately every four years. A fixed supply and a gradually decreasing rate of new issuance are key economic features of Bitcoin, but this does not guarantee that prices will rise; its market price remains subject to a variety of factors, including demand, macroeconomic conditions, and the regulatory environment.

Part 3: Issues with buying Bitcoin directly

Buying Bitcoin directly requires careful consideration of the timing of the purchase, and since Bitcoin prices are highly volatile, it’s easy to end up buying at the peak or selling out of panic. Cloud mining, on the other hand, offers an alternative approach: users can gradually accumulate BTC through ongoing hashrate services, eliminating the need to constantly assess the best time to buy and thereby reducing the pressure associated with market timing.

Part 4: Why home mining is no longer feasible

Bitcoin mining has become highly specialized and large-scale. Individual miners not only need to purchase expensive ASIC miners but also bear costs related to electricity, space, cooling, equipment maintenance, and round-the-clock operations, while also requiring a certain level of technical expertise. In today’s highly competitive mining environment, the cost of residential electricity often cannot compete with the low-cost energy available to large-scale mining farms, further increasing the financial burden on individual miners.

Part 5: What is cloud mining?

Cloud mining is a model that allows individual investors to participate in Bitcoin mining through the computing power of professional data centers, without the need to purchase and operate ASIC mining rigs themselves. The platform handles the procurement, deployment, power supply, cooling, maintenance, software updates, and mining pool management of the mining rigs, while users receive mining rewards based on the computing power shares they purchase and can view relevant data through their accounts.

Part 6: Introduction to ASDeFi Cloud Mining and guide to getting started

Founded in 2020 and headquartered in the United Kingdom, ASDeFi is a cryptocurrency mining platform specializing in AI-powered cloud computing power. Leveraging global green energy mining facilities and an AI-powered computing power scheduling system, it automates computing power allocation and revenue settlement.

The sign-up process is very straightforward:

1. Visit official ASDeFi website and complete the account registration.

Registered users receive a $15 in cash for free; they can earn $0.60 per day through mining.

2. Complete Account Setup

Deposit cryptocurrency and link the cryptocurrency wallet address for withdrawals.

3. Select a Hashrate Contract

Go to the Contracts page and, based on your budget and investment plan, select a hashrate contract with the desired term, amount, and returns.

4. View Operation Status

Once the contract purchase is complete, the system runs automatically. View account and earnings data via the web or mobile app, and manage earnings.

Example of a hashrate contract:

Summary

As Bitcoin mining becomes increasingly specialized, individual investors who purchase mining rigs on their own face multiple costs related to equipment, electricity, cooling, and technical maintenance. Cloud mining, on the other hand, lowers the barrier to entry for individuals by leveraging professional infrastructure, allowing users to participate in Bitcoin hashrate services without owning physical mining rigs. Through hashrate resource management and automated operations, ASDeFi offers users interested in this model an alternative way to participate in the Bitcoin ecosystem.

For more information, visit the official website.

Bitcoin BTC$63,501.46 steadied above $63,000 on Monday, clawing back a fraction of last week’s losses with a 0.8% gain since midnight UTC.

Without an obvious catalyst, the largest cryptocurrency appears to be tracking U.S. equities. Nasdaq 100 index futures are up 0.5% to their highest point since July 2.

Any positive reading will need to take into account last week’s net $390 million outflow from spot exchange-traded funds, including the first three-day stretch since the end of July. That was the largest weekly withdrawal from U.S. spot bitcoin products in six weeks.

Ether ETH$1,900.99 ETFs flows were limited, and solana (SOL) ETFs bucked the trend with their strongest weekly inflows since mid-May.

The bigger picture is the Clarity Act. Galaxy Research’s head of research, Alex Thorn, cut his odds of the landmark crypto bill becoming law in 2026 to roughly 10% on Aug. 14, joining prediction markets that now put the probability at around 17%. A cloture vote is scheduled for Sept. 15 when the Senate returns from recess, although market observers are expecting another delay.

Derivatives positioning

• Taker ratio stays balanced: the 24-hour long-short volume ratio for takers hangs in balance again, extending Friday’s trend. Takers are entities that pull liquidity from the order book by trading at available prices.
• Thin liquidity raises swing risk: BTC’s notional open interest, at $48 billion, is now nearly double its 24-hour trading volume. XRP’s market shows a similar pattern. That gap means any mass liquidation event could run into thin liquidity, raising the odds of wild price swings.
• BTC OI pulls back, XRP holds firm: in contract terms, BTC’s open interest (OI) has pulled back to 750,000 BTC from Friday’s 760,000 BTC. That’s been a pattern since April, with spikes above 750,000 BTC often proving short-lived. XRP futures show the opposite dynamic, with OI holding steady at 10-month highs. Positioning in ETH and SOL remains relatively light in comparison.
• CC shows bearish buildup: Canton Network’s CC token has dropped over 1.5% in 24 hours, making it one of the biggest losers among the top 100 coins by market value. OI in futures tied to the token has risen more than 5% over the same period. That combination points to shorts, or bearish bets, being built up. Negative annualized perpetual funding rates and a negative OI-adjusted 24-hour cumulative volume delta (CVD) both support that read, indicating bears are leading the market.
• ZEC bucks the trend: Privacy-focused ZEC is also an OI gainer. In this case, a positive 24-hour CVD, is a sign bulls are being more aggressive, taking longs via market orders rather than passive limit orders. ZEC’s funding rate is also positive at +10%, indicating a growing bias toward bullish bets.
• Volatility and fear stay low: Bitcoin and ether’s 30-day implied volatility indexes remain pinned near year-to-date lows, suggesting fear levels and demand for options-based insurance against price swings are both muted. Wall Street’s VIX tells a similar story, sitting at its lowest level since January.
• Options positioning leans bullish near-term: On Deribit, the skew for BTC and ETH shows a bid for calls, or bullish bets, at the front end of the curve. The implied volatility term structure shows no signs of short-term stress either, despite Wednesday’s scheduled release of the Fed minutes.
• Volume rankings show a split: 24-hour volume rankings show a mixed profile, with both BTC calls and puts among the top five most-traded instruments. The same holds for ether.

Token talk

• Pump.fun PUMP$0.002888 is one of the standout performers on Monday, adding 7.80% since midnight UTC with daily trading volume rising 55% to $90 million.
• ZEC has gained 4.70% since midnight at $508, extending a notable stretch for privacy coins following XMR’s strong run last week.
• MORPHO advanced by 5% at $2.07, reversing some of Friday’s weakness and leading the DeFi names higher.
• HYPE rose 3.53% to $59.08, continuing its steady grind and now up around 2% on the week.
• FET is one of the weakest altcoins on Monday, down 1.56% since midnight at $0.1196, giving back some of last week’s gains as AI-adjacent tokens lose momentum.
• CoinMarketCap’s “Altcoin Season” indicator is at 46/100, recovering from the Aug. 7 low of 36/100 as optimism slowly returns to the altcoin sector. CoinMarketCap’s Fear and Greed index sits at 38/100, a “fear” reading.

How the theft happened