Release date: March 3, 2025
Author: BlockBeats Editorial Team

Over the past 24 hours, the crypto market has witnessed multifaceted dynamics ranging from macroeconomic discussions to specific ecosystem developments. Mainstream topics have centered on the leap in capabilities of small models and the trend toward local deployment, disputes over the boundaries of collaboration between AI companies and governments, and energy price fluctuations and risk premium reassessments triggered by sudden events in the Middle East; meanwhile, phased breakthroughs in quantum computing have been incorporated into long-term technological competition frameworks. In terms of ecosystem development, Ethereum is advancing its ePBS and anti-MEV roadmap, Base is accelerating its deployment of AI Agent infrastructure and on-chain incentive quantification mechanisms; prediction markets are intensifying competition in trading volume and rule transparency, with Nasdaq signaling entry; Perp DEX, leveraging its 7×24 trading capability, has strengthened its institutional advantages amid macroeconomic volatility.

I. Mainstream Topics

The Alibaba Qwen team has released the Qwen3.5 small model series, covering 0.8B, 2B, 4B, and 9B parameter versions, emphasizing “smarter with less computation.” It supports multimodal capabilities, architectural optimizations, and extended reinforcement learning training. The official team highlights its suitability for edge device scenarios: the 4B version is ideal for lightweight agent applications, while the 9B version delivers performance close to much larger models. Developer tests show that the 2B model with 6-bit quantization can run smoothly on iPhone via MLX acceleration, with support for inference toggling; many users interpret this as “powerful agents that run locally,” recommending deployment with tools like LM Studio. Comparative data indicates that the 4B model performs similarly to the previous generation’s 80B A3B, while the 9B model is benchmarked against higher-parameter open-source models; the 0.8B and 2B versions are considered well-suited for offline mobile use cases.

The debate in overseas communities centers on whether there is a gap between the model's true capabilities and its marketing claims. Some supporters argue that the leap in small model performance signifies that AI is genuinely moving toward localized and decentralized deployment, unlocking unprecedented capabilities for edge computing and personal devices; critics, however, caution that benchmark results do not equate to stable performance in complex real-world scenarios, particularly in long-chain reasoning and complex decision-making tasks, where small models still exhibit clear limitations.

Behind different perspectives lies a long-standing tension: there has never been a unified standard for evaluating the balance between model scale, benchmark performance, and real-world application capability. As the narrative of “small but powerful” gains prominence, the industry both seeks to move beyond scale worship and struggles to let go of its reliance on test scores—this structural contradiction continues to persist.

Anthropic’s decision to refuse collaboration with the U.S. Department of Defense has sparked ongoing turmoil in the industry. Subsequently, Sam Altman released internal emails clarifying OpenAI’s boundaries of cooperation, including no development of autonomous weapons without human oversight, no participation in domestic surveillance targeting U.S. citizens, and no provision of services to specific intelligence agencies. He also acknowledged that the pace of prior contract disclosures had been too hasty, and urged against viewing Anthropic as a supply chain risk. Commentators cited the view that Anthropic’s excessive use of “nuclear weapon” analogies to elevate its stature has instead drawn heightened government scrutiny, representing a “hype tax.” Some analyses suggest this upheaval is not an isolated incident but the result of long-term strategic communication missteps, potentially costing policy influence and lost revenue. Meanwhile, media reports note that after Anthropic launched its “memory migration” tool, some users have begun migrating to Claude.

The core of the disagreement lies in how AI companies should navigate the relationship between national security and business ethics. Supporters of OpenAI emphasize that "responsible collaboration within a democratic framework" is the realistic path, viewing Anthropic’s stance as overly idealistic or even arrogant; supporters of Anthropic see it as a symbol of commitment to privacy and principles, criticizing OpenAI for continually shifting its boundaries under commercial pressure. Some more neutral observers argue that while the government’s response has indeed been forceful, corporate strategic messaging has also lacked prudence.

This upheaval reveals an unavoidable structural tension between AI companies and governments: when technology is granted "strategic" significance, any excessive self-mythologizing or opaque contractual arrangements amplify public distrust. The industry urgently needs clearer, auditable ethical frameworks; otherwise, the gap between commercial expansion and value promises will only widen.

The Financial Times revealed that Israel has infiltrated Tehran’s traffic camera systems for years to monitor relevant personnel, ultimately carrying out a precise strike against Iran’s Supreme Leader. Subsequently, some analysts noted that the United States is restructuring its military posture in the Gulf, potentially pushing Iran further into China’s sphere of influence, while Israel deepens its integration with Gulf nations; others believe that, in a future multipolar order, cryptocurrencies could emerge as a new geopolitical settlement layer. Following the incident, international oil prices declined significantly, and the geopolitical risk premium previously priced into crypto markets evaporated.

The debate centers on whether so-called "geopolitical realignment" truly exists. One side argues that it is a sign of the accelerating formation of a multipolar order, with U.S. military influence retreating at the margins and regional powers reshuffling, making the logic of crypto assets as an alternative settlement layer clearer; the other side questions whether this grand narrative lacks direct evidence, suggesting that markets are primarily hedging against short-term risks rather than entering a new phase of "precise strategizing."

The differing interpretations reflect a deeper issue: in an environment of highly pervasive intelligence warfare, any sudden action could trigger sharp fluctuations in energy and financial markets. The frequent inclusion of crypto assets in "geopolitical hedging" narratives underscores that the limitations of the traditional financial system in sanctions and settlement have not yet been resolved, and the transition toward multipolarity remains fragile and uncertain.

A long-form article titled “SUPERPOSITIONED: Quantum Situational Awareness” highlights that quantum computing surpassed decades-old technological thresholds in 2025, including key milestones such as optimized error-correction algorithms, while mapping hundreds of billions of dollars in government and private-sector investments and the evolving landscape of major players, and envisioning its potential applications in drug discovery and complex optimization. The author positions it as an ongoing, living industry draft.

Community disagreements center on the prioritization between quantum technology and AI narratives. Some believe quantum computing has crossed a critical threshold and will develop in parallel with AI, particularly holding strategic significance in quantum security and high-complexity computing. Others argue that these discussions lack actionable investment pathways or practical implementation, remaining largely at the level of broad visions.

The underlying issue reveals the fragmentation of information structures: the quantum field is highly specialized, with scarce and dispersed public resources, leading to delayed public understanding. In an AI-dominated舆论 environment, quantum narratives struggle to gain sustained attention and lack a systematically integrated platform; this structural imbalance may slow cross-disciplinary collaboration.

Claude Code, by Anthropic, has launched a voice mode, rolling out to users in phases. Users can hold the space bar to speak and release it to automatically transcribe; it supports mixed voice and text input, is included at no extra cost, and transcription usage does not count against quotas, available for Pro, Team, and Enterprise plans.

Community discussions have centered on feature completeness and extensibility. Supporters argue that this seamless embedded voice input significantly reduces prompt costs and improves workflow efficiency; however, more users are requesting the addition of voice output functionality, as well as open SDK and API interfaces to enable integration with other products.

Discussions from different perspectives point to a common trend: AI tools are shifting from purely text-based interactions to multimodal experiences, yet gradual rollouts and phased deployments raise questions about fairness and accessibility. As features spread through "gray release" methods, user experiences become stratified—balancing the pace of innovation with universal user access has become a new challenge in product evolution.

II. Major Ecosystem Updates

1. Vitalik explains the Glamsterdam roadmap: ePBS enables decentralized block building

Vitalik Buterin further breaks down the ePBS mechanism in Ethereum’s Glamsterdam upgrade, proposing to strip block building rights from proposers and outsource them to a permissionless open market to prevent builder power from infiltrating the staking layer. The roadmap also incorporates the FOCIL mechanism, where 16 random attesters enforce transaction inclusion to enhance censorship resistance, with plans to expand coverage and further diminish the builder’s role through Big FOCIL. Additionally, it includes encrypted mempools to mitigate toxic MEV (such as sandwich attacks), network-level anonymization (e.g., privacy routing via Tor or mixnets), and a long-term vision for decentralized block building aimed at reducing the cost of transactions dependent on global state.

The community widely views ePBS as a key signal of Ethereum’s strengthening of decentralization and MEV resistance, with the path from ePBS to FOCIL and then to Big FOCIL reflecting a systematic decomposition of block-building power. Some commentators argue that this evolution signifies a shift from block building dominated by a few participants toward a more commoditized market structure; others note that network-level anonymization and encrypted mempools still require broader client and protocol support. One perspective summarizes it as: “The evolution from ePBS to FOCIL and then to Big FOCIL clearly demonstrates that Ethereum is systematically weakening the power of centralized participants until block building becomes a commodity.”

This roadmap signals the ongoing evolution of Ethereum's infrastructure toward censorship resistance and decentralized architecture, but uncertainties remain regarding its complexity and technical implementation.

2. Venice AI became an OpenClaw recommended model provider (now the recommendation has been removed), accelerating the Base AI Agent ecosystem

Erik Voorhees previously announced that Venice AI would be the recommended model provider for the OpenClaw framework on the Base chain, highlighting its privacy-first local inference capabilities and suggesting the use of GLM 4.6 as an alternative to the default Llama 3.3 model; however, this recommendation has since been removed from the official documentation. Meanwhile, the Base Builder Quest has concluded, attracting over 125 OpenClaw AI Agent projects and distributing 5 ETH in rewards, with projects spanning prediction markets, bounty systems, free token distribution tools, AI lifecycle NFTization, digital clone interactions, and liquidity management.

The community generally views this series of actions as a signal that the Base AI Agent ecosystem is transitioning from concept to building a standardized tech stack, with the integration of privacy-preserving inference and on-chain autonomous agents forming a replicable pathway. Some commentators suggest this creates room for open-source collaboration and framework integration; others note that Venice is not a fully private architecture, as data may still be accessible by network nodes, and the removal of recommended content has sparked discussions about the stability of partnerships. Related comments state: “We hope to integrate this into our crypto-native OpenClaw fork.”

Base is building an AI Agent infrastructure centered on privacy-first principles, but model selection and partnership stability remain potential variables.

3. Brian Armstrong: Base Builder Codes quantify the on-chain traffic contribution of each application.

Coinbase CEO Brian Armstrong has launched the Base Builder Codes mechanism (based on ERC-8021), enabling applications and protocols to tag on-chain user origins through transaction suffix labels, thereby quantifying their referral contributions. Developers must register a unique code NFT, bind metadata and a revenue address, and integrate via the official library. This mechanism is set as the sole basis for future reward programs, with projects such as Aerodrome and Moonwell already adopting it.

The community generally interprets this move as a structural upgrade of Base’s incentive mechanism, shifting from subjective judgment to on-chain verifiable data, with the belief that quantifying influence can provide a more transparent basis for reward distribution. Some commentators view it as an attempt toward meritocracy; others note that retroactive attribution of contributions and transaction tagging still require careful evaluation for privacy concerns. A representative response is: «based».

Builder Codes point to a long-term direction centered on data-driven growth and incentive restructuring, but the privacy costs and definitions of fairness still require validation.

1. Kalshi Election Center launches, weekly volume of $2.72B surpasses Polymarket

Kalshi has launched an Election Real-Time Tracking Hub, integrating AP voting data with platform trading information to enable dynamic monitoring across multiple markets. Data shows its weekly trading volume reached $2.72 billion, surpassing Polymarket’s $2.4 billion and ranking first in the market. Meanwhile, Kalshi’s CEO announced settlement rules for markets related to Khamenei, specifying that settlements will be based on the last traded price before death and that all fees will be refunded, emphasizing avoidance of direct profit from death outcomes.

The community generally views leading trading volume as a sign of accelerating convergence between traditional prediction markets and on-chain trading patterns, and believes that transparent settlement logic helps enhance transparency. Some commentators criticized the rules for previously lacking clarity, potentially affecting trust; others viewed it as a public stress test under high-intensity conditions. Related comments stated: "Kalshi and Polymarket are leading the market, with a clear gap forming between the third-place player and the top two."

Prediction markets are evolving toward real-time data integration and rule transparency, but the boundaries of institutional design remain uncertain.

2. Bloomberg reports that Nasdaq is attempting to enter the prediction market (binary options)

Bloomberg reports that Nasdaq plans to launch binary options products linked to the Nasdaq-100 Index, using a yes/no contract structure with price ranges from $0.01 to $1 to reflect market probability expectations. This would mark Nasdaq’s first official foray into prediction market-related products and is still subject to approval by the U.S. Securities and Exchange Commission.

The community generally views this as traditional exchanges acknowledging the product form of prediction markets, believing institutions are incorporating probabilistic trading into compliant frameworks. Some commentators see this as a sign that prediction markets are entering the mainstream financial system; others note it is closer to a compliant version of the crypto platform’s approach. Comments state: “Nasdaq is replicating Polymarket with more complex steps.”

Nasdaq's entry is a key variable in predicting the institutionalization and mainstream adoption of prediction markets, but the pace of regulatory approval still determines its final form.

Bloomberg cites Hyperliquid data to show 24/7 trading value.

Bloomberg reported that Hyperliquid has set a new record for open interest in futures markets related to traditional assets, highlighting how its 7×24 trading mechanism allows traders to maintain continuous exposure to assets such as oil during geopolitical events, when traditional markets are closed over the weekend. The report describes it as a complement to traditional trading hours through on-chain derivatives.

The community widely views this as a structural signal of crypto-native platforms absorbing demand for traditional asset trading, and believes that 24/7 trading capabilities demonstrate institutional advantages in environments of macroeconomic volatility. Some commentators note that this may signify that round-the-clock trading is becoming the new normal. A representative comment states: “As open interest (OI) for traditional asset futures on perpetual DEXs hits record highs amid escalating geopolitical volatility, this is gradually becoming a new常态.”

Hyperliquid's expansion reinforces the trend of perp DEXs evolving into global macro risk-hedging tools, but the sustainability of its growth still depends on market conditions and the density of risk events.

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