Can PEPE Regain Its Lost Glory? You Should See This TCT Distribution Model

bitcoinistPublished on 2026-05-07Last updated on 2026-05-07

PEPE is trying to hold its place in the meme coin market after months of weaker momentum, but a new technical setup shows that the next move may be decided by a narrow support zone. The latest chart analysis shared by crypto analyst Lars Koostra on X shows the meme coin reacting from a demand area.

PEPE Holds Demand, But The TCT Model Still Warns Of Distribution

The analysis is built around a TCT model, which analyst Lars Koostra says has now been confirmed. The question now is whether it can defend the current demand point of interest or whether the token is setting up for a deeper bearish rotation back into range lows.

The technical chart shows PEPE trading around 0.00000400, with its price bouncing from what the analyst describes as the only demand POI currently preventing a full bearish rotation. This is the final support area keeping the structure from completing the downside move projected by the TCT model.

Source: Chart from Lars Koostra on X

The TCT model points out that the meme coin has already shown signs of distribution near the upper part of the range. The price action previously moved into the higher supply area in late April but failed to break cleanly above it, confirming the analyst’s view that demand is below the current price.

Therefore, the recent bounce does not automatically invalidate the bearish structure. It only delays it until PEPE either breaks higher with strength or loses the support now holding the market together. Speaking of the recent bounce, the meme coin is currently trading with a 4.8% increase in the past 24 hours and a 5.5% increase in the past seven days.

Extreme Supply Could Decide Whether The Bounce Has Real Strength

The chart’s red projection shows PEPE possibly pushing higher into extreme supply before reversing lower. This upper resistance band visible on the chart is sitting in the $0.000004130 to $0.000004200 region.

This makes the extreme supply area the next major test for the meme coin. A weak reaction there would support the bearish TCT model and keep the range-low target around $0.0000037 alive. The analyst noted that if it retraces into extreme supply, they would look to refine an entry and add risk only after high-quality confirmations.

A stronger move above that zone, however, would begin to weaken the distribution case and lead to a reassessment of whether PEPE is building a larger recovery. At the time of writing, PEPE is trading at $0.000004268. On the other hand, the meme coin is still down by 47% on a one-year basis despite gaining more than 26% over the past month. That creates a mixed setup.

The monthly rebound shows traders are slowly moving into PEPE, but the larger decline shows that the token has not yet reclaimed its lost glory. The TCT distribution model says that PEPE may still need to complete a deeper liquidity move before any stronger recovery can develop.

PEPE trading at $0.000004 on the 1D chart | Source: PEPEUSDT on Tradingview.com

Trending Cryptos

Related Reads

Vitalik's Algorithmic Stablecoin Vision: Interpreting the Mechanism and Challenges from an Options Perspective

Vitalik Buterin's recent algorithmic stablecoin proposal envisions using an option-like mechanism to create a stablecoin without the liquidation risks inherent in traditional collateralized debt position (CDP) models. The design splits one unit of ETH into two components: a 'stable' leg (P) that maintains value up to a certain strike price, and an 'upside' leg (N) that captures any appreciation above that price. Together, they always sum to one ETH, eliminating the need for debt or liquidation mechanisms. From an options perspective, the stable leg essentially functions as a synthetic, covered call position. However, significant challenges exist. For the stable asset to maintain its peg, it must continuously roll deep in-the-money call options, leading to potential rollover slippage, predictable trading paths vulnerable to front-running, and liquidity issues. Crucially, the system's scalability depends on a constant demand for the upside leg—a form of leveraged ETH long position without funding rates or liquidation risk. It's unclear if such persistent, specific demand will materialize from speculators or market makers who have simpler alternatives like perpetual swaps. The author, drawing from experience with Rysk, argues that DeFi options have struggled as standalone trading products due to complexity and fragmented liquidity. Their potential lies instead as foundational infrastructure underpinning more complex financial primitives like stablecoins, structured yields, or index products—transforming from a direct product into a core pricing and risk distribution engine for the next generation of on-chain finance.

marsbit1h ago

Vitalik's Algorithmic Stablecoin Vision: Interpreting the Mechanism and Challenges from an Options Perspective

marsbit1h ago

GPT-5.6 Countdown: Abandon the Illusion of a Single API, Computational Iteration Can't Outpace a Single Page of Compliance

In mid-June, three seemingly independent industry events—the compliance-driven throttling of Fable 5, the open-sourcing of GLM-5.2, and the leaked release timeline for GPT-5.6—are pushing the global AI industry toward a watershed moment. These shifts signal a fundamental restructuring of the industry's underlying logic. First, **"usability" has substantially overtaken "advanced capabilities"** as the primary weight, pushing the global large language model (LLM) supply chain into a "dual-track" phase of controlled closed-source and local open-source coexistence. Second, **the competitive moats of closed-source giants are shifting**. Their technical focus is moving from "language intelligence" toward "spatial intelligence (world models)"—a domain heavily reliant on computing power. Third, faced with常态化 transnational compliance risks, **a "model-agnostic" decoupled design has become a survival necessity for application-layer developers to maintain business continuity.** The article details how Anthropic's Fable 5, despite its advanced engineering feats, was restricted for non-U.S. citizens within 72 hours of launch, highlighting how geopolitical compliance can instantly limit even the most advanced models. In response, the open-source camp, exemplified by Zhipu AI's MIT-licensed GLM-5.2, is gaining market share by offering stable performance improvements and significant cost advantages (up to 70% savings for enterprises), while achieving full adaptation with domestic semiconductor platforms. Meanwhile, closed-source leaders like OpenAI are pivoting. The anticipated GPT-5.6 reportedly shifts focus from language to spatial intelligence and world models, aiming to rebuild a generational gap in areas like 3D understanding, simulation, and industrial design that demand immense compute. The core conclusion is that the LLM supply chain's logic has changed. Enterprises must now evaluate infrastructure based on a composite of technical performance and policy compliance. For developers, complete reliance on a single closed-source API poses unacceptable risk. Implementing a truly model-agnostic architecture—enabling swift switches to compliant, locally deployable open-source alternatives—is no longer just good practice but a fundamental baseline for business continuity.

marsbit4h ago

GPT-5.6 Countdown: Abandon the Illusion of a Single API, Computational Iteration Can't Outpace a Single Page of Compliance

marsbit4h ago

Is the 'Token Subsidy War' Among AI Giants Almost Over?

The article discusses the ongoing "token subsidy war" among AI giants like OpenAI and Anthropic, questioning whether it's nearing its end. It reveals that current AI subscription prices are heavily subsidized, with some plans offering tokens at up to 70 times the actual cost to attract and retain heavy users, especially developers and enterprises. This strategy mirrors past internet-era subsidy battles, but with a key difference: AI tokens lack "lock-in" effects. Unlike ride-hailing or food delivery apps, users can easily switch between AI providers as APIs become standardized, making it difficult for companies to raise prices post-subsidy. The piece highlights a structural asymmetry in the competition. Giants like Google, with massive advertising revenue, can afford to subsidize tokens indefinitely, akin to using "tokens as a weapon." In contrast, venture-backed companies like OpenAI and Anthropic face pressure to become profitable, especially as they approach IPO. The article cites Google Ventures founder Bill Maris, who suggests Google could slash token prices by 80%, putting immense pressure on competitors. Two potential endgames are presented: the "internet service" model (subsidize, monopolize, then raise prices) and the "utility" model (tokens become a standardized, low-margin commodity like electricity). Given the low switching costs, the latter seems more likely. The competition may not have a single winner but could instead accelerate AI's evolution into a foundational, infrastructure-level technology, akin to a public utility. For now, users continue to benefit from heavily subsidized token costs.

marsbit4h ago

Is the 'Token Subsidy War' Among AI Giants Almost Over?

marsbit4h ago

Trading

Spot
Futures

Hot Articles

Discussions

Welcome to the HTX Community. Here, you can stay informed about the latest platform developments and gain access to professional market insights. Users' opinions on the price of MEME (MEME) are presented below.

活动图片