Why WAL Token Could 3–5x in 2026 – My Quick Take
As we kick off 2026, here’s a quick reality check on WAL Coin. The price recently dipped to around $0.13 amid broader market noise, but the fundamentals are strengthening fast.
Some key points to consider:
Circulating Supply: ~1.58B out of a max 5B, with smart vesting schedules helping prevent sudden dumps.
User Retention Moves: Walrus extended the Tusky migration to March—a smart play to keep users engaged.
Partnerships: Quiet but meaningful collaborations in prediction markets and ad tech are building real-world usage.
AI Data Infrastructure: Perhaps the most exciting part: WAL is positioned perfectly for the growing demand for verifiable AI data. Combining Sui’s speed with Walrus’s efficiency creates low-cost, censorship-resistant storage—something traditional cloud providers can’t match on privacy.
Scarcity Potential: If adoption accelerates (Q2 SEAL expansions could help), fee- and staking-driven token burns may create real scarcity.
In short, WAL isn’t just hype—it’s infrastructure with legs. Not financial advice, but for me, dips like this are compelling entry points.
What about you—bullish or waiting?
@WalrusProtocol #walrus $WAL
Why Plasma Makes $XPL Matter
Plasma isn’t about flashy features or buzzwords—it’s about making stablecoin payments genuinely usable. The focus is simple: smooth sending, transparent fees, and no extra hassle for users.
When moving digital dollars becomes easy and reliable, XPL becomes more than just a token—it’s the engine that supports the system behind the scenes. It’s not about hype or big promises; it’s about real, everyday use cases that make crypto practical for anyone.
For me, that’s what counts. I’m more interested in tools people can actually use than in headlines that fade by tomorrow. Plasma XPL isn’t flashy—but it could be essential.
#plasma $XPL @Plasma
For a long time, Web3 has treated privacy and regulation like they can’t exist together. Projects usually pick one and ignore the other. That’s why Dusk caught my interest.
Dusk isn’t trying to hide from rules, and it’s not turning finance into a glass box either. It’s built as a Layer 1 where privacy and compliance are part of the base design. Sensitive data stays protected, but audits and checks are still possible when required.
This really matters for RWAs. Institutions want assets on-chain, but they don’t want their positions, identities, or strategies exposed. Dusk’s approach allows that balance: private by default, accountable when needed. It feels less like rebellion and more like real financial infrastructure.
#dusk $DUSK @Dusk_Foundation
Most blockchains focus on speeding up transactions. Walrus takes a different route by optimizing the data layer itself. Through erasure coding, parallel data retrieval, and intelligent distribution, Walrus transforms decentralized storage into a high-performance foundation built for gaming, AI, and rich media. As Web3 applications become more data-heavy and complex, this design choice could prove critical.
#walrus $WAL @WalrusProtocol
$BANANAS31 /USDT on Binance (15m).
Since you didn’t ask a direct question, I’ll give you a quick read, then you tell me what you want next (signal, entry, scalp, or just explanation).
Quick take (from what you shared)
Price: 0.004286
24h change: +6.09% → bullish momentum intraday
24h High: 0.004426
24h Low: 0.003985
Volume:
BANANAS31: ~1B (high, speculative interest)
USDT: ~4.28M
Timeframe shown: 15m → short-term / scalp context
What this suggests
Lately, I’ve been noticing a strong convergence in the Web3 narrative, one where decentralized compute, data infrastructure, AI networks, and DePIN real-world layers are starting to form an interconnected foundation.
Each of these projects tackles a different bottleneck of the centralized internet:
$FLT (Fluence) is building the decentralized compute marketplace, letting developers deploy backend logic without relying on #AWS or GCP. It’s the missing layer between DePIN devices and onchain AI.
$AKT (Akash) and $TAO (Bittensor) push open-access AI and #GPU compute to new levels.
$PYTH brings verified, real-world data onchain — a crucial link for intelligent, autonomous systems.
$PEAQ expands the network to machines and physical infrastructure, enabling verifiable real-world input.
Together, these ecosystems are sketching the next architecture for trustless coordination, where intelligence, computation, and infrastructure don’t depend on a single entity.
Fluence stands out because it connects these pieces: it’s where applications actually run. Not just data feeds or GPUs — but logic, APIs, and #AIagents that live on open protocols.
We’re slowly watching the decentralized cloud become a living system, compute as commons, not a product.