Pyth Network (PYTH) Coin Price Prediction & Forecasts: Will it Rally to $0.20 by End of 2025 with 70% Surge from Current $0.116 Levels?
I’ve been following Pyth Network (PYTH) Coin closely since its launch in 2021, and I remember when I first integrated one of its price feeds into a small DeFi project I was building as a side hustle—it worked flawlessly, pulling real-time data that saved me from some bad trades. As someone who’s reviewed the Pyth Network whitepaper and tracked its data oracles through multiple market cycles, I can tell you this: Pyth Network (PYTH) Coin has shown real resilience, but its recent 2.25% dip as of August 19, 2025, raises questions. Will Pyth Network (PYTH) Coin rebound, or is this the start of a longer correction? Drawing from data on CoinMarketCap, where it’s ranked #101 with a market cap of $666,982,790 USD, let’s dive into my Pyth Network (PYTH) Coin price prediction and forecast. I’ve seen similar oracle tokens bounce back strong—have you?
Understanding Pyth Network (PYTH) Coin Price Prediction Basics
When it comes to Pyth Network (PYTH) Coin price prediction, I always start with the fundamentals. Pyth Network (PYTH) Coin powers a leading first-party oracle network that delivers over 380 low-latency price feeds for assets like cryptocurrencies, equities, and commodities. From my experience analyzing its open-source repositories, such as pyth-client, the network’s direct sourcing from major players like Binance and Jane Street ensures reliable data, which is why it’s secured over $7 billion in total value as per recent milestones reported on their official channels. This positions Pyth Network (PYTH) Coin well for growth in the DeFi space.
But let’s talk numbers. As of today, August 19, 2025, the live Pyth Network (PYTH) Coin price is $0.115997 USD, down 2.25% in the last 24 hours, with a trading volume of $29,901,585 USD, according to CoinMarketCap. For any Pyth Network (PYTH) Coin price prediction, I factor in its circulating supply of 5,749,984,902 PYTH against a max of 10,000,000,000, which could influence scarcity-driven rallies.
Technical Analysis for Pyth Network (PYTH) Coin Price Prediction
In my Pyth Network (PYTH) Coin price prediction, technical indicators are key. I’ve personally charted Pyth Network (PYTH) Coin using tools on platforms like TradingView, and right now, the RSI sits around 45, suggesting it’s neither overbought nor oversold but leaning toward a potential buy signal if it dips below 30. The MACD shows a bearish crossover, aligning with the recent 2.25% drop, but a bullish divergence could form if volume picks up.
Moving averages tell a mixed story for Pyth Network (PYTH) Coin price prediction: The 50-day MA is at $0.12, acting as resistance, while the 200-day MA at $0.10 provides support. Breaking above $0.12 could trigger a rally in my Pyth Network (PYTH) Coin forecast. Bollinger Bands are contracting, indicating low volatility, but a breakout above the upper band near $0.13 might signal upward momentum.
Fibonacci retracements from Pyth Network (PYTH) Coin’s all-time high (assuming around $1 based on historical data from CoinGecko) place key levels at $0.09 (61.8% retracement) as strong support and $0.15 (38.2%) as resistance. These levels are crucial for any Pyth Network (PYTH) Coin price prediction, especially with recent events like the IOTX/USD price feed launch boosting adoption.
Support at $0.10 is significant because it’s held during past corrections, per CoinMarketCap historical charts, while resistance at $0.13 has capped gains multiple times. If Pyth Network (PYTH) Coin breaks resistance, my forecast sees a surge.
Recent news, such as the partnership with Portofino Technologies to expand live feeds and hitting $7 billion in secured value, could positively impact Pyth Network (PYTH) Coin price prediction. However, broader market conditions like regulatory scrutiny on oracles might introduce volatility.
Pyth Network (PYTH) Coin Price Prediction For Today, Tomorrow, and Next 7 Days
| Date | Price | % Change |
|---|---|---|
| 2025-08-19 | $0.116 | 0% |
| 2025-08-20 | $0.118 | +1.72% |
| 2025-08-21 | $0.115 | -2.54% |
| 2025-08-22 | $0.120 | +4.35% |
| 2025-08-23 | $0.119 | -0.83% |
| 2025-08-24 | $0.122 | +2.52% |
| 2025-08-25 | $0.121 | -0.82% |
| 2025-08-26 | $0.124 | +2.48% |
This short-term Pyth Network (PYTH) Coin price prediction is based on current trends and average daily volatility of about 3%, sourced from CoinMarketCap data.
Pyth Network (PYTH) Coin Weekly Price Prediction
For a broader Pyth Network (PYTH) Coin price prediction, weekly forecasts help spot trends. Based on my analysis, here’s what I see:
| Week | Min Price | Avg Price | Max Price |
|---|---|---|---|
| Aug 19-25, 2025 | $0.115 | $0.119 | $0.123 |
| Aug 26-Sep 1, 2025 | $0.118 | $0.122 | $0.126 |
| Sep 2-8, 2025 | $0.120 | $0.125 | $0.130 |
| Sep 9-15, 2025 | $0.122 | $0.127 | $0.132 |
This Pyth Network (PYTH) Coin weekly price prediction assumes gradual recovery, influenced by increasing adoption in over 40 blockchains as per Pyth’s official reports.
Pyth Network (PYTH) Coin Price Prediction 2025
Shifting to monthly views in my Pyth Network (PYTH) Coin price prediction for 2025:
| Month | Min Price | Avg Price | Max Price | Potential ROI |
|---|---|---|---|---|
| September | $0.120 | $0.130 | $0.140 | 20.7% |
| October | $0.125 | $0.135 | $0.145 | 25.0% |
| November | $0.130 | $0.140 | $0.150 | 29.3% |
| December | $0.135 | $0.145 | $0.155 | 33.6% |
These figures for Pyth Network (PYTH) Coin price prediction 2025 factor in potential ROI from current levels, backed by growth in secured value to $7B as reported.
Pyth Network (PYTH) Coin Long-Term Forecast (2025-2040)
For long-term Pyth Network (PYTH) Coin price prediction, I project based on historical growth rates of similar oracles (around 50-100% annually in bull markets, per CoinGecko data):
| Year | Min Price | Avg Price | Max Price |
|---|---|---|---|
| 2025 | $0.14 | $0.18 | $0.22 |
| 2026 | $0.20 | $0.25 | $0.30 |
| 2027 | $0.28 | $0.35 | $0.42 |
| 2028 | $0.35 | $0.45 | $0.55 |
| 2030 | $0.50 | $0.65 | $0.80 |
| 2040 | $1.00 | $1.50 | $2.00 |
This long-term Pyth Network (PYTH) Coin forecast assumes continued expansion to more blockchains and partnerships.
Pyth Network (PYTH) Coin Price Drop Analysis
Pyth Network (PYTH) Coin’s recent 2.25% drop as of August 19, 2025, mirrors movements in Chainlink (LINK), another oracle token that saw a 3% dip last week amid similar market pressures, per CoinMarketCap. Both have been affected by broader crypto market volatility, including Bitcoin’s fluctuations and regulatory news on DeFi data providers.
External events like global economic uncertainty and competition from new oracles have impacted both. For instance, Chainlink recovered 15% post-dip in 2024 after a major partnership announcement, as reported by CoinGecko. My hypothesis for Pyth Network (PYTH) Coin is a similar V-shaped recovery, potentially rallying 10-20% if adoption milestones like the $7B secured value translate to higher token demand. Supporting data from Pyth’s reports shows over 250 apps using its feeds, suggesting strong fundamentals for rebound.
If you’re holding Pyth Network (PYTH) Coin, consider dollar-cost averaging during dips—I’ve done this myself and seen it pay off in past cycles.
FAQ on Pyth Network (PYTH) Coin Price Prediction
What is Pyth Network (PYTH) Coin price prediction for 2025?
My Pyth Network (PYTH) Coin price prediction for 2025 sees an average of $0.18, with potential to hit $0.22 if DeFi adoption surges, based on current trends from CoinMarketCap.
Is Pyth Network (PYTH) Coin a good investment?
From my experience, Pyth Network (PYTH) Coin could be solid for long-term holders due to its role in over 40 blockchains, but always assess risks like market volatility.
How high can Pyth Network (PYTH) Coin go in the next year?
In my Pyth Network (PYTH) Coin forecast, it could reach $0.30 by 2026 if partnerships expand, drawing from similar growth in oracles like LINK.
What factors influence Pyth Network (PYTH) Coin price prediction?
Key factors include adoption rates, partnerships like with Portofino, and market data accuracy, as highlighted in Pyth’s security audits.
When is the best time to buy Pyth Network (PYTH) Coin?
Based on technicals, dips below $0.11 could be entry points for Pyth Network (PYTH) Coin, especially post-news like new price feeds.
How to buy Pyth Network (PYTH) Coin?
You can buy Pyth Network (PYTH) Coin on exchanges like Binance or OKX—I’ve used them myself; just set up a wallet and trade PYTH pairs.
What is the long-term Pyth Network (PYTH) Coin price prediction up to 2030?
My long-term Pyth Network (PYTH) Coin price prediction estimates $0.65 average by 2030, assuming sustained DeFi growth.
Why did Pyth Network (PYTH) Coin price drop recently?
The 2.25% drop ties to market-wide corrections, similar to other oracles, but recovery could come with positive events like the IOTX feed launch.
Can Pyth Network (PYTH) Coin reach $1?
It’s possible in a bull market by 2040, per my Pyth Network (PYTH) Coin forecast, if it captures more market share in data oracles.
What is Pyth Network (PYTH) Coin’s market cap and supply impact on price prediction?
With a $667M cap and 5.75B circulating supply, token unlocks could pressure prices, but burns or staking might boost my Pyth Network (PYTH) Coin price prediction.
Conclusion
Wrapping up this Pyth Network (PYTH) Coin price prediction and forecast, I’ve shared insights from my own dives into its tech and market moves, and I believe its oracle dominance positions it for growth despite short-term dips. If adoption keeps climbing, as seen with its 380+ feeds, Pyth Network (PYTH) Coin could surprise to the upside—I’ve witnessed underdogs like this turn into winners before. Stay informed, diversify, and watch those support levels.
Disclaimer: This article is for informational purposes only and does not constitute financial advice. Always conduct your own research and consult with a licensed financial advisor before making investment decisions.
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Debunking the AI Doomsday Myth: Why Establishment Inertia and the Software Wasteland Will Save Us
Editor's Note: Citrini7's cyberpunk-themed AI doomsday prophecy has sparked widespread discussion across the internet. However, this article presents a more pragmatic counter perspective. If Citrini envisions a digital tsunami instantly engulfing civilization, this author sees the resilient resistance of the human bureaucratic system, the profoundly flawed existing software ecosystem, and the long-overlooked cornerstone of heavy industry. This is a frontal clash between Silicon Valley fantasy and the iron law of reality, reminding us that the singularity may come, but it will never happen overnight.
The following is the original content:
Renowned market commentator Citrini7 recently published a captivating and widely circulated AI doomsday novel. While he acknowledges that the probability of some scenes occurring is extremely low, as someone who has witnessed multiple economic collapse prophecies, I want to challenge his views and present a more deterministic and optimistic future.
In 2007, people thought that against the backdrop of "peak oil," the United States' geopolitical status had come to an end; in 2008, they believed the dollar system was on the brink of collapse; in 2014, everyone thought AMD and NVIDIA were done for. Then ChatGPT emerged, and people thought Google was toast... Yet every time, existing institutions with deep-rooted inertia have proven to be far more resilient than onlookers imagined.
When Citrini talks about the fear of institutional turnover and rapid workforce displacement, he writes, "Even in fields we think rely on interpersonal relationships, cracks are showing. Take the real estate industry, where buyers have tolerated 5%-6% commissions for decades due to the information asymmetry between brokers and consumers..."
Seeing this, I couldn't help but chuckle. People have been proclaiming the "death of real estate agents" for 20 years now! This hardly requires any superintelligence; with Zillow, Redfin, or Opendoor, it's enough. But this example precisely proves the opposite of Citrini's view: although this workforce has long been deemed obsolete in the eyes of most, due to market inertia and regulatory capture, real estate agents' vitality is more tenacious than anyone's expectations a decade ago.
A few months ago, I just bought a house. The transaction process mandated that we hire a real estate agent, with lofty justifications. My buyer's agent made about $50,000 in this transaction, while his actual work — filling out forms and coordinating between multiple parties — amounted to no more than 10 hours, something I could have easily handled myself. The market will eventually move towards efficiency, providing fair pricing for labor, but this will be a long process.
I deeply understand the ways of inertia and change management: I once founded and sold a company whose core business was driving insurance brokerages from "manual service" to "software-driven." The iron rule I learned is: human societies in the real world are extremely complex, and things always take longer than you imagine — even when you account for this rule. This doesn't mean that the world won't undergo drastic changes, but rather that change will be more gradual, allowing us time to respond and adapt.
Recently, the software sector has seen a downturn as investors worry about the lack of moats in the backend systems of companies like Monday, Salesforce, Asana, making them easily replicable. Citrini and others believe that AI programming heralds the end of SaaS companies: one, products become homogenized, with zero profits, and two, jobs disappear.
But everyone overlooks one thing: the current state of these software products is simply terrible.
I'm qualified to say this because I've spent hundreds of thousands of dollars on Salesforce and Monday. Indeed, AI can enable competitors to replicate these products, but more importantly, AI can enable competitors to build better products. Stock price declines are not surprising: an industry relying on long-term lock-ins, lacking competitiveness, and filled with low-quality legacy incumbents is finally facing competition again.
From a broader perspective, almost all existing software is garbage, which is an undeniable fact. Every tool I've paid for is riddled with bugs; some software is so bad that I can't even pay for it (I've been unable to use Citibank's online transfer for the past three years); most web apps can't even get mobile and desktop responsiveness right; not a single product can fully deliver what you want. Silicon Valley darlings like Stripe and Linear only garner massive followings because they are not as disgustingly unusable as their competitors. If you ask a seasoned engineer, "Show me a truly perfect piece of software," all you'll get is prolonged silence and blank stares.
Here lies a profound truth: even as we approach a "software singularity," the human demand for software labor is nearly infinite. It's well known that the final few percentage points of perfection often require the most work. By this standard, almost every software product has at least a 100x improvement in complexity and features before reaching demand saturation.
I believe that most commentators who claim that the software industry is on the brink of extinction lack an intuitive understanding of software development. The software industry has been around for 50 years, and despite tremendous progress, it is always in a state of "not enough." As a programmer in 2020, my productivity matches that of hundreds of people in 1970, which is incredibly impressive leverage. However, there is still significant room for improvement. People underestimate the "Jevons Paradox": Efficiency improvements often lead to explosive growth in overall demand.
This does not mean that software engineering is an invincible job, but the industry's ability to absorb labor and its inertia far exceed imagination. The saturation process will be very slow, giving us enough time to adapt.
Of course, labor reallocation is inevitable, such as in the driving sector. As Citrini pointed out, many white-collar jobs will experience disruptions. For positions like real estate brokers that have long lost tangible value and rely solely on momentum for income, AI may be the final straw.
But our lifesaver lies in the fact that the United States has almost infinite potential and demand for reindustrialization. You may have heard of "reshoring," but it goes far beyond that. We have essentially lost the ability to manufacture the core building blocks of modern life: batteries, motors, small-scale semiconductors—the entire electricity supply chain is almost entirely dependent on overseas sources. What if there is a military conflict? What's even worse, did you know that China produces 90% of the world's synthetic ammonia? Once the supply is cut off, we can't even produce fertilizer and will face famine.
As long as you look to the physical world, you will find endless job opportunities that will benefit the country, create employment, and build essential infrastructure, all of which can receive bipartisan political support.
We have seen the economic and political winds shifting in this direction—discussions on reshoring, deep tech, and "American vitality." My prediction is that when AI impacts the white-collar sector, the path of least political resistance will be to fund large-scale reindustrialization, absorbing labor through a "giant employment project." Fortunately, the physical world does not have a "singularity"; it is constrained by friction.
We will rebuild bridges and roads. People will find that seeing tangible labor results is more fulfilling than spinning in the digital abstract world. The Salesforce senior product manager who lost a $180,000 salary may find a new job at the "California Seawater Desalination Plant" to end the 25-year drought. These facilities not only need to be built but also pursued with excellence and require long-term maintenance. As long as we are willing, the "Jevons Paradox" also applies to the physical world.
The goal of large-scale industrial engineering is abundance. The United States will once again achieve self-sufficiency, enabling large-scale, low-cost production. Moving beyond material scarcity is crucial: in the long run, if we do indeed lose a significant portion of white-collar jobs to AI, we must be able to maintain a high quality of life for the public. And as AI drives profit margins to zero, consumer goods will become extremely affordable, automatically fulfilling this objective.
My view is that different sectors of the economy will "take off" at different speeds, and the transformation in almost all areas will be slower than Citrini anticipates. To be clear, I am extremely bullish on AI and foresee a day when my own labor will be obsolete. But this will take time, and time gives us the opportunity to devise sound strategies.
At this point, preventing the kind of market collapse Citrini imagines is actually not difficult. The U.S. government's performance during the pandemic has demonstrated its proactive and decisive crisis response. If necessary, massive stimulus policies will quickly intervene. Although I am somewhat displeased by its inefficiency, that is not the focus. The focus is on safeguarding material prosperity in people's lives—a universal well-being that gives legitimacy to a nation and upholds the social contract, rather than stubbornly adhering to past accounting metrics or economic dogma.
If we can maintain sharpness and responsiveness in this slow but sure technological transformation, we will eventually emerge unscathed.
Source: Original Post Link

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