Solana OI And Weighted Funding Rate Crash To Levels Not Seen Since 2023

bitcoinistPublished on 2026-03-04Last updated on 2026-03-04

Abstract

Solana has experienced a significant decline, with its price falling over 71% from its all-time high of $291 in January 2025. Key metrics such as Open Interest and Weighted Funding Rate have also dropped to multi-year lows. Open Interest, which reflects market activity, has plummeted from a peak of $17.1 billion to under $4.9 billion, indicating reduced investor interest. The Weighted Funding Rate, which influences trader positions, has also fallen to its lowest level in more than a year and remains mostly negative, meaning short traders are currently paying to maintain their positions. Both metrics underscore the ongoing bearish trend in the Solana market.

After hitting an all-time high of $291 back in January 2025, Solana has begun what has been a year of steady declines. While there have been some relief bounces along the way, the main direction has been downward. At the time of writing, the price of Solana is now sitting more than 71% below its all-time high levels. Other major metrics have also seen significant declines during this time, with Open Interest and Weight Funding Rate falling to two-year lows.

Solana Open Interest And Weighted Funding Rate Reflect The Bear Trend

According to data from the Coinglass website, the Solana open interest had actually peaked long after its price hit its peak, which is usually not the case. The open interest topped out at $17.1 billion, nine months after the price hit its all-time high. However, in the five months following the open interest hitting a new high, things have changed drastically.

The website shows that Solana’s open interest has now crashed below $5 billion, sitting at $4.89 billion at the time of writing. Interestingly, the open interest has followed closely with the price decline, and the crash below $100 for the first time since January 2024 has triggered a cascade.

Since open interest measures the open contracts on an asset, it is often a signal of how much attention a coin is getting. With the open interest sitting so low, it suggests that investors are not taking as many bets on Solana as they used to. This is normal in bear markets, when investors are still fearful and wait to see the market improve before jumping back in again.

Source: Coinglass

In the same vein, the weighted funding rate has taken a nosedive. Similar to the open interest, the funding rate had hit a new all-time high back in 2025 before moving downward again, and has now hit its lowest level in more than one year.

The funding rate is essentially what traders pay to hold perpetual positions, with long traders paying short traders when the rates are positive and short traders paying long traders when the rates are negative. Simply put, the funding rate can encourage traders to open positions in different directions in favor of not paying fees.

Currently, the Solana weighted funding rate is fluctuating between positive and negative. However, it has been mostly negative with the decline in price. This means that currently, short traders are paying to keep their positions open.

SOL still trending below $90 | Source: SOLUSDT on Tradingview.com

Trending Cryptos

Related Questions

QWhat is the current price of Solana compared to its all-time high, and by what percentage has it declined?

AThe current price of Solana is more than 71% below its all-time high of $291.

QWhat are the two major Solana metrics that have fallen to two-year lows according to the article?

AThe two major metrics are Open Interest and Weighted Funding Rate.

QAt what value did Solana's Open Interest peak, and what is its value now?

ASolana's Open Interest peaked at $17.1 billion and is now at $4.89 billion.

QWhat does a negative funding rate indicate about who is paying fees in the perpetual futures market?

AA negative funding rate indicates that short traders are paying long traders to keep their positions open.

QWhat event triggered a cascade in the Solana market according to the article?

AThe price of Solana crashing below $100 for the first time since January 2024 triggered a cascade.

Related Reads

Ethereum Q1 2026 Report: Fees Decline, Users and Transaction Volume Hit New Highs

Ethereum Q1 2026 Report: Fees Down, Users & Transactions Hit New Highs Token Terminal's Q1 2026 report on Ethereum presents a pivotal development: the network achieved record highs in monthly active users (13.2M, +85.9% YoY), total transactions (200.4M, +81.5% YoY), and throughput (25.78 TPS), while transaction fees on the mainnet plummeted by 47.9% quarter-over-quarter. This shift is attributed to the network's strategic move into a "low fees for scale" phase, exemplified by the Fusaka upgrade which increased data capacity and lowered block space costs, releasing pent-up demand (a manifestation of Jevons's Paradox). The report highlights a core narrative shift for Ethereum: from a DeFi-centric blockchain to a global financial settlement layer. It maintains a dominant position in tokenized assets, holding majority market shares among top chains in stablecoins (61.8%), tokenized funds (73.0%), and tokenized commodities (84.0%). Growth in tokenized funds (+73.1% YoY) and commodities (+325.9% YoY) was particularly strong, driven by institutions like BlackRock and JPMorgan entering the space. Contrasting these usage gains, several USD-denominated value metrics declined in Q1: fully diluted market cap fell 30.3% QoQ, total value locked (TVL) dropped 11.0%, and ecosystem transaction volume decreased 24.0%. The report interprets this as Ethereum prioritizing long-term network expansion and cementing its role as the default settlement layer for finance over short-term fee capture. The commentary from Etherealize argues that, much like the early internet, Ethereum's open, permissionless model is poised to win over closed alternatives as institutional tokenization accelerates.

marsbit19m ago

Ethereum Q1 2026 Report: Fees Decline, Users and Transaction Volume Hit New Highs

marsbit19m ago

He Just Raised 2.7 Billion, and Li Fei-Fei Also Invested

Pete Florence, a former senior research scientist at Google DeepMind and a key contributor to the Vision-Language-Action (VLA) model architecture, is deliberately distancing his startup, Generalist AI, from the trendy "world model" label. He argues that the industry should prioritize concrete goals over buzzwords. His goal is to create robots that can perform a vast range of unseen tasks with high speed and success rates, without needing task-specific training data. Recently, his company raised $400 million (¥2.7 billion) at a $2 billion valuation. Notable investors include NVIDIA's NVentures, Bezos Expeditions, NFDG, as well as Xiaomi co-founder Lin Bin, Zoom founder Eric Yuan, and renowned AI scientist Fei-Fei Li. Florence's approach stems from his academic background at MIT under Professor Russ Tedrake, focusing on understanding the physical world. After joining DeepMind, he developed models like Transporter Network and co-created the VLA framework. He left in 2025 to found Generalist AI. The company has launched two models: GEN-0, which demonstrated that scaling laws apply to physical motion, and GEN-1. GEN-1 was trained on over 500,000 hours of physical interaction data collected via a specialized wearable device. It achieves a 99% success rate on precise mechanical tasks like folding boxes and maintains performance three times faster than its predecessor. Florence believes GEN-1 is reaching a commercial utility threshold similar to the GPT-3 inflection point. The substantial funding round, following GEN-1's release, signifies strong investor confidence in Generalist AI's practical, goal-driven path to creating versatile, useful robots, regardless of the "world model" terminology.

marsbit26m ago

He Just Raised 2.7 Billion, and Li Fei-Fei Also Invested

marsbit26m ago

Two Legends Lost in Three Days: Is Google's AI Talent Dam Cracking?

In three days, Google lost two AI legends. On June 18, Noam Shazeer, co-author of the seminal "Attention is All You Need" paper and Gemini co-lead, left for OpenAI. Just 48 hours later, John Jumper, 2024 Nobel laureate and AlphaFold lead, departed DeepMind for Anthropic. This follows Andrej Karpathy joining Anthropic in May. These moves highlight a structural trend: top AI talent is concentrating at mission-driven, pre-IPO firms like OpenAI and Anthropic, while Google becomes a primary source. The exodus stems from a core mission mismatch. Google's ad-centric model often subordinates AI research to product and revenue goals, creating friction for pioneers like Shazeer, who returned in 2024 only to leave again. In contrast, OpenAI and Anthropic offer singular focus on pushing AI boundaries, whether towards AGI or safety-aligned models, which deeply appeals to top researchers like Jumper. Financial incentives amplify the pull. With both OpenAI and Anthropic nearing IPO, employees stand to gain immensely from equity, an upside Google's mature stock cannot match. Furthermore, the 2023 merger of Google Brain and DeepMind, intended to consolidate strength, has instead created cultural tension and slowed the path from research to product, as evidenced by Gemini's pace. This talent redistribution is reshaping the AI landscape. While Google retains vast data and compute resources, its true crisis is the quiet, continuous loss of the people who define the field's future. The real moat in AI is not infrastructure, but the concentration of brilliant minds—a battle Google is currently losing.

marsbit2h ago

Two Legends Lost in Three Days: Is Google's AI Talent Dam Cracking?

marsbit2h ago

Behind the AI Report Card, Lies a Chinese 'Exam Setter'

Beyond the familiar performance charts like MMLU-Pro and MMMU, which major AI models strive to ace, stands a key "examiner": Chinese-Canadian researcher Wenhu Chen. An assistant professor at the University of Waterloo and founder of TIGERLab, Chen addresses the crucial need for more rigorous AI evaluation. As models like GPT-4 began scoring near-perfect results on older benchmarks like MMLU, it became difficult to distinguish their true capabilities. In response, Chen introduced MMLU-Pro in 2024, featuring harder, more reasoning-focused questions with more answer choices, successfully reintroducing meaningful performance gaps. His work extends to multi-modal evaluation with MMMU and its enhanced version, MMMU-Pro. These benchmarks test a model's ability to understand and reason with complex information from images, charts, and text across diverse academic subjects, exposing the significant challenges even top models face in genuine comprehension. Chen's background in complex QA, table reasoning, and his experience at Google DeepMind on projects like Gemini inform his approach. He understands that effective benchmarks must anticipate how models might "cheat" by memorizing data or avoiding visual analysis. His lab also actively researches video understanding and generation models (e.g., UniVideo, Vamba), ensuring his evaluation work is grounded in practical model-building challenges. Now at Meta's Super Intelligence Lab, Chen continues his focus on multi-modal data and evaluation, representing the deep yet often unseen contributions of Chinese talent in shaping the fundamental tools of the AI industry.

marsbit2h ago

Behind the AI Report Card, Lies a Chinese 'Exam Setter'

marsbit2h 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 SOL (SOL) are presented below.

活动图片