Time To Buy Ethereum? Here’s How High The Price Could Be By December 2026

bitcoinistPublished on 2026-03-10Last updated on 2026-03-10

Abstract

Despite its underwhelming performance in the last bull run, Ethereum remains a top investment choice as the second-largest cryptocurrency. A machine learning algorithm from CoinCodex predicts a bullish 2026 for ETH, with the price expected to stay above $2,000 for most of the year, aside from a dip in March. The analysis suggests Ethereum could surpass $3,000 in May, reaching a yearly peak of around $3,673—a potential 90% gain from current levels. By December, the price is projected to be around $2,477, offering a 28% return. March is highlighted as the best entry point for the lowest prices, while May is ideal for selling at the peak. The latter half of the year is forecasted to see ETH trading in a relatively tight range.

Despite its disappointing performance over the last bull run, Ethereum has remained a top choice for investors across the crypto sector. Its position as the second-largest cryptocurrency by market cap makes it one of the first stops for new and old investors. But with the price still trading well below its previous all-time high, the question remains as to whether this is a good time to actually buy Ethereum, and if there will be great returns by the end of the year.

Can Ethereum Cross $3,000 This Year?

The machine learning algorithm at the CoinCodex website gives a breakdown of where the Ethereum price could be each month of the year, taking certain factors into account. Going by the predictions on the website, it seems that the year 2026 is expected to be a rather bullish one for Ethereum. It also answers the question of whether ETH’s price could break $3,000 again this year.

One interesting thing of note is that the predictions show that each month will finish higher than the current price. Besides the month of March, there is no other month in 2026 where the algorithm predicts that the Ethereum price will fall below $2,000 again. Instead, the predictions show possible double-digit increases for the digital asset.

Source: CoinCodex

As for when the price could cross $3,000, it suggests that this could happen sometime in May, which is two months from now. After that, the price is expected to fall below $3,000 again, trending around this level till the end of the month.

Taking into account that the highest level for the year is expected to be around $3,673, it would mean an approximately 90% gain on the price if bought from current levels. If holding through to the end of the year, the highest level in December 2026 is expected to reach $2,477. This would mean a 28% return on investment.

Going by the prediction, March would be the best time to get into Ethereum at the lowest prices in 2026. Then the best time to sell would be in May when the price is expected to hit its peak. From June to the end of the year, the price is expected to then trade in a fairly tight range.

ETH recovers above $2,000 | Source: ETHUSDT on Tradingview.com

Related Reads

CLARITY Act: Banking Trade Groups Push For Yield Agreement Revision – Details

US banking trade groups are urging revisions to the stablecoin yield compromise in the upcoming CLARITY Act ahead of a key committee markup. The Act currently aims to ban all passive, deposit-like interest on stablecoins to prevent competition with traditional bank savings, while allowing rewards tied to active uses like staking or transactions. In a letter, groups including the American Banking Association and Bank Policy Institute proposed stricter language to eliminate perceived loopholes for passive yield and prevent deposit flight from banks. However, these efforts are reportedly viewed as minor by some lawmakers. The Senate Banking Committee is scheduled to mark up the bill on May 14, a critical step before it can advance through Congress.

bitcoinist12h ago

CLARITY Act: Banking Trade Groups Push For Yield Agreement Revision – Details

bitcoinist12h ago

This Finance CEO Picks Solana Instead Of Bitcoin — Here’s Why

Finance CEO Raoul Pal prefers Solana over Bitcoin, citing its high throughput and low transaction costs as better suited for the future crypto-AI era. He believes Solana is ideal for machine-to-machine microtransactions and AI-driven DeFi activity, predicting AI agents will soon dominate DeFi users. While Bitcoin serves as a store of value, Pal sees higher growth in networks built for mass, automated transactions. This view was highlighted at Consensus 2026, where AI integration and crypto infrastructure were key themes.

bitcoinist12h ago

This Finance CEO Picks Solana Instead Of Bitcoin — Here’s Why

bitcoinist12h ago

Gensyn AI: Don't Let AI Repeat the Mistakes of the Internet

In recent months, the rapid growth of the AI industry has attracted significant talent from the crypto sector. A persistent question among researchers intersecting both fields is whether blockchain can become a foundational part of AI infrastructure. While many previous AI and Crypto projects focused on application layers (like AI Agents, on-chain reasoning, data markets, and compute rentals), few achieved viable commercial models. Gensyn differentiates itself by targeting the most critical and expensive layer of AI: model training. Gensyn aims to organize globally distributed GPU resources into an open AI training network. Developers can submit training tasks, nodes provide computational power, and the network verifies results while distributing incentives. The core issue addressed is not decentralization for its own sake, but the increasing centralization of compute power among tech giants. In the era of large models, access to GPUs (like the H100) has become a decisive bottleneck, dictating the pace of AI development. Major AI companies are heavily dependent on large cloud providers for compute resources. Gensyn's approach is significant for several reasons: 1) It operates at the core infrastructure layer (model training), the most resource-intensive and technically demanding part of the AI value chain. 2) It proposes a more open, collaborative model for compute, potentially increasing resource utilization by dynamically pooling idle GPUs, similar to early cloud computing logic. 3) Its technical moat lies in solving complex challenges like verifying training results, ensuring node honesty, and maintaining reliability in a distributed environment—making it more of a deep-tech infrastructure company. 4) It targets a validated, high-growth market with genuine demand, rather than pursuing blockchain integration without purpose. Ultimately, the boundaries between Crypto and AI are blurring. AI requires global resource coordination, incentive mechanisms, and collaborative systems—areas where crypto-native solutions excel. Gensyn represents a step toward making advanced training capabilities more accessible and collaborative, moving beyond a niche controlled by a few giants. If successful, it could evolve into a fundamental piece of AI infrastructure, where the most enduring value in the AI era is often created.

marsbit13h ago

Gensyn AI: Don't Let AI Repeat the Mistakes of the Internet

marsbit13h ago

Why is China's AI Developing So Fast? The Answer Lies Inside the Labs

A US researcher's visit to China's top AI labs reveals distinct cultural and organizational factors driving China's rapid AI development. While talent, data, and compute are similar to the West, Chinese labs excel through a pragmatic, execution-focused culture: less emphasis on individual stardom and conceptual debate, and more on teamwork, engineering optimization, and mastering the full tech stack. A key advantage is the integration of young students and researchers who approach model-building with fresh perspectives and low ego, prioritizing collective progress over personal credit. This contrasts with the US culture of self-promotion and "star scientist" narratives. Chinese labs also exhibit a strong "build, don't buy" mentality, preferring to develop core capabilities—like data pipelines and environments—in-house rather than relying on external services. The ecosystem feels more collaborative than tribal, with mutual respect among labs. While government support exists, its scale is unclear, and technical decisions appear driven by labs, not state mandates. Chinese companies across sectors, from platforms to consumer tech, are building their own foundational models to control their tech destiny, reflecting a broader cultural drive for technological sovereignty. Demand for AI is emerging, with spending patterns potentially mirroring cloud infrastructure more than traditional SaaS. Despite challenges like a less mature data industry and GPU shortages, Chinese labs are propelled by vast talent, rapid iteration, and deep integration with the open-source community. The competition is evolving beyond a pure model race into a contest of organizational execution, developer ecosystems, and industrial pragmatism.

marsbit14h ago

Why is China's AI Developing So Fast? The Answer Lies Inside the Labs

marsbit14h ago

3 Years, 5 Times: The Rebirth of a Century-Old Glass Factory

Corning, a 175-year-old glass company, is experiencing a dramatic revival as a key player in AI infrastructure, driven by surging demand for high-performance optical fiber in data centers. AI data centers require vastly more fiber than traditional ones—5 to 10 times as much per rack—to handle high-speed data transmission between GPUs. This structural demand shift, coupled with supply constraints from the lengthy expansion cycle for fiber preforms, has created a significant supply-demand gap. Nvidia has invested in Corning, along with Lumentum and Coherent, in a $4.5 billion total commitment to secure the optical supply chain for AI. Corning's competitive edge lies in its expertise in producing ultra-low-loss, high-density, and bend-resistant specialty fiber, which is critical for 800G+ and future 1.6T data rates. Its deep involvement in co-packaged optics (CPO) with partners like Nvidia further solidifies its position. While not the largest fiber manufacturer globally, Corning's revenue from enterprise/data center clients now exceeds 40% of its optical communications sales, and it has secured multi-year supply agreements with major hyperscalers including Meta and Nvidia. Financially, Corning's optical communications revenue has surged, doubling from $1.3 billion in 2023 to over $3 billion in 2025. Its stock price has risen nearly 6-fold since late 2023. Key future catalysts include the rollout of Nvidia's CPO products and the scale of undisclosed customer agreements. However, risks include high current valuations and potential disruption from next-generation technologies like hollow-core fiber. The company's long-term bet on light over electricity, maintained even through the telecom bubble crash, is now being validated by the AI boom.

marsbit15h ago

3 Years, 5 Times: The Rebirth of a Century-Old Glass Factory

marsbit15h 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 ETH (ETH) are presented below.

活动图片

Top Questions