CBRS First Post-IPO Earnings Report: Revenue Doubles but Gross Margin Guidance Plummets, OpenAI's Massive Order Faces a Long Road to Realization

marsbit發佈於 2026-06-24更新於 2026-06-24

文章摘要

Cerebras Systems (CBRS) released its first quarterly report since going public. Q1 core revenue of $191.3M beat expectations, surging 92% YoY, with full-year revenue guidance raised to $855-$865M. However, the company's Q2 gross margin guidance of 36%-38% represents a sharp drop from Q1's 47%, sending shares down over 10% after-hours. Management attributed the margin pressure to temporary costs from leasing back hardware to deploy capacity for OpenAI, highlighting a business model shift from selling chips to selling compute power. While growth is strong, key investor debates center on valuation, customer concentration, and long-term contracts. Revenue remains heavily concentrated (86% from two UAE-linked entities in FY25), though major deals with OpenAI (a $20B+ contract) and AWS provide a long-term growth narrative. Analysts are broadly bullish, citing Cerebras's unique wafer-scale chip architecture as a potential advantage in the AI inference market. However, skeptics point to the narrow moat of its speed advantage, uncertainties around margin recovery amid its business transition, and a high valuation (~50x forward sales) that prices in the flawless execution of its large, long-dated contracts.

Author: David, Chaoxiang Research

Chaoxiang Guide: Cerebras (CBRS) delivered its first quarterly report since the IPO. Q1 core revenue was $191 million, a 92% year-over-year increase, exceeding market expectations. However, Q2 core gross margin guidance dropped sharply from 46.5% to 36%-38%, causing the stock price to fall over 10% after-hours. This company, which makes chips from an entire wafer and bets on the AI inference track, holds OpenAI contracts worth over $20 billion and an AWS cooperation framework. Full-year revenue guidance is $855-$865 million. The growth data is solid, but the valuation debate is equally significant.

Key Points of Focus

  1. Revenue beats expectations, guidance beats even more. Q1 core revenue was $191.3 million (up 92% YoY), higher than the consensus estimate of approximately $181 million. Full-year core revenue guidance of $855-$865 million (up 69% YoY) exceeds the market expectation of $828 million. On a GAAP basis, cloud and services revenue reached $82.8 million, a 178% YoY increase, making it the fastest-growing segment.
  2. The sharp drop in gross margin guidance is the biggest negative this quarter. Q1 core gross margin was 47%, up nearly 5 percentage points YoY. However, Q2 guidance fell to 36%-38%, a drop of about 10 percentage points from Q1; full-year guidance is 38%-41%. Management attributed this to insufficient data center capacity: the company is temporarily leasing back systems from existing customers who have already purchased the hardware to deploy capacity, worsening short-term costs. After-hours stock price fell over 10%.
  3. Customer concentration shows signs of improvement but is far from resolved. 86% of FY2025 revenue came from two UAE-related entities (MBZUAI accounted for 62%, G42 for 24%). OpenAI will start contributing revenue in February 2026, and the AWS cooperation is expected to reflect financially only in 2027. Genuine revenue diversification will not be verifiable until 2027.
  4. Valuation pricing extends to 2028. Based on the after-hours price of about $200, CBRS trades at about 90x trailing twelve-month revenue; even using the full-year guidance midpoint of $860 million, the forward P/S is still above 50x. The median price target from 10 covering analysts is $300 (range $250-$340), which implicitly assumes the OpenAI contract worth over $20 billion and AWS deployments are fulfilled on schedule and volume.
  5. Short-term catalysts and headwinds coexist. Catalysts: Accelerated deployment of OpenAI's 750MW computing power, AWS inference solution rollout, new data center capacity coming online in the second half. Headwinds: Lock-up period contains unconventional early release clauses (triggered if market cap exceeds $40 billion, current market cap is near that threshold), unclear path to gross margin recovery, OpenAI itself is not yet profitable and has already scaled back some computing power commitments.

Earnings Reveal Business Model Shift: From Selling Chips to Selling Computing Power

The most easily overlooked detail in the Q1 report is the change in revenue mix.

Under the core metric, hardware revenue was $111.6 million, accounting for 58% of total revenue; cloud and services revenue was $79.8 million, accounting for 42%. A year ago, this ratio was roughly 70:30. Cloud services revenue grew 167% YoY, nearly three times the growth rate of hardware.

Management made this trend clearer on the earnings call:

Hardware revenue will decline sequentially in the coming quarters because the company will deploy more hardware capacity into its own cloud to fulfill OpenAI's and AWS's inference computing power contracts, rather than selling directly to customers. Cerebras is shifting from a "chip-selling company" to a "computing power-selling company."

This transformation directly explains the sharp drop in Q2 gross margin guidance.

An analyst pressed for details on capacity deployment during the call. Management revealed:

The company's current bottleneck is not chip supply from TSMC, but the physical space in data centers. To deliver computing power to OpenAI as soon as possible, Cerebras is "temporarily leasing back" hardware systems already sold to G42 (its previous largest customer and a minority equity investor).

Deploying its own systems in leased third-party facilities worsens the cost structure in the short term, which is the main reason for the gross margin guidance drop from 47% to 36%-38%. Management's timeline indicates new data centers will start coming online in the second half of the year, easing cost pressures at that time.

The financial structure of the OpenAI contract is also worth unpacking. On the surface, it's a multi-year computing power purchase worth over $20 billion, but underneath, three relationships are layered: OpenAI provided Cerebras with a $1 billion operating capital loan (reflected on the Q1 balance sheet as $621 million in current loans and $362 million in non-current loans), while also receiving warrants for Cerebras stock.

In other words, OpenAI simultaneously plays the roles of largest customer, creditor, and potential shareholder for Cerebras. Risk disclosures in the S-1 indicate that if Cerebras fails to deliver capacity as agreed, OpenAI has the right to terminate the contract and trigger loan repayment.

The cooperation framework with AWS adopts a "split inference" architecture: AWS's Trainium 3 chip handles prompt input (prefill stage), while Cerebras's CS-3 system is dedicated to high-speed output generation (decode stage). This design allows Cerebras to handle only the part of the inference pipeline where its speed advantage is greatest. However, management declined to disclose the specific scale of the AWS cooperation during the Q&A and stated that revenue contribution would only appear on the financials in 2027.

The common feature of these two large contracts is: Contract sizes are massive, but realization paths are long, and heavily dependent on Cerebras's data center construction progress.

Full-year revenue guidance of $855-$865 million implies the next three quarters need to average around $220 million each, with sequential acceleration in growth. Management's statement is "year-over-year growth will increase each quarter in 2026, with more revenue concentrated in the second half."

The Bull Case: Nine Banks Initiate Coverage with Buy Ratings, What Are They Buying?

On June 8, the day the IPO quiet period ended, nine underwriting banks simultaneously initiated coverage, all issuing Buy or Outperform ratings. CBRS stock rose 18.3% that day. This kind of coordinated bullishness is not uncommon for US IPOs (underwriters have inherent interests), but their investment theses point to the same core proposition.

Thesis One: The battlefield for AI computing power is shifting from training to inference, and the rules of competition in inference differ from training.

Morgan Stanley analyst Joseph Moore issued an Overweight rating with a $250 price target in his June 8 initiation report. His core argument is: The training scenario competes on total computing throughput, where NVIDIA GPU clusters dominate absolutely; the inference scenario competes on the speed and latency of single responses, as models must process millions of user requests per second, and speed directly impacts service cost and user experience. Cerebras's wafer-scale chips, with their on-chip SRAM capacity far exceeding conventional GPUs (data doesn't need frequent movement to external memory), possess a structural advantage in inference latency. Moore's statement is that Cerebras is "the only company that has commercially deployed wafer-scale processors," giving it a first-mover advantage over NVIDIA.

Citi analyst Atif Malik gave the highest price target among coverages at $340. Mizuho added a technical detail in its June 8 report: The WSE-3 chip has 44GB of built-in SRAM, several times that of Google's latest TPU and Groq's LPU, a hardware gap that cannot be closed through architectural optimization in the short term.

Thesis Two: Two major contracts advance Cerebras from a "technology story" to a "revenue story."

The OpenAI contract exceeds $20 billion, covering 750MW of inference computing power, to be delivered over multiple years. Amortized over five years, this contract alone would contribute approximately $4 billion in annual revenue, nearly 5 times the midpoint of the 2026 full-year revenue guidance. Although management refused to disclose the specific amount for the AWS cooperation, the framework is confirmed: Cerebras's inference capabilities will be offered globally to enterprise customers through Amazon Bedrock.

Q1 earnings data provided early validation. OpenAI began deploying Cerebras systems in February, and cloud service revenue jumped from less than $30 million YoY to nearly $80 million in one quarter. Management's statement is "year-over-year growth will increase each quarter in 2026, with more revenue concentrated in the second half." The full-year guidance of $855-$865 million exceeds the consensus estimate of $828 million.

Thesis Three: The density of coverage right after the quiet period is itself a signal.

The median price target from 10 analysts is $300, with a low of $250 (Morgan Stanley) and a high of $340 (Citi). Based on the after-hours price of $200, the median target implies about 50% upside. Wedbush ($270 target), Needham ($300), Barclays ($280), TD Cowen ($275), and Craig-Hallum (Buy) all initiated coverage in the same week.

The underlying assumption of the bull case can be summed up in one sentence:

If AI inference becomes a larger computing power market than training (multiple institutions predict inference spending will surpass training by 2027), and Cerebras's speed advantage is real and sustainable, then it only needs to capture 3%-5% of the market where NVIDIA holds an 80%+ share to justify its current valuation.

The Bear Case: Gross Margin, Customer Concentration, and the Fragility of a $45 Billion Valuation

For each of the bull's three theses, the bears have counterarguments.

Counterargument One: The moat from inference speed advantage may be narrower than imagined.

Cerebras's speed advantage is built on on-chip SRAM capacity, but NVIDIA is not standing still. The B300 chip released by NVIDIA in March significantly increased HBM bandwidth, and Groq's LPU architecture is also iterating rapidly on the inference front.

Viewed from another angle: Cerebras's customers are currently highly concentrated in just OpenAI and AWS. OpenAI is also one of NVIDIA's largest GPU purchasing clients, and AWS's in-house Trainium chip is covering more and more inference scenarios. Cerebras's major customers are simultaneously betting on alternatives, meaning its speed premium will face continuous price negotiation pressure.

Counterargument Two: The gross margin decline might not be just "temporary."

Management attributed the Q2 gross margin drop from 47% to 36%-38% to temporary leasing costs due to insufficient data center capacity. But this explanation assumes "costs will improve when new data centers come online in the second half."

Considering that revenue scale is expected to jump in the second half (management explicitly stated revenue is back-end loaded), and new data center capacity ramp-up itself requires time and capital investment, this recovery path is not easy.

A deeper issue is the impact of the business model shift itself on gross margin. Cerebras's shift from selling hardware to selling cloud computing power means taking on data center construction, operation, and depreciation costs. As depreciation expenses for self-built data centers are accounted for, uncertainty remains over whether cloud service gross margins can stay above 50%. The profitability ceiling of this business model has yet to be tested.

Counterargument Three: Customer concentration is a problem that has "changed names but is not solved."

In 2024, G42 alone contributed 85% of Cerebras's revenue. In 2025, G42's share dropped to 24%, but MBZUAI (Mohamed bin Zayed University of Artificial Intelligence) surged from nothing to 62%. The S-1 prospectus clearly labels these two as "related parties." The two UAE-related entities combined still account for 86% of revenue. Revenue source diversification is more about a change in names rather than substantive dispersion.

Finally, CBRS's IPO lock-up period contains an unconventional clause:

If the company's market cap consistently exceeds $40 billion, insider shares can be released early. At the after-hours price of $200, the current market cap is about $45 billion, already near the trigger line. On the short side, as of May 29, the short interest was 17.15% of the float, which is on the high side. If the lock-up period triggers an early release, unleashing a large number of insider shares, combined with existing short pressure, the stock could face concentrated selling.

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相關問答

QWhat was the main negative surprise in Cerebras' (CBRS) Q2 guidance according to the article?

AThe main negative surprise was the sharp decline in the Q2 core gross margin guidance from 47% in Q1 to a range of 36%-38%. This triggered a more than 10% drop in the stock price after hours.

QWhat are the two major contracts that represent the 'revenue story' for Cerebras' future growth?

AThe two major contracts are: 1) The over $20 billion, multi-year contract with OpenAI for 750MW of inference compute power, with revenue contribution starting from February 2026. 2) The collaboration framework with AWS to offer inference solutions via Amazon Bedrock, with revenue expected to show up in financials from 2027.

QWhy does the article argue that Cerebras' customer concentration issue is 'not solved' despite the changing names?

AIn FY2025, 86% of Cerebras' revenue still comes from two UAE-affiliated entities: MBZUAI (62%) and G42 (24%). These are noted as related parties. Therefore, while the name of the largest contributor changed, revenue remains heavily concentrated within a related group, not genuinely diversified.

QAccording to the bullish analyst logic, what is Cerebras' key structural advantage in the AI inference market?

AIts key structural advantage is the massive on-chip SRAM capacity (44GB on the WSE-3) of its wafer-scale processors. This allows data to be processed without frequent transfers to external memory, significantly reducing latency, which is critical for real-time AI inference serving user requests.

QWhat is the primary reason given by management for the expected sharp decline in Q2 gross margins?

AManagement attributed the decline to a shortage of data center capacity. To expedite deployment for OpenAI, Cerebras is temporarily leasing back hardware systems already sold to existing customers (like G42). This short-term rental arrangement worsens the cost structure, pressuring margins. They expect pressure to ease when new data centers come online in the second half of the year.

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什麼是 $S$

理解 SPERO:全面概述 SPERO 簡介 隨著創新領域的不斷演變,web3 技術和加密貨幣項目的出現在塑造數字未來中扮演著關鍵角色。在這個動態領域中,SPERO(標記為 SPERO,$$s$)是一個引起關注的項目。本文旨在收集並呈現有關 SPERO 的詳細信息,以幫助愛好者和投資者理解其基礎、目標和在 web3 和加密領域內的創新。 SPERO,$$s$ 是什麼? SPERO,$$s$ 是加密空間中的一個獨特項目,旨在利用去中心化和區塊鏈技術的原則,創建一個促進參與、實用性和金融包容性的生態系統。該項目旨在以新的方式促進點對點互動,為用戶提供創新的金融解決方案和服務。 SPERO,$$s$ 的核心目標是通過提供增強用戶體驗的工具和平台來賦能個人。這包括使交易方式更加靈活、促進社區驅動的倡議,以及通過去中心化應用程序(dApps)創造金融機會的途徑。SPERO,$$s$ 的基本願景圍繞包容性展開,旨在彌合傳統金融中的差距,同時利用區塊鏈技術的優勢。 誰是 SPERO,$$s$ 的創建者? SPERO,$$s$ 的創建者身份仍然有些模糊,因為公開可用的資源對其創始人提供的詳細背景信息有限。這種缺乏透明度可能源於該項目對去中心化的承諾——這是一種許多 web3 項目所共享的精神,優先考慮集體貢獻而非個人認可。 通過將討論重心放在社區及其共同目標上,SPERO,$$s$ 體現了賦能的本質,而不特別突出某些個體。因此,理解 SPERO 的精神和使命比識別單一創建者更為重要。 誰是 SPERO,$$s$ 的投資者? SPERO,$$s$ 得到了來自風險投資家到天使投資者的多樣化投資者的支持,他們致力於促進加密領域的創新。這些投資者的關注點通常與 SPERO 的使命一致——優先考慮那些承諾社會技術進步、金融包容性和去中心化治理的項目。 這些投資者通常對不僅提供創新產品,還對區塊鏈社區及其生態系統做出積極貢獻的項目感興趣。這些投資者的支持強化了 SPERO,$$s$ 作為快速發展的加密項目領域中的一個重要競爭者。 SPERO,$$s$ 如何運作? SPERO,$$s$ 採用多面向的框架,使其與傳統的加密貨幣項目區別開來。以下是一些突顯其獨特性和創新的關鍵特徵: 去中心化治理:SPERO,$$s$ 整合了去中心化治理模型,賦予用戶積極參與決策過程的權力,關於項目的未來。這種方法促進了社區成員之間的擁有感和責任感。 代幣實用性:SPERO,$$s$ 使用其自己的加密貨幣代幣,旨在在生態系統內部提供多種功能。這些代幣使交易、獎勵和平台上提供的服務得以促進,增強了整體參與度和實用性。 分層架構:SPERO,$$s$ 的技術架構支持模塊化和可擴展性,允許在項目發展過程中無縫整合額外的功能和應用。這種適應性對於在不斷變化的加密環境中保持相關性至關重要。 社區參與:該項目強調社區驅動的倡議,採用激勵合作和反饋的機制。通過培養強大的社區,SPERO,$$s$ 能夠更好地滿足用戶需求並適應市場趨勢。 專注於包容性:通過提供低交易費用和用戶友好的界面,SPERO,$$s$ 旨在吸引多樣化的用戶群體,包括那些以前可能未曾參與加密領域的個體。這種對包容性的承諾與其通過可及性賦能的總體使命相一致。 SPERO,$$s$ 的時間線 理解一個項目的歷史提供了對其發展軌跡和里程碑的關鍵見解。以下是建議的時間線,映射 SPERO,$$s$ 演變中的重要事件: 概念化和構思階段:形成 SPERO,$$s$ 基礎的初步想法被提出,與區塊鏈行業內的去中心化和社區聚焦原則密切相關。 項目白皮書的發布:在概念階段之後,發布了一份全面的白皮書,詳細說明了 SPERO,$$s$ 的願景、目標和技術基礎設施,以吸引社區的興趣和反饋。 社區建設和早期參與:積極進行外展工作,建立早期採用者和潛在投資者的社區,促進圍繞項目目標的討論並獲得支持。 代幣生成事件:SPERO,$$s$ 進行了一次代幣生成事件(TGE),向早期支持者分發其原生代幣,並在生態系統內建立初步流動性。 首次 dApp 上線:與 SPERO,$$s$ 相關的第一個去中心化應用程序(dApp)上線,允許用戶參與平台的核心功能。 持續發展和夥伴關係:對項目產品的持續更新和增強,包括與區塊鏈領域其他參與者的戰略夥伴關係,使 SPERO,$$s$ 成為加密市場中一個具有競爭力和不斷演變的參與者。 結論 SPERO,$$s$ 是 web3 和加密貨幣潛力的見證,能夠徹底改變金融系統並賦能個人。憑藉對去中心化治理、社區參與和創新設計功能的承諾,它為更具包容性的金融環境鋪平了道路。 與任何在快速發展的加密領域中的投資一樣,潛在的投資者和用戶都被鼓勵進行徹底研究,並對 SPERO,$$s$ 的持續發展進行深思熟慮的參與。該項目展示了加密行業的創新精神,邀請人們進一步探索其無數可能性。儘管 SPERO,$$s$ 的旅程仍在展開,但其基礎原則確實可能影響我們在互聯網數字生態系統中如何與技術、金融和彼此互動的未來。

106 人學過發佈於 2024.12.17更新於 2024.12.17

什麼是 $S$

什麼是 AGENT S

Agent S:Web3中自主互動的未來 介紹 在不斷演變的Web3和加密貨幣領域,創新不斷重新定義個人如何與數字平台互動。Agent S是一個開創性的項目,承諾通過其開放的代理框架徹底改變人機互動。Agent S旨在簡化複雜任務,為人工智能(AI)提供變革性的應用,鋪平自主互動的道路。本詳細探索將深入研究該項目的複雜性、其獨特特徵以及對加密貨幣領域的影響。 什麼是Agent S? Agent S是一個突破性的開放代理框架,專門設計用來解決計算機任務自動化中的三個基本挑戰: 獲取特定領域知識:該框架智能地從各種外部知識來源和內部經驗中學習。這種雙重方法使其能夠建立豐富的特定領域知識庫,提升其在任務執行中的表現。 長期任務規劃:Agent S採用經驗增強的分層規劃,這是一種戰略方法,可以有效地分解和執行複雜任務。此特徵顯著提升了其高效和有效地管理多個子任務的能力。 處理動態、不均勻的界面:該項目引入了代理-計算機界面(ACI),這是一種創新的解決方案,增強了代理和用戶之間的互動。利用多模態大型語言模型(MLLMs),Agent S能夠無縫導航和操作各種圖形用戶界面。 通過這些開創性特徵,Agent S提供了一個強大的框架,解決了自動化人機互動中涉及的複雜性,為AI及其他領域的無數應用奠定了基礎。 誰是Agent S的創建者? 儘管Agent S的概念根本上是創新的,但有關其創建者的具體信息仍然難以捉摸。創建者目前尚不清楚,這突顯了該項目的初期階段或戰略選擇將創始成員保密。無論是否匿名,重點仍然在於框架的能力和潛力。 誰是Agent S的投資者? 由於Agent S在加密生態系統中相對較新,關於其投資者和財務支持者的詳細信息並未明確記錄。缺乏對支持該項目的投資基礎或組織的公開見解,引發了對其資金結構和發展路線圖的質疑。了解其支持背景對於評估該項目的可持續性和潛在市場影響至關重要。 Agent S如何運作? Agent S的核心是尖端技術,使其能夠在多種環境中有效運作。其運營模型圍繞幾個關鍵特徵構建: 類人計算機互動:該框架提供先進的AI規劃,力求使與計算機的互動更加直觀。通過模仿人類在任務執行中的行為,承諾提升用戶體驗。 敘事記憶:用於利用高級經驗,Agent S利用敘事記憶來跟蹤任務歷史,從而增強其決策過程。 情節記憶:此特徵為用戶提供逐步指導,使框架能夠在任務展開時提供上下文支持。 支持OpenACI:Agent S能夠在本地運行,使用戶能夠控制其互動和工作流程,與Web3的去中心化理念相一致。 與外部API的輕鬆集成:其多功能性和與各種AI平台的兼容性確保了Agent S能夠無縫融入現有技術生態系統,成為開發者和組織的理想選擇。 這些功能共同促成了Agent S在加密領域的獨特地位,因為它以最小的人類干預自動化複雜的多步任務。隨著項目的發展,其在Web3中的潛在應用可能重新定義數字互動的展開方式。 Agent S的時間線 Agent S的發展和里程碑可以用一個時間線來概括,突顯其重要事件: 2024年9月27日:Agent S的概念在一篇名為《一個像人類一樣使用計算機的開放代理框架》的綜合研究論文中推出,展示了該項目的基礎工作。 2024年10月10日:該研究論文在arXiv上公開,提供了對框架及其基於OSWorld基準的性能評估的深入探索。 2024年10月12日:發布了一個視頻演示,提供了對Agent S能力和特徵的視覺洞察,進一步吸引潛在用戶和投資者。 這些時間線上的標記不僅展示了Agent S的進展,還表明了其對透明度和社區參與的承諾。 有關Agent S的要點 隨著Agent S框架的持續演變,幾個關鍵特徵脫穎而出,強調其創新性和潛力: 創新框架:旨在提供類似人類互動的直觀計算機使用,Agent S為任務自動化帶來了新穎的方法。 自主互動:通過GUI自主與計算機互動的能力標誌著向更智能和高效的計算解決方案邁進了一步。 複雜任務自動化:憑藉其強大的方法論,能夠自動化複雜的多步任務,使過程更快且更少出錯。 持續改進:學習機制使Agent S能夠從過去的經驗中改進,不斷提升其性能和效率。 多功能性:其在OSWorld和WindowsAgentArena等不同操作環境中的適應性確保了它能夠服務於廣泛的應用。 隨著Agent S在Web3和加密領域中的定位,其增強互動能力和自動化過程的潛力標誌著AI技術的一次重大進步。通過其創新框架,Agent S展現了數字互動的未來,為各行各業的用戶承諾提供更無縫和高效的體驗。 結論 Agent S代表了AI與Web3結合的一次大膽飛躍,具有重新定義我們與技術互動方式的能力。儘管仍處於早期階段,但其應用的可能性廣泛且引人入勝。通過其全面的框架解決關鍵挑戰,Agent S旨在將自主互動帶到數字體驗的最前沿。隨著我們深入加密貨幣和去中心化的領域,像Agent S這樣的項目無疑將在塑造技術和人機協作的未來中發揮關鍵作用。

883 人學過發佈於 2025.01.14更新於 2025.01.14

什麼是 AGENT S

如何購買S

歡迎來到HTX.com!在這裡,購買Sonic (S)變得簡單而便捷。跟隨我們的逐步指南,放心開始您的加密貨幣之旅。第一步:創建您的HTX帳戶使用您的 Email、手機號碼在HTX註冊一個免費帳戶。體驗無憂的註冊過程並解鎖所有平台功能。立即註冊第二步:前往買幣頁面,選擇您的支付方式信用卡/金融卡購買:使用您的Visa或Mastercard即時購買Sonic (S)。餘額購買:使用您HTX帳戶餘額中的資金進行無縫交易。第三方購買:探索諸如Google Pay或Apple Pay等流行支付方式以增加便利性。C2C購買:在HTX平台上直接與其他用戶交易。HTX 場外交易 (OTC) 購買:為大量交易者提供個性化服務和競爭性匯率。第三步:存儲您的Sonic (S)購買Sonic (S)後,將其存儲在您的HTX帳戶中。您也可以透過區塊鏈轉帳將其發送到其他地址或者用於交易其他加密貨幣。第四步:交易Sonic (S)在HTX的現貨市場輕鬆交易Sonic (S)。前往您的帳戶,選擇交易對,執行交易,並即時監控。HTX為初學者和經驗豐富的交易者提供了友好的用戶體驗。

1.9k 人學過發佈於 2025.01.15更新於 2026.06.02

如何購買S

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歡迎來到 HTX 社群。在這裡,您可以了解最新的平台發展動態並獲得專業的市場意見。 以下是用戶對 S (S)幣價的意見。

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