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Are Bitcoin's 80,000, 120,000, and 300,000 still far away?

Are Bitcoin's 80,000, 120,000, and 300,000 still far away?

Author: Debashree Patra Compiled by: Deep Tide TechFlow Original title: Bitcoin Sword Fingers at $80,000: Analysts Predict Breaking 120,000 Next Year and Shocking 300,000 in 2030 DeepWave Guide: Bitcoin rebounds strongly from around $63,000 to $75,401, completing a 5.8 times standard deviation increase within 48 hours, driving analyst Pierre Rochard to reaffirm his bullish roadmap — hitting $80,000 in 2026 and breaking through $120,000 next year. The sword in 2030 is $300,000. In the short term, bear liquidation and downtrend line breakouts provide momentum, but whether the leverage-driven surge can be turned into continued spot demand will determine whether the larger goal is realistic. Pierre Rochard's $80,000-$300,000 roadmap analyst Pierre Rochard (BitcoinPierre) expects Bitcoin to close around $80,000 in 2026. He believes that Bitcoin is not ready for a “parabolic rise,” but it is expected to break through $120,000 next year. In the longer term, he predicted that Bitcoin could reach $300,000 by 2030. The key variables in this forecast are the Federal Reserve and the broader macro environment. Rochard believes that if the economy is weak enough to allow the Federal Reserve to cut interest rates without reigniting inflation, Bitcoin will benefit from improved liquidity. He also pointed out that artificial intelligence (AI) may improve macroeconomic prospects by increasing productivity and reducing inflation. In that situation, interest rate cuts will create a more favorable environment for risky assets such as Bitcoin. The $80,000 target refocused on Bitcoin's latest price trend has shown signs of regaining momentum. BTC climbed from around $63,000 to $75401 in less than 48 hours. Previously, buyers successfully defended in the $63,000 area. Notably, Bitcoin formed higher highs and higher lows. This round of rebound was partly fueled by large-scale short liquidations. According to reports, as Bitcoin and Ethereum soared, around $14 billion to $17 billion of short crypto positions were liquidated, removing bearish leverage. Glassnode indicated an unusual pattern of this fluctuation. They said that Bitcoin's jump from around $75,401 was a 5.8 times standard deviation (5.8 sigma) of its 30-day volatility — the biggest upward move since October 2023. The last time Bitcoin closed at such a large daily rate was in February, which was only a rebound after a sharp drop of -14% the day before. And there's no crash to bounce back this time around — this is a 5.8 times standard deviation fluctuation compared to its own 30-day volatility, the biggest upward move since October 2023. — Glassnode (@glassnode) However, liquidation alone does not confirm the existence of sustainable spot demand. On-chain analyst Onchain Insights said that Bitcoin has broken through the annual downward trend line resistance and recovered to the $70,000 range. If it continues to close above this structural resistance, it may indicate a weakening of selling pressure and further upward momentum. Another analyst also said that short positions have limited resistance until $80,000, making it an important near-term target. The BTC giant whale sells for $74,000 and $80,000. The gap between these resistances is very large. ——CW (@CW8900) On Polymarket, the probability that Bitcoin will hit $80,000 in August rose to 13%, up 9 percentage points within 6 hours. BTC would need to rise about 14% more from $71,000 to reach $80,000. Can the $120,000 be recovered? Rochard expects Bitcoin to easily break through $120,000 next year if the macro environment turns favorable. His long-term goal of $300,000 by 2030 reflects broader bullish arguments around liquidity, supply, and adoption. His opinion was also supported by SkyBridge Capital CEO Anthony Scaramucci, who expected Bitcoin to surpass $100,000. He cites the halving cycle and new supply...

1d ago深潮TechFlow#Bitcoin

DeepSeek visual model officially launched API: the price is exactly the same as V4 Flash

In comparison, DeepSeek officially launched a new visual model, deepseek-v4-flash-vision-exp. The official API documentation has juxtaposed it with V4 Flash and V4 Pro, and developers can directly import images through the DeepSeek API. The model supports 1 million token contexts, a maximum output of 384,000 tokens, and also supports JSON Output, Tool Calls, Responses API, and Anthropic API. The price is directly aligned with the V4 Flash. The peak period for each million token input is 3 yuan and the idle period is 1.5 yuan; the cache hit is only 0.1 yuan and 0.05 yuan, respectively. Each million tokens are worth 9 yuan during peak output periods and 4.5 yuan during idle periods. Compared to the V4 Pro, the price of the same class is only one-third. There is no separate charge per image. DeepSeek will convert the image into a token based on the image size, and then bill it together with the text token. Peak periods are 9:00 to 12:00 and 14:00 to 18:00 Beijing time; prices are halved the rest of the day.

1d ago

Coinbase CEO: Bitcoin may be close to a new round of bull market

Comparing news, according to Bitcoin Magazine, Coinbase CEO Brian Armstrong said in an interview with CNBC that the crypto market “is probably at the beginning of the next bull run.” He mentioned that the September 15 vote on the “Clarity Act” and October, November, and December, which have traditionally performed well after the Bitcoin halving cycle, may be important factors influencing market trends.

2d ago

Coinbase CEO: It's probably on the eve of the next bull market

Comparing news, Coinbase CEO Brian Armstrong said in an interview with CNBC that I think we are probably on the eve of the next bull market. He said: We are watching the “Clarity Act” vote on September 15. Furthermore, according to the pattern of Bitcoin's previous halving cycles, October, November, and December are generally good months for Bitcoin.

2d ago

It is reported that the bank drastically lowered the cost of leveraged investment in SK Hynix Korean stocks

Comparative news, according to Kim Ju's report, after SK Hynix went public in the US and AI-related stocks experienced a sharp decline, the financing costs for global investors to make leveraged investments in SK Hynix Korean stocks have been cut in half in recent weeks. According to people familiar with the matter, a number of banks, including Bank of America, Citigroup, Goldman Sachs Group, and J.P. Morgan Chase, are offering customers an increase of about 150 to 300 basis points on the Guaranteed Overnight Financing Rate (SOFR) to obtain exposure to SK Hynix Korean shares through swap transactions. In mid-June of this year, for customers who wanted to establish a new SK Hynix swap contract or renew their offer, some banks once increased by more than 1000 basis points in SOFR. Since May 1, the SOFR has been fluctuating between 3.50% and 3.69%. Previously, in order to allocate a limited amount among customers to meet the demand for additional SK Hynix swap transactions, banks offered extremely high financing interest rates, and even directly rejected customer requests under certain circumstances. At the time, the AI boom boosted SK Hynix Korea stock's cumulative 11-fold increase in the 12 months up to June 22. As market sentiment becomes extremely bullish, banks are worried that their portfolios will be overly focused on such stocks, which in turn will drive up their financing costs in the repurchase market. According to people familiar with the matter, some banks that previously rejected customer requests are now actively seeking new business.

2d ago

Ukrainian Black Sea ports closed, agricultural exports or halved

Comparing news, the Ukrainian government said that Ukraine's remaining Black Sea ports in the Greater Odesa region have essentially been closed due to Russian air raids, and its planned agricultural exports may be cut in half, posing a risk to global food supply.

8d ago

When will Bitcoin bottom out? 4chan's anonymous Oracle post reached a high level of consensus with analysts such as Jiang Zhuoer

Comparing news, 10 months have passed since Bitcoin peaked in October 2025, and the four-year cycle theory believed by the crypto community recently sparked another buzz: when will Bitcoin bottom out and when can it hit bottom. On this issue, the opinions of many well-known analysts have been compiled as follows: Famous trader and chart analyst Peter Brandt said in late July that the current Bitcoin market cycle is expected to bottom out on October 4, 2026, and believes that the current earnings performance of investing in Bitcoin in the next two or three years may be better than investing in AI stocks. Furthermore, Brandt anticipates that the top of Bitcoin's next cycle will occur in 2029, with a target price range of $250,000 to $300,000. Jiang Zhuoer, founder of Libitt Mining Pool (B.TOP), predicted the bottom of the current bear market in conjunction with the previous 3 rounds of Bitcoin halving cycles. The bottom price of BTC in this round is estimated to be $44016, which is expected to occur on October 31. Well-known traders Killa and CryptoD gave relatively broad time frames. Killa believes the bottom may be formed in July-September. However, CryptoD, which once relied on the meme coin TRUMP to profit more than 10 million dollars, believes that now the overall crypto market is gradually approaching the bottom, and Q3 and Q4 are likely to be the last period before the next round of bull markets. It is worth noting that Peter Brandt and Jiang Zhuoer's October bottom-line theory has reached a high degree of consensus with the 4chan forum's anonymous Oracle post, which was widely circulated on the Internet. Historical records show that the Oracle post was published on December 12, 2023, and the post listed the time span of the four Bitcoin price highs and lows since 2015 (ATL 2015 → ATH 2017 = 1064 days; ATH 2017 → ATL 2018 364 days; ATL 2018 → ATH 2021 1064 days; ATH 2021 → ATL 2022 и 364 days), and was compared according to this rule The conclusion was that Bitcoin peaked on October 6, 2025. Based on this logical deduction, the current round of Bitcoin will also bottom out in October of this year. However, the above analysis may be a search for a sword. In this cycle, the entry of institutional capital has redefined the Bitcoin pattern, and it makes sense for the cycle to change.

11d ago

Ant Ling-3.0-Flash is officially open source, FP8 version is only 128GB

Comparative news, according to monitoring, InclusionAI (InclusionAI) officially released Ling-3.0-flash weights, and also provided the original BF16 and FP8 quantitative versions. Both versions use the MIT license, have launched Hugging Face and ModelScope, and can be self-deployed using SGLang or vLLM. The BF16 copyright weighs about 255GB, the FP8 version is about 128GB, and the size is nearly halved. FP8 uses lower accuracy to save parameters, which can lower the storage and video memory threshold. Of the 4 officially listed tests, the maximum score difference between FP8 and BF16 was 1.57 points. LING-3.0-Flash has a total parameter of 124 billion, and only 5.1 billion are activated per generation. The model supports 256,000 token contexts and is mainly aimed at agent tasks such as programming, search, in-depth research, and tool calls. According to official reviews, it met or surpassed the trillion-parameter predecessor Ring-2.6-1T on most benchmarks.

17d ago
The AI sector is bloody. Why is Gavin Baker, a well-known investor, bucking the trend and bullish on AI?

The AI sector is bloody. Why is Gavin Baker, a well-known investor, bucking the trend and bullish on AI?

Abstract: Gavin Baker said that AI stocks fell by 40%-60% in July, which seriously deviated from actual fundamentals — after field research in Silicon Valley, he did not find any negative quantifiable indicators, and GPU rental prices rose 50%-60%. He believes that the only real risk is the tightening of the credit market, but if the operating cash flow of hyperscale cloud vendors accelerates as scheduled, the demand for debt financing will be drastically reduced. Regulation, on the other hand, is listed as the biggest tail risk. Markets are panicking, but Silicon Valley data tells a different story. Recently, well-known technology investor Gavin Baker revisited the sharp sell-off in the AI and semiconductor sector in July 2026 on the podcast program “Invest Like the Best”. Baker described this period as “compressing 2022 into one month,” and said that after weeks of field research in Silicon Valley, he couldn't find any negative quantifiable indicators. The trigger for the sell-off: a series of narratives, not fundamentals, Baker sorted out the trigger chain for the July market decline. First, Meta announced that it would rent out part of its computing power. The market interpreted this as a sign of “excess computing power and cutting capital expenses,” and the stock price immediately fell. But Baker thinks this is a misinterpretation — “Meta's capital expenditure plan hasn't changed at all; if anything, they've become more aggressive. “Meta then released the strong Llama model, further proving that it wasn't on the brakes. Immediately after that, open source models such as Kimi K3 were released, and structural changes occurred when superimposed on the Silicon Data Token Index. The market feared that the open source model would seize share and reduce AI infrastructure demand. Baker clearly refutes this: “Generating a token, whether open source or closed source, consumes exactly the same computing power — the same floating-point operations, the same memory, and the same power consumption. Open source grabbed share, but only transferred profits from the cutting-edge model layer to the AI infrastructure layer, and there was no negative impact on computing power demand. “Then there was the DUV lithography machine rumor, which caused the semiconductor equipment sector to plummet. Baker believes the market is overreacting, but it shouldn't be completely ignored either. The only real risk: Of all the triggers in the credit market, Baker only takes changes in the credit market seriously. “Real interest rates have risen and credit spreads have widened; these are undeniable facts. “He pointed out that the pricing of bonds issued by Meta last week was far lower than expected, and CDS spreads across the board for major tech companies. The core of the question is: How much debt financing is needed for large-scale AI infrastructure construction? Baker's judgment is that if the operating cash flow of hyperscale cloud vendors accelerates as planned, the need for debt financing will be drastically reduced. Citing data, he said that operating cash flow (non-free cash flow) of Microsoft, Meta, and Amazon has accelerated from 28% in the previous quarter to 32%. After excluding one-time items such as EU fines, the actual growth rate reached 35%. “This is a substantial acceleration at this volume. “He further estimated that if the computing power of hyperscale cloud vendors were to be monetized at the current Blackwell price rather than the lower previous generation price, operating cash flow could jump from the current consensus estimate of $1.3 trillion to $140 billion to about $2 trillion, thus removing about $700 billion in credit requirements from the market. “If repriced at current prices, construction over the next few years could be entirely self-funded from operating cash flow. “GPU prices: 50%-60% increase, which is completely contrary to expectations. Baker shared an example that he believes best explains the problem. A well-known startup leased a number of Blackwell clusters for around $2 per GPU per hour 7 months ago and expects to pay close to $4 when renewing the contract — an increase of about 50%-60%. “You would have expected a moderate drop in prices to be beneficial; the result was a vertical rise. “He also mentioned that an inference cloud company publicly stated on the podcast that it plans to pay 100% more for Blackwell after the contract expires. “This means that all hyperscale cloud vendors are underestimating their profitability. “Baker said the goal of his research in Silicon Valley was to “try as hard as possible to find negative data points,” but apart from the increase in Anthropic...

17d ago22#AI #Nvidia