deepseek

🚀 $AI FLASHING INTO THE MARKET WITH DEEPSEEK V4.1 BREAKTHROUGH 🦈

DeepSeek just dropped V4.1 Flash, a 552B beast that runs on a lean 8B/16B activation split. 📊 The architecture slashes HBM demand to a quarter and SSD to an eighth, meaning AI compute costs tumble while performance spikes. ⚡

For $AI token holders, this efficiency upgrade is a liquidity magnet – whales can flood the order book without burning cash, setting the stage for a bullish wave. 🌊 Smart‑money is already eyeing the next swing, so keep eyes on volume spikes and on‑chain inflows. 🦈

💬 Are you positioning for the AI‑fuelled rally or waiting for the next price correction? 👇

⚠️ Not financial advice. Always manage your risk. 🛡️

🏷️ #AI #DeepSeek #AIModel #Crypto

🔥 💎

AMERICA ACCUSES CHINESE AI FIRMS OF “DIGESTING” U.S. AI MODELS

U.S. law enforcement and intelligence officials are accusing DeepSeek, Moonshot AI, Alibaba, and three other Chinese AI companies of using a method described as “distillation” to train models based on technology from U.S. companies such as OpenAI, Anthropic, and Google.

According to the allegations, the scale of this activity could be very large and may have been carried out with advance knowledge of the Chinese government.

Washington warns that this is not just about commercial competition. If Chinese models can rapidly absorb capabilities from advanced U.S. AI systems, they could help enhance China’s military capabilities and cyberattacks.

My take: the AI battle is shifting from “who can build better models” to “who can absorb the opponent’s capabilities faster.” If these allegations are proven, this would be a major issue for the technological advantage of U.S. AI companies.

AI competition is getting less about training and more about stealing the shortcut.

Do you think distillation is a normal AI technique, or is it becoming a weapon in the U.S.–China technology war?

#BrainrotCrypto #AI #DeepSeek #USChinaTechRace

📰 DeepSeek has commissioned Citic Securities to prepare for a STAR Market (科创板) IPO, with plans to initiate the relevant process within this year. The exact amount to raise and the target valuation are not determined yet, which means it’s still too early to talk about a final listing price.

🔥 But this is not a small matter. DeepSeek is currently in a new round of fundraising, targeting a valuation of around RMB 500 billion, or approximately USD 75 billion. As recently as this past June, the company completed a fundraising round of about USD 7.4 billion at a post-money valuation of over USD 50 billion.

💡 Among the investors at the time, founder Liang Wenfeng contributed RMB 20 billion, Tencent invested RMB 10 billion, and CATL invested RMB 5 billion. Several institutions also became key external shareholders as a result. Honestly, this roster of shareholders is already quite noteworthy.

👀 The company plans to use funds raised via the IPO to keep investing in compute infrastructure, model R&D, and in-house chip development, while also strengthening incentives for core talent. In short, the money is mainly going into compute power, technology, and people—not just making moves at the capital level.

🤔 The biggest question now is what valuation DeepSeek will ultimately achieve, how much it will raise, and whether the STAR Market IPO can truly be launched within the year. Do you think the market attention when it lists will be higher than that of the fundraising round in June this year?

#DeepSeek #人工智能 #科创板 #芯片算力

DeepSeek kicks off a new round of financing, with a pre-money valuation of about US$71 billion. Last month, ARR reached US$500 million; this year, AI infrastructure spending has already reached US$1.6 billion.#DeepSeek
#AI

📰 U.S. law enforcement and intelligence officials have turned their attention to Chinese AI companies. According to Reuters, six companies, including DeepSeek, Moonshot AI, and Alibaba, were accused of using “distillation” to train their own products with models from U.S. companies such as OpenAI, Anthropic, Google, and SpaceX.

🔥 It’s important to keep things straight: what has been disclosed is the accusations made by the U.S. side, not a conclusion that has already been proven. The U.S. side also claims these activities may have been carried out with the knowledge of the Chinese government, but the excerpted report does not provide corporate responses or additional evidence.

Honestly, model distillation is a common technical approach in the AI industry. But once it’s placed directly in the context of law enforcement, intelligence, and national security, it’s no longer just a technical dispute.

⚠️ The U.S. side further warned that the relevant capabilities may enhance China’s military and cyber-attack capabilities. That’s a very serious statement, and it also means that the China–U.S. AI competition is moving beyond chip and compute constraints to extend into the model training methods.

🤔 If, going forward, the U.S. really imposes restrictions based on “distillation,” who do you think will be affected first: Chinese AI companies, or model providers like OpenAI and Anthropic?

#人工智能 #DeepSeek #中美科技 #Web3 observation

📰 DeepSeek Open Platform Announcement: Starting at 12:00 PM (Beijing time) on September 10, the pricing for calls to the Flash series models has been reduced.

This isn’t just a simple, uniform discount. Cache hits, cache misses, and output prices are all adjusted separately.

🔥 Honestly, the biggest drop is in the cache-hit pricing. For scenarios with repeated calls involving similar content, cost changes will be more direct. Cache-miss pricing and output pricing are also lowered, but the reductions are not as large.

In reality, API price adjustments like this affect more than just developers’ bills. They also make it easier for everyone to re-evaluate how they use model calls: which requests are suitable for caching, and which content is worth handling with Flash—these choices become simpler to compare.

💡 The announcement states the changes take effect tomorrow at 12:00 PM. It’s already quite close. Teams building AI tools, robots, or automation services will likely first review their call structure and costs.

🤔 Will you increase your usage of DeepSeek Flash calls because of this price cut?

#DeepSeek #AI #API #加密行业

DEEPSEEK JUST DECLARED WAR ON AI API PRICES. 💀

DeepSeek will cut the price of its Flash API line starting at 04:00 UTC on 10/9.

Maximum discounts:
Cache hit: -60% Cache miss: -33.33% Output: -11.11%
AI API market right now:

DeepSeek: “Prices are too high.”
Everyone else: “Bro, what are you doing?” 💀

Up to 60% off for cache hits is quite aggressive, especially for workloads with a high cache hit rate.

Do you think this AI API price war will benefit developers—or will models ultimately race to the bottom?

#DeepSeek #Aİ #api3update #BrainrotCrypto

📰 DeepSeek releases v4.1 Flash beta. This time it uses a brand-new architecture, and the focus is very straightforward: native multimodal, stronger capabilities, faster speed—while continuing to drive costs down.

🔥 The way to call it hasn’t been complicated for developers. You don’t need to change your existing base_url—just replace the model name with deepseek-v4.1-flash-expires-on-0910 to connect. The account-level concurrent request limit is 20, clearly indicating it’s still in a limited trial stage.

💡 What’s even more interesting is that the current pricing for v4.1 Flash is the same as deepseek-v4-flash. Honestly, if the new version really can deliver multimodality, speed, and capability at the same price, then what everyone cares about most isn’t the parameter table—it’s whether, in real tasks, you can spend less and wait less time.

👀 The model name directly includes expires-on-0910, suggesting this test window may be pretty short. If you want to try it, you’ll need to move quickly—but don’t jump to conclusions after just a few simple questions. The real answers on multimodal performance, stability for long-running tasks, and behavior under high concurrency can only be verified through actual calls.

🤔 If you could test only one thing first, would you prioritize its multimodal capability—or use the same tasks to compare the speed and cost against v4 Flash?

#DeepSeek #人工智能 #AI模型 #Technology Frontiers

📰 DeepSeek suddenly posted around 150 senior backend and server-engineer positions. This isn’t just filling a few openings—it’s because a new direction, new systems, and new requirements are all coming in at the same time.

🔥 The most interesting part of this recruiting post is the official explanation: after the scale of computer systems grows, complexity rises exponentially. The amount of data is increasing, the number of machines and containers is increasing, and training and evaluation tasks are expanding in step.

To be honest, when many people see AI companies expanding hiring, their first reaction is that the model needs to be upgraded again. But based on this round of job types, what DeepSeek needs to add most are backend and server engineers—suggesting that large-scale systems themselves have already become a very heavy engineering challenge.

💡 The figure of 150 HC also shows that after the new direction takes shape, the real drain on manpower isn’t necessarily only algorithm research. How to make the system handle more data, more machines, and an ever-growing number of training and evaluation tasks will all become responsibilities for the backend team.

🤔 What do you think this hiring round is for—preparing for the next wave of products and models, or simply because the current systems are so complex they must expand the team? Would you consider applying for roles like these?

#DeepSeek #人工智能 #后端工程师 #TechnologyRecruitment

DeepSeek’s founder is quietly positioning for China’s next IPO wave.

Liang Wenfeng, the founder of DeepSeek, is taking High-Flyer, the quantitative fund behind DeepSeek, deeper into China’s pre-IPO market.

High-Flyer is said to have participated in pre-IPO deals in sectors that Beijing is prioritizing, such as AI, semiconductors, and robotics, including CXMT and Unitree Robotics.

What’s notable is that this strategy isn’t just about investing.
DeepSeek is reportedly aiming for an IPO on the STAR Market in Shanghai, turning the AI company that once jolted global markets into one of the major candidates in China’s technology IPO wave.

If this model succeeds, Liang Wenfeng won’t just be building an AI lab.

He is using quant + AI + private markets to gain access to an entire technology ecosystem before it goes public.

The AI race is becoming an IPO race too.

What do you think—could DeepSeek’s IPO become the next boost for China Tech, or is the Chinese market pricing AI too far beyond fundamentals?

#DeepSeek #Aİ #ChinaTech #IPOWave

DeepSeek was reported to have revenue of about 10 times the whole of last year in the first seven months of this year, with an API business gross margin of 82.9%. The company is also seeking a second round of external financing.

The proposed financing is to raise RMB 50 billion at a valuation of RMB 500 billion, and the company has already hired an investment bank to prepare for an IPO in Shanghai next year. In June, it just completed its first round of external financing of RMB 50 billion.

On the revenue side, in the first seven months revenue was RMB 475 million, and its net loss narrowed to RMB 715 million. Overall gross margin was 44.6%. After the adoption rate of the V4 series increased, annualized revenue is reportedly expected to reach between USD 400 million and USD 500 million.

During the same period, spending on AI infrastructure increased to RMB 11 billion, mainly used for server rentals and the purchase of AI chips and computing equipment. With heavy investment and improvements in profitability occurring at the same time,

For market observation only and does not constitute investment advice.

#DeepSeek #AI #融资

Bitcoin has just surged past $80,000, and DeepSeek’s gross margin is 82.9%! So what is this AI compute narrative that’s about to take off?

Yesterday, the “big pie” hit as high as $81,270 intraday—up 24% over the week—its best performance since 2023. The market greed index is at 80, extremely greedy. But right at this moment, DeepSeek’s numbers are even more explosive: in the first 7 months, revenue was 475 million, which is 10x the full-year figure from last year. API business gross margin is 82.9%, and overall gross margin is 44.6%. The most wild part is that during the peak of V4‑Pro, its output price was raised from $0.87 to $3.96—what confidence is behind that? AI infrastructure investment skyrocketed from $1.2 billion last year to $11 billion in the first 7 months.

Our view is pretty simple: the AI compute race is replaying the logic of the 2021 DeFi Summer. DeepSeek’s valuation is $500 billion, and there’s talk of a Shanghai IPO next year. This isn’t just an AI story—compute equals power, power equals narrative, and narrative equals liquidity. With the big pie breaking $80k this time, the backdrop includes the U.S. Treasury’s debt-repurchase liquidity easing plus Trump pushing the Clarity Act. But the next narrative to take the baton is likely the AI x Crypto track.

What should retail investors do? Don’t chase the big pie at the highs—watch the pullback for support around $78k. Focus on the underlying infrastructure projects at the intersection of AI and blockchain: compute rental, decentralized inference, and other directions—these could be the engine powering the next leg of the main upswing.

Which sector do you think this AI narrative can take off? Chat in the comments.
#DeepSeek #OpenAI据报完成新一代Bel模型预训练
$BTC $ETH $ZEC

🚨 DEEPSEEK FLASH WAS TOO CHEAP. THEN REALITY SENT THE BILL. 💀

DeepSeek V4 Flash previously increased its usage on OpenCode from about 3T → 18T tokens/day in just around two weeks, nearly 6x.

Then on August 16:
💰 DeepSeek increased prices.
V4 Flash output went from $0.28 → $0.66/M tokens outside peak, and to $1.32/M tokens during peak hours.

Results reported from OpenCode data:
→ Token usage fell by more than 50% from the peak
→ About 10T tokens/day “disappeared”
→ OpenCode is said to require around 1,000 B300 GPUs to meet current demand

It’s a very simple equation:
Cheap + Powerful + Massive Scale
Pick 2.

AI users:
“Make AI cheaper.”
GPUs:
“Absolutely not.” 💀

DeepSeek Flash just showed the market a bigger problem:
AI inference isn’t just a battle of models.

It’s a battle of compute economics.

If demand keeps rising but GPUs aren’t enough, the question isn’t:
“Which model is the best?”

It becomes:
“Does AI have enough compute to run it at massive scale?”

Do you think AI is entering an era of compute shortages, or will GPU/cloud companies quickly bring inference costs back down? 👀

#BrainrotCrypto #DeepSeek

🤖 DEEPSEEK-V4-FLASH IS BASICALLY SAYING: “$0, COME BUILD.” 💀

B.AI continues to expand its unlimited free DeepSeek-V4-Flash program, letting users experience the model on both the Web and API for $0.

Notable points:
→ DeepSeek-V4-Flash: free
→ Free expansion for both Web + API
→ Smart routing to optimize cost + performance
→ Supports long context up to the level of millions of tokens
→ Optimized for Agent workflows and heavy workloads
→ Payment integration for both Web2 + Web3
→ Aiming for infrastructure for AI Agents / AGI

B.AI is playing a pretty obvious game:

AI infrastructure + smart routing + crypto payments + agent economy.

Developer:
“How much is this API?”
B.AI:
“$0.”
Developer:
“Okay, so how do you make money?” 💀

But this is the part that’s worth watching.

If free access attracts developers into the ecosystem, the long-term advantage may not be in selling individual API calls—it may be in the routing infrastructure, model marketplace, agent deployment, and the payment rails behind it.

AI is moving from:
“Chat with a model”
to:
“Build an agent that actually does shit.” 💀

Do you think the free-AI strategy → pulling developers → monetizing infrastructure can scale, or is this just the next round of AI burning money?

#DeepSeek #DigitalSchizophrenia

🦈 $DEEPSEEK ROUTING MYSTERY — THREE HIDDEN MODELS OR ONE RL-CALIBRATED ENGINE? 🧠

📊 The AI community cracked a 30-point performance gap across the same V4-Pro API — but the variable isn't the model weights. 📌 The Aug 10 Harness commit reveals the real edge: aligning the Minimal Agent with RL training distribution unlocks the highest scores. 💡 That's structural insight, not hocus-pocus.

🔍 Same brain, different environment. DSH Minimal hits 99/96 versus Standard's 91 — because the model performs best inside the exact scaffolding it was optimized against. The "God Mode" isn't a bigger model, it's a closer fit to the training envelope. ⚡ The Anchored Standard hack proves it: reset the initial tool schema, restore full tools after — 98/99 repeatedly.

Official docs deny multi-model routing. So the edge lives in context, not weights. 💬 Is the market pricing the AI "liquidity" rumor as alpha, or just chasing confirmation bias? 👇

⚠️ Not financial advice. Always manage your risk. 🛡️

🏷️ #DEEPSEEK #AI #SmartMoney #Analysis #Crypto

🔥 💎

#deepseeklaunchesharnesscodeagentbeta
🚨 DEEPSEEK’S NEW AI CODING AGENT EXPLODES! 🤖
DeepSeek launched Harness v0.1, an open-source AI coding-agent framework, and its GitHub repo crossed 33K+ stars within hours.
🧠 Built around the new DeepSeek-V4-Pro, Harness uses a modular plugin-based design and is released under the MIT license, aiming to compete with tools like Claude Code and Qwen Code.

🎯 TRADING VIEW: BUY 📈
Strong developer adoption could boost the AI ecosystem and related sentiment, but watch whether the early hype translates into sustained usage.

❓ Is DeepSeek becoming a serious threat to existing AI coding agents? "CLICK ON THE BELOW YELLOW COIN TAG TO GO TO DESIRED TRADING PAGE TO GET BENEFIT TRADE"$TUT $AKE $EDEN
#DeepSeek #AICoding

DeepSeek finally isn’t just racing to build better models: What Harness really wants to steal is the “AI work entry point”
On August 13, DeepSeek Harness opened a developer preview and released its source code. The name sounds very technical—one-sentence translation: previously, DeepSeek mainly focused on “using its brain,” while Harness starts taking responsibility for equipping AI with hands and feet and a toolbox.
It can combine capabilities such as models, tools, skills, sandboxes, storage, and task orchestration. In other words, AI is no longer just answering “how to write code,” but is beginning to move toward “reading files, calling tools, executing tasks, and completing workflows” on its own.
That’s more worth watching than simply re-ranking model leaderboards again.
In the past, AI companies competed over: whose model is smarter.
Now, Claude Code, Codex, and DeepSeek Harness are competing in a way that’s increasingly like: who can truly take over the user’s workflow.
This is also why I’m paying more and more attention to agents. Model capability is of course important, but once everyone can ultimately reach an 80–90 score, the real differentiator may become: who can call more tools, connect more data, complete longer tasks, and make fewer mistakes.
The next round of AI competition might not be “who can chat best,” but who can actually do the work for you.
#DeepSeek #AI #deepseek推出harness代码智能体公测

#DeepSeekLaunchesHarnessCodeAgentBeta
💻 DeepSeek Harness — an agent-builder assembled like Lego!
On August 13, DeepSeek released Harness v0.1 to the public beta as open-source (MIT). This isn’t just another Claude Code—it's an agent framework where everything is a plugin: models, tools, and the interface. Already, there are 300+ plugins available. It competes with OpenAI Codex and Anthropic Claude Code. It works with the formula Model + Harness = Agent.
Along with the launch, DeepSeek introduced peak pricing for its API—starting August 17, prices will be half during off-peak hours.

🔥 Do you think Harness will become the main tool for developers, or will Codex take the lead? Write in the comments! 👇

#DeepSeek #AI #Trade 👇

​#deepseeklaunchesharnesscodeagentbeta
​🚀 The Real Catalyst: Decoding DeepSeek’s Open-Source Harness

​The market is focused on model drops, but DeepSeek just pulled off a masterstroke by open-sourcing their infrastructure.

​The launch of DeepSeek Harness (dsh v0.1) (MIT-licensed) is a massive leap forward for decentralized AI development. Here is the technical breakdown of why this matters:

​1️⃣ 100% Plugin Architecture

There are no rigid structures here. From the UI to the sandboxes and agent loops, every single component is an independent plugin.

2️⃣ Frictionless Workflow Integration

Need a specific operational flow? You can instantly compose and swap environments (like mimicking Claude Code) using Cordis, requiring absolutely zero source code modifications.

3️⃣ Flawless Traceability

Debugging complex agents just became effortless. The system utilizes append-only logs, allowing you to fork, resume, or perfectly replay previous sessions.

​DeepSeek didn't just give us a new brain (V4-Pro); they gave us the entire nervous system (the Harness). The competition has officially shifted from model capabilities to runtime execution. 🌐🔥

#DeepSeek #AIAgents #CryptoNews

$FET
$TAO
$NEAR

🚀 DeepSeek V4 Pro Officially Released: API Price Increases by 50%, AI Agent Framework Ignites the Developer Community!

Another major breakthrough from China’s large-scale models! DeepSeek has announced that its V4 Pro model will go live on August 17, with API pricing raised by 50% to $1,100.

🔥 The accompanying Harness v0.1 Agent product quickly racked up over 22,000 GitHub Stars, showcasing the formidable dominance of homegrown models in the developer community.

New infrastructure for AI + Web3—worth tracking for the long term!

#DeepSeek #人工智能 #大模型 #Web3AI