kimi

🚨 IS $KIMI REALLY OVERVALUED AT 500 BILLION BEFORE ITS HONG KONG IPO? 📈

Smart money is dissecting the valuation math behind the hype. At a 500 billion target valuation, market multiples tell a far more subtle story when benchmarked against competitors like MiniMax and Intellispectrum. 📊

Post-K3 launch enterprise sales surged over 6x daily, meaning everything hinges on Kimi's actual revenue run-rate. 💡 If ARR clears 12 billion, the premium instantly compresses below peer averages. ⚡

Institutional capital is betting heavily on explosive post-launch momentum to justify the price tag. 🔍 Is this valuation pure speculation or a calculated front-run on AI revenue dominance? 👇

⚠️ Not financial advice. Always manage your risk. 🛡️

🏷️ #KIMI #AI #Valuation #PreIPO #Tech

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China’s homegrown open-source model is topping the charts again: Kimi K3.1 Pro scored 55 on the AA Intelligence Index, ranking 4th globally and 1st among open-source models. Its 65.7% score in terminal coding matches Claude Opus 5.5 and beats GPT-6 Astra by over 7 percentage points. At 2.8 trillion parameters, it’s still the world’s largest open-source model—but then you look closer: its generation speed of 73 tokens per second is below average, and the full weights won’t be released until before November 4. For now, you can only look at the leaderboard—you can’t try it yourself. The comments are divided: A: First place among open-source models is a big deal. Matching Opus isn’t worth bragging about? B: Until the weights are released, benchmark scores are just slideshows.

$BTC $ETH $SOL
#Kimi #AI #OpenSourceModels

I came across this post from Vitalik today: He can accept Kimi 3.1 deliberately leaving top-tier offensive cyberattack capabilities out of its training data—“Restricting by use is far better than discriminating by user identity.”

The key point: He says the world needs time to harden systems, audit legacy code, and formally verify new code so we can withstand even more powerful AI-driven cyberattacks down the road. If we mishandle the first wave of AI risks, it could easily slide into a dystopia of strict KYC, mass surveillance, and models tiered by nationality or credentials.

The line between capability restrictions and identity barriers is pretty clear—better to blunt the blade first than start labeling people.

#AI #Vitalik $ETH #Kimi

In the alignment debate, Vitalik has come down on the side of “restrict capabilities, not people.”

According to multiple reports, Ethereum co-founder Vitalik Buterin supports Kimi 3.1’s decision to remove advanced cyberattack capabilities from its training data. He emphasized that restricting capabilities based on use cases is preferable to discriminating based on users’ identities. He also warned that mishandling AI risks could lead to excessive model lock-in, pervasive surveillance, and social stratification.

How to read this: This is an AI safety and alignment issue, not just product PR. What’s more relevant to the crypto community is that open-source models, automated attack tools, and the attack surface of on-chain infrastructure could all grow at the same time. Going forward, it’s more useful to watch the public boundaries each model card sets around “offensive capabilities,” and whether legitimate red-teaming channels remain open for security research, than to focus on slogans.

#Vitalik #AI对齐 #Kimi #Security

【Market Flash】In the future, using AI may require passing KYC and being ranked by nationality—Vitalik has laid out this worst-case scenario. He accepted Kimi’s removal of top-tier offensive cyber training: first dial back its sharpest capabilities to buy time to strengthen legacy systems and audit code, rather than later resorting to locked-down models and blanket surveillance. Kimi’s benchmark score fell from 90.5% to 81.0%, and the weights will be released before November 4. Can this boundary hold?
$ETH $TAO $FET
#以太坊 #Kimi #AI Safety
(Source: BlockTempo)
⚠️Risk warning: The above is shared for market information only and does not constitute investment advice. Investing involves risks; please exercise caution.

Kimi releases K3.1 Pro, a 3T-parameter flagship with 1M context that ranks 4th globally and 1st among open-source models, rivaling GPT-6 Astra and Opus 5.5 on coding, 3D, and finance benchmarks. Which capability matters most to you?
#Kimi #K3 #GPT6 #Astra #Opus
https://aidisruption.ai/p/kimi-k31-pro-released

🚀 $KIMI UNVEILS KIMI K3.1 PRO – AUTONOMOUS 3D GAME & FINANCE ENGINE! 🟢

📊 The freshly dropped Kimi K3.1 Pro slams through the development pipeline, auto‑driving Godot builds and Blender renders without human touch. Its 1‑million token context and 2‑3× speed boost give it a clear edge in data‑heavy workflows.

🦈⚡ From flawless 3D vehicle physics to zero‑collision parking drills, the model also nails financial report extraction and valuation sensitivity runs – a dual‑play that could fuel institutional demand for the $KIMI ecosystem.

📌 If the weight files go open source in two weeks, the community can embed this engine directly into dApps, turning token utility into a real‑time AI service. 💬 How will this autonomous pipeline reshape token utility and institutional interest? 👇

⚠️ Not financial advice. Always manage your risk. 🛡️

🏷️ #KIMI #AIInnovation #SmartMoney #TechBreakthrough #Crypto

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Moonshot’s Kimi K3.1 Pro is here, along with a Highspeed version.

The official website says it’s currently one of the strongest models in their 3T-class open-weight lineup, with a context window of up to 1 million tokens. It scored 65.7% on Terminal-Bench 4.0, beating GPT-6 Astra’s 58.2% and just behind Claude Opus 5.5’s 66.4%. Its hallucination rate has also dropped significantly: in an internal stress test, single-sentence hallucinations fell from around 23.4% to 8.3%.

It’s now available on kimi.ai, Work, Code, and API; the full weights are expected to be open-sourced by November 4. The open-source landscape now has another model capable of going toe-to-toe with the closed-source frontier.#AI #Kimi

Moonshot AI launches Kimi K3.1 Pro: a 3T-class open-source model that deliberately “weakens” hacking capabilities

Reuters, 10/24 (Saturday): Moonshot AI launched Kimi K3.1 Pro, calling it the company’s most powerful open-weight model in the 3-trillion-parameter class, with a 1M context window. The weights are scheduled to be released publicly before November 4. A Highspeed version, 2–3 times faster, is also available.
The company said it removed data related to cyberattacks from its training corpus and reinforcement-learning environments. In internal cyberattack and defense tests, the model scored 81.0%, compared with 90.5% for a version that had not been modified (not independently verified).
According to company data compiled by The Context, the model scored 65.7% on Terminal-Bench 4.0, ahead of GPT-6 Astra at 58.2% and just below Claude Opus 5.5 at 66.4%.
Reuters also noted that China proposed last week restricting the export of technologies such as AI-powered malicious software generation.

【Take】
Open-source models are now approaching the closed-source leaders in agent capabilities. The focus of competition is shifting from “benchmark scores” to “open-sourcing safely and responsibly.” Deliberately reducing cyberattack and defense capabilities could pave the way for overseas compliance and regulatory approval. It also shows that AI cybersecurity risks have become a hard constraint on model releases.

【Opportunities/Risks】
1. Weights open on November 4: Watch for demand for self-hosting and inference compute rentals. Decentralized computing and AI stocks could see a sentiment catalyst.
2. The more powerful open-source models become, the more the pricing power of closed-source providers and the “AI capex returns” narrative may come under scrutiny. Next week’s earnings from Microsoft, Google, and Amazon will show whether cloud and AI revenue is delivering.
3. Risk: Benchmark scores are based on company-run tests. The AI sector has been under broad pressure recently, and thematic trades can move in and out quickly.

Do you think “deliberately weakening capabilities before open-sourcing” will become an industry standard, or is it just a compliance gesture? Share your thoughts in the comments.

#AI #Kimi #开源大模型 #AI安全 $FET $RENDER

For reference only; not investment advice

It’s a season of model releases, with open weights and inference speed both caught up in the race.

Moonshot AI has released Kimi 3.1 Pro (also referred to as the K3.1 Pro specifications): a mixture-of-experts architecture, roughly 2.8 trillion parameters, around 10.4 billion active parameters, and a claimed context window of up to one million tokens. It also touts capabilities in coding, CAD/Blender, financial modeling, and long-horizon agents. Alongside it, the company has launched a high-speed Pro API, which it says is around 2–3× faster than the standard version, while its open-weight release plans are also moving forward.

How to read this: For crypto, the significance is not just another chat model—it’s a shift in the infrastructure underpinning on-chain analysis, risk-control scripts, and agentic trading. Those who can reliably integrate long context and tool use into real workflows will be better positioned to benefit from the next AI×Crypto narrative, rather than merely jumping on the trending hashtag.

#Kimi #AI #开放权重 #Agent

A 17-year-old high school student jumps from Kimi to Anthropic, and the Chinese AI scene collectively loses it. Put plainly: three years of empty promises at a big tech company are worth less than someone else’s offer letter. Moonshot AI’s biggest contribution over the past few years isn’t Kimi—it’s been a steady pipeline of talent to Silicon Valley. If you can’t keep your geniuses, don’t blame them for reaching for greater heights. Don’t blame the kid; it’s only natural to aim higher. Blame the companies that treat geniuses as disposable, using them up and then tossing them aside. In the end, the AI race isn’t about the models—it’s about who can keep the people who build them. This round goes to Silicon Valley again. #AI #Anthropic #Kimi

What moves people most about a community
is not how many nice things are said.

It is that you can feel
that someone is truly building it and caring for it.
That is the beginning of all long-term value.

The growth of Kimi Ai
comes from everyone who takes part in it.
Maybe it starts with voluntarily locking up tokens.
Maybe the seeds of success were already planted in a meeting room at 3 a.m.
#kimi ai

#kimi k3#
Moon’s Dark Side co-founder, will release open-source Kimi k3. Wow— the world’s number one large language model is going open-source. How does this not kill OpenAI and Claude Code’s closed-source offerings? $BABA

$KIMI IPO RUMOR SHAKES THE AI SECTOR — THEN OFFICIALS SAY NOT TRUE ⚡

Headline-grabbing IPO rumors are rarely clean. A $3B Hong Kong filing from the Darkside of the Moon would have been a landmark event for the AI narrative — but the project just stepped in to kill the story. 📊

That denial matters more than the rumor itself. In absence of confirmation, markets trade the residual expectation: whether the AI funding wave finds another public listing vehicle. 🔍 Smart money treats these headline flips as volatility traps — prices spike on hope, then retrace on official word. 🌊

The key is watching how AI-linked assets digest this contradiction. ⚡ Are you fading the rumor or waiting for the real filing? 👇

⚠️ Not financial advice. Always manage your risk. 🛡️

🏷️ #KIMI #AI #IPO #CryptoNews #MarketStructure

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$KIMI K3 JUST BEAT ANTHROPIC'S OPUS IN AI BENCHMARKS 🔥

This benchmark data from an independent analyst shows the Kimi K3 model surpassing Anthropic's Opus 4.8, forcing U.S. labs to accelerate Opus 5 and GPT-6 releases. The gap between GPT-5.6 Sol and K3 is now negligible — meaning the next generation is coming sooner than expected.

When AI models leapfrog each other, the underlying narrative for AI-focused crypto projects strengthens. This kind of competitive pressure typically drives capital into the sector as anticipation builds. Are you positioned for the next wave?

Not financial advice. Always manage your risk.

#KIMI #AI #CryptoAI #Breakthrough #Narrative

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Valuation of the Dark Side of the Moon: $5 billion — Repricing after Kimi K3’s success

News: The Dark Side of the Moon is pushing forward with the final round of financing before an IPO, targeting a pre-investment valuation of $5 billion.

Looking back at the controversial April piece, “100 Hours Undercover as a Kimi Insider”:
- No KPIs, no hierarchy, no attendance requirements
- Researchers can sleep in naturally, and meetings can last for hours
- The team constantly debates around the model, with resources absolutely tilted toward the model

At the time, it was questioned as a “well-packaged PR article.” But after the release of Kimi K3, these organizational details began to take on a new interpretation: for a Foundation Model company, putting R&D at the highest priority may really be the optimal solution.

What’s truly worth关注 isn’t the label of “no KPIs,” but how the entire organization operates around a single shared goal.

AI company valuations are not only about model capability, but also organizational efficiency.

#Kimi #月之暗面 #AI #中国AI

🚨 $KIMI $3B HONG KONG IPO RUMOR HITS THE TAPE — FACT OR FICTION? 💥

The rumor mill just went into overdrive as Darkside of the Moon (Kimi) is reportedly prepping a Hong Kong IPO filing this month with a $3B raise on the table. But the project hit back fast, calling the report untrue. 🦈 That kind of headline whiplash creates serious two-way liquidity for anyone watching the AI narrative space.

Whether or not the filing ever lands, the reaction alone tells you the story: AI plays are commanding heavy flows, and every fresh headline moves the tape. 📊 This is a news-driven market, so the edge belongs to traders who respect uncertainty instead of chasing the loudest rumor. 💡

💬 When a high-profile denial hits a hot narrative, do you trade the volatility spike or wait for the official filing? 👇

⚠️ Not financial advice. Always manage your risk. 🛡️

🏷️ #KIMI #IPO #AI #MarketSentiment #CryptoNews

🎯 🦈

🚨 $KIMI SHRINKS 2.78T PARAMETERS INTO 8GB RAM — WITHOUT A GPU! 💥

🔍 This open-source experiment challenges every assumption about inference scaling. A 176KB pure C99 project runs Kimi K3's 1.56TB weight set on just 8GB of memory by streaming expert weights from NVMe storage on demand. 💡

The magic is MoE sparse activation — only 16 of 896 experts are active per layer. So the developer trades flash storage bandwidth for RAM, treating disk like a slow extension of memory. 📊 The tradeoff is brutal: one token every 32.7 seconds. That's not production-ready, but it's a structural blueprint for ultra-low-cost inference infrastructure.

The bigger signal is direction. 📉 As hardware bottlenecks force creative engineering, efficiency becomes the next narrative. Are we building the plumbing for the next wave of decentralized AI? 💬

⚠️ Not financial advice. Always manage your risk. 🛡️

🏷️ #KIMI #AI #MoE #OpenSource #Crypto

💡 🔥

Kimi K3 is a model from the “tough and doesn’t talk much” crowd. Not only is the front-end excellent, but to a certain extent its back-end performance also surpasses Fable5 and GPT-5.6 Sol.

Test result: Using GPT-5.6 Sol, find and fix 6 defects, then have Fable5 and Kimi K3 each conduct a review. Fable5 says “it’s ready to submit,” while Kimi K3 spots a serious PostgreSQL jsonb validation issue.

Regarding the controversy over Kimi Code’s harness—some say it isn’t done well, but the core logic is “a model company builds models.” As harness becomes less important, the model’s built-in capabilities are eating up the value of the harness.

This is actually the direction in which AI toolchains are evolving:
• harness is an add-on rules system; when the model’s ability is weak, it needs to make up the gap
• when the model itself becomes strong enough, harness shifts from being a “necessity” to a “constraint”
• Kimi’s built-in vertical capabilities—like its Tianyancha-style lookup—are more damaging than relying on a generic harness

China’s real-world AI model capabilities are narrowing the gap with, and in some scenarios even surpassing, Silicon Valley’s top players. Don’t just look at benchmark scores—look at the results of actual code reviews.

#AI #Kimi #大模型 #code review