kimi

Kimi leads spending on open-source large language models, with 61% going to China

Nearly 90% of U.S. companies’ spending on open-source large language models goes to China. Kimi dominates with a 61% share, followed by DeepSeek and Zhipu. This reflects how Chinese models are gradually becoming an important force in the global open-source ecosystem.#开源大模型 #Kimi #DeepSeek #Zhipu

How capable is the model, really?
You can’t judge by other people’s tests alone;
you have to try it yourself to know.

This morning, I spent nearly two hours scrolling through Twitter and saw quite a few bloggers testing Kimi 3.1 Pro:

Some said it was extremely capable;
others reported that it used up their quota too quickly;
and some felt it fell far short of expectations,
even calling it a failed model.

There could be many reasons behind
such vastly different test results.

So don’t take KOL reviews at face value.

If you want to get firsthand information,
you’ll have to try it yourself
and put it to the test in a real project.

#kimi

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

🚨 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

🔥 💎

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

【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

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

🚀 $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

🔥 💎

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

🚨 $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 OPENS WEIGHTS ON JULY 27 — 2.8T PARAMETER MODEL TESTS LIQUIDITY ZONE 📉

Entry: (not provided)
Target: (not provided)
Stop Loss: (not provided)

Moonshot AI unveiled Kimi K3 with 2.8 trillion parameters and a 1M token context window, positioning it near frontier US models on independent benchmarks. The full open weights drop under a permissive license on July 27 — a structural shift that could drain liquidity from closed-source AI tokens.

Developers on Arena ranked it first for front-end coding, and the mixture-of-experts design fires only 16 of 896 experts per token, keeping inference costs low. The real test is whether this supply-side catalyst restructures the AI narrative or gets swept by competing ecosystems.

Are you accumulating pre-weight release or waiting for confirmation on-chain?

Not financial advice. Always manage your risk.

#KIMI #AI #OpenSource #Crypto

🔥

$KIMI RESTRUCTURING FOR HONG KONG IPO — A NEW LISTING PLAY IN THE AI SPACE 🚀

The company behind Kimi AI has notified investors of a full restructuring and is targeting a Hong Kong IPO within the next 6 months. This is a major liquidity event for early backers and a signal that the project is maturing beyond just product hype.

Transaction volume on Kimi's native token has been picking up since the announcement hit top-tier exchange feeds. The narrative shift from "AI chatbot" to "public company" changes the long-term valuation floor entirely.

Are you holding through the restructuring or taking profits into the IPO hype?

Not financial advice. Always manage your risk.

#KIMI #IPO #AI #Crypto #Restructuring

🚀

🚨 $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 AI UNICORN AT $50B – THE NEXT MEGA MOMENTUM PLAY? 💎

💡 The Dark Side of the Moon’s flagship model is reportedly in Pre-IPO talks at a $50B valuation. That’s not just hype – it’s smart money positioning for the next AI wave. 📊 When AI giants start bidding at these levels, early speculative tokens often lead the charge in crypto.

⚡ Volume is already whispering on decentralized order books. This isn’t a retail pump – it’s institutional scent. 💬 Are you front-running the AI narrative before the crowd wakes up, or waiting for confirmation? 👇

⚠️ Not financial advice. Always manage your risk. 🛡️

🏷️ #KIMI #AI #PreIPO #Momentum #Crypto

🔥 🦈

$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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Day after day, one step at a time: Why can Kimi build K3? Yang Xinyu lists four sins among its peers

① Arrogance: Veteran teams believe the AI war is over and that they’ve already won.
② Impatience: Young labs lack solid fundamentals, and when they can’t keep up, they quickly pivot.
③ Cowardice: Their strength isn’t weak, but they’re afraid to set their sights on being #1 in the industry.
④ Misaligned goals: Everyone is fighting for personal credit, and no one truly cares whether the company can build AGI.

Yang Xinyu says what’s most different about the Dark Side of the Moon is that the founding team still has an intense drive to pursue AGI.

He also shared “Kimi’s Five Precepts”:
- Model companies should build models
- Do Research and publish papers through experiments
- When training models, look at metrics
- Don’t force it if it doesn’t work
- Don’t YOLO

In plain terms: tell fewer stories, do more experiments. Train by data, stop failing fast, and don’t rely on intuition to place big bets.

These four sins and five precepts are really about the same thing: most AI companies fail because they’re too eager to be “the boss,” not because they’re determined to “do the right work.” Kimi’s differentiation isn’t that it’s smarter—it’s that it’s more restrained.

#Kimi #K3 #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