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DeepSeek、安さの裏に“待った”あり!? 低料金でも長時間とX投稿

情報源 · 1 件の投稿
  1. SulkaMikehttps://x.com/i/status/2111788557832438100

安いAI、待ち時間までお得とは限らない!? XユーザーのSulkaMike氏が、AIモデル「DeepSeek」の料金と処理時間に注目したテスト例を紹介している。開発元の公式発表ではなく、同氏の投稿による報告だ。

投稿によると、あるテストではDeepSeekが約23セントでまずまずの結果を出したのに対し、Opusは6ドル。ただし、所要時間はDeepSeekが約1時間、Opusが20分だったという。お財布には優しくても、時計には厳しい比較だ。

同氏が紹介する別のテストでは、DeepSeekは約90分を要し、料金は14セント。比較相手のHaikuは8セントで、ずっと速く完了したという。こちらではDeepSeekが料金でも時間でも有利だったわけではない。

投稿者自身も、安いトークンが安い仕事を意味するのかと問いかけている。紹介されたテスト例だけでモデル全般の優劣は決められないが、料金表だけでは見えない「待ち時間」も、使い勝手を左右しそうだ。

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総パラメーター1兆超の〝重量級〟AI!「Mistral Large 4」公開とSunnyAIDock報告

情報源 · 1 件の投稿
  1. SunnyAIDockhttps://x.com/i/status/2109826460974256450

AI開発企業Mistralが、愛称「Le Chonk」のAIモデル「Mistral Large 4」のパブリックプレビューを2026年10月6日に開始したと、アカウントSunnyAIDockが報告した。総パラメーター1兆超の〝重量級〟だという。

同投稿によると、総パラメーター数は1兆500億、処理時に稼働するパラメーター数は490億。Mixture-of-Experts方式を採用しているとされる。総数と稼働数は別の数字だ。

性能指標「Artificial Analysis Intelligence Index」は、前モデル「Mistral Large 3」の9から38へ上昇したとも伝えている。ただし同投稿は、現時点のベンチマークがMistralまたは同社が引用する評価者による暫定的なものだと注意を促している。指標値は実際の利用での性能を保証しないという。

さらに同投稿は、Mistralが10月末までにモデルの重みを公開する計画で、非公開環境への導入やカスタマイズが可能になると説明している。公開済みと報告されているのはパブリックプレビューであり、重みの公開はまだ予定。〝重量級〟でも、そこは混同禁物だ。

Qwen「大か小か?」 vraj_aiが紹介する“大小両取り”公開説

AIモデル「Qwen」の予告をめぐり、投稿者vraj_aiが大小モデルの重み同時公開説を紹介した。引用されたQwenDevsの文言は「大きいのと小さいの、どっち?」。この引用文だけでは、具体的なモデルや公開条件は分からない。

vraj_aiによれば、Qwenは続いて「両方やる」と述べたという。その予告をQwen4-27BとQwen4-Maxの重み同時公開と読む人がいると紹介する一方、日程もベンチマークもまだないと説明。Maxの重み公開も「本当なら驚き」と条件付きだ。“両取り”の期待はあっても、公開確定の号砲と決めつけるのは早い。

別の投稿でlemonDefi1は、アリババがQwenの改良に「再帰的自己改善(RSI)」を使っていると報告し、Qwen 4.0系列の中核になる可能性にも言及した。

同投稿が引用したOluwaphilemon1の説明では、実利用ログから弱点を見つけ、訓練データを生成・検証し、主力モデルの訓練につなげる循環だという。AIが好き勝手に自分の重みを書き換える話ではなく、後続版を改良する訓練工程で、人の監督やデータ品質も重要だとしている。大か小かに加え、何がどう公開されるのか。そこは、予想と正式な発表を分けて見たい。

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Post reports Nvidia's China AI-chip share fell to 34% in H1 2026 as Huawei climbed to 28%

情報源 · 1 件の投稿
  1. liranzoaihttps://x.com/i/status/2110045518810198351

A post by user liranzoai reports that Nvidia's share of China's AI-chip market fell to 34% in the first half of 2026, while Huawei's share rose to 28%, with 572,000 accelerators shipped. The post quotes Nvidia CEO Jensen Huang as saying US export controls are handing Huawei the $50 billion market. The post also describes this as a direct sequel to a DeepSeek document from earlier the same day. The post does not provide independent verification of these figures.

Anthropic red team warns small AI models could self-replicate on consumer devices within months; OpenAI pledges $1B for cybersecurity

Two posts on October 13, 2026, reported significant developments in AI safety and investment. One post, from an account with handle greek2240, summarized a series of AI news items, including OpenAI's announcement of a $1 billion cybersecurity commitment called 'Daybreak for Frontline Defenders.' The post said the program would subsidize security tool usage for critical infrastructure teams, with two tiers: Blue for regular defense and Red for audit agencies. It also mentioned that 2,000 institutions and thousands of defenders are using the tools, with a US-first rollout over six months. The same post reported that Anthropic's Frontier Red Team published research on AI self-replication, claiming a 9B model ran on 8 of 9 hardware devices tested, and that GLM-5.2 was the only open-weight model to complete a full end-to-end replication cycle. The post also noted DeepSeek's planned lead investment in Winverse AI, a company founded by former Tencent chief scientist Hu Han, with a post-money valuation of about $400 million. Another post, from an account with handle ailabswire, independently reported on Anthropic's red team findings, stating that small AI models may be months away from self-replicating on smart TVs and ovens, with a 9B model running on 8 of 9 devices and GLM-5.2 completing the full copy-and-spread cycle in simplified evals. The post emphasized that this is controlled research, not an incident, and that the threat is months away, not imminent. Both posts attribute these claims to their respective sources, and the reports have not been independently confirmed.

Anthropic reports 16M+ Claude exchanges via 24,000 fraudulent accounts; names DeepSeek, Moonshot, MiniMax in distillation crackdown

Two posts on X report that Anthropic has published details of large-scale attempts to distill its Claude model, naming DeepSeek, Moonshot, and MiniMax as the labs behind the campaigns. The first post, by user stretchcloud, says Anthropic identified more than 16 million exchanges with Claude run through roughly 24,000 fraudulent accounts, aimed at harvesting outputs to train rival models. The post attributes the claims to Anthropic, citing IP correlation, request metadata, and infrastructure fingerprints. It also quotes Anthropic's official account: 'Over the last few months, we've made significant progress in reducing the effectiveness of distillation attacks against Claude.' The post adds that Anthropic has cut the effectiveness of these campaigns sharply using rate limits and behavioral detection, and notes the economics: training a frontier model can cost over $100 million, while distillation costs a fraction. A second post, by user 24moonbridge, reports additional details from Anthropic's announcement, focusing on Chinese labs. It says Zhipu and Moonshot were 'publicly executed' for industrial-scale theft of Claude's chain-of-thought. The post provides figures: with full chain-of-thought, SWE-bench reaches 80.4%, versus 71.8% with simplified answers, an 8.6-point gap. It describes three attack vectors: Alibaba-affiliated operations from May to July with 151 million conversations, a peak of 3 million per day, and 3,500 fake accounts; Moonshot rerouting 300,000 user requests from Kimi to Claude over 10 days; and Zhipu running 3.4 million requests over 17 days with 273 accounts targeting Claude Fable 5's cybersecurity capabilities. The post also reports Anthropic's countermeasures, including locking reasoning context, a two-stage constitutional classifier with false-positive rate below 0.1%, and charging for blocked requests starting September 24. It claims stolen data volume was cut by 90%–99%, at the cost of rejecting trillions of tokens of paid traffic. Both posts are reports of Anthropic's announcement; the second post includes a note that one Moonshot request came from a user with suspected PLA background, but this is not independently verified. The posts do not provide independent confirmation of Anthropic's claims.

DeepSeek reportedly in talks for up to $12B+ funding round, mulls robotics push

Multiple social media posts report that Chinese AI company DeepSeek is preparing a major new funding round, with amounts ranging from RMB 80 billion to RMB 100 billion (about $12 billion to $15 billion). A post by OpenBuildxyz, summarizing last week's China AI news, says DeepSeek is reportedly set to raise more than RMB 80 billion (~$12B), potentially reaching RMB 100 billion, with Tencent and CATL among expected backers and a target valuation of around RMB 500 billion (~$74B) ahead of a possible domestic IPO. Another post, from BreakingAlert_, states in Chinese that DeepSeek will complete 100 billion yuan in financing and is also considering entering embodied intelligence, with founder Liang Wenfeng reportedly in intensive talks with related entrepreneurs. These are separate reports; the exact terms and participants are not independently confirmed. In a separate development, a post by shihaodduan reports that DeepSeek is leading a seed round for robotics AI startup Winverse AI, investing several tens of millions of dollars at a post-money valuation of about $400 million, with founder Hu Han, a former Tencent AI scientist, and Meituan Longzhu also participating. A post by Zekunnnnn, quoting a Business article, similarly reports that DeepSeek aims to lead the first round for a months-old startup building AI for robots, using capital from its own $12 billion-plus financing. The posts describe DeepSeek's move as part of a broader trend of AI model companies investing in robotics, though the company has not made an official announcement.

Qwen Image 2.1 Pro and Turbo models announced with 2K generation and fast 8-step output

情報源 · 1 件の投稿
  1. icreat_aihttps://x.com/i/status/2109920517390291375

A post by the account icreat_ai announces the release of Qwen Image 2.1 Pro and Qwen Image 2.1 Turbo, two new image generation models from the Qwen family. The post describes Qwen Image 2.1 Pro as offering exceptional 2K high-fidelity generation, precise prompt following, and studio-grade details. Qwen Image 2.1 Turbo is described as providing blazing-fast 8-step generation, delivering maximum quality at unbeatable speed and efficiency. The post also claims that in a real test, the Turbo model can output one image in about 3 seconds. The announcement was made on October 13, 2026, and includes the hashtags #Qwen, #QwenImage, and #AIart. The post is a single source report and has not been independently confirmed.

Muse Wonder launch announced as closed-source frontier model family, breaking from Llama's open-weight legacy

情報源 · 1 件の投稿
  1. aiwaremaxhttps://x.com/i/status/2109810914807648417

A post by aiwaremax reports the launch of Muse Wonder, a new family of frontier models, citing an announcement from the official account. The post says independent evaluation by Artificial Analysis gives Wonder Full a score of 56, tying Claude Sonnet 5.5 and surpassing GPT-6 Astra's 53. API pricing is listed at $4/$20, in the same tier as GPT-6 Sol and Claude Opus 5.5, but the post notes Wonder Full is not available via API and is exclusive to Muse Code subscribers. The post highlights features called 'Active Memory' for cross-session long-term memory and 'Active Focus' for multi-step agent reliability, with a context window of 1 million tokens. The post emphasizes that this release is fully closed-source with no weights published, marking a complete departure from the open-source approach associated with Llama. The quoted announcement from the official account reads: 'Introducing Muse Wonder, our new family of frontier models with state of the art performance for personal and professional agentic work.'

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