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实测帖:DeepSeek V4.1 Flash 搬上桌,速度亮眼,内存吃紧

把模型搬到桌上,难点不只是跑起来,还得看跑起来之后剩下多少余量。

测试者 @yume_arasaki 发帖称,自己试跑了一晚由 @sudoingX 提供的部署方案:用两台桌面设备 DGX Spark 运行 DeepSeek V4.1 Flash。这篇帖子谈的是部署和推理表现,而不是模型发布。

按作者报告,在单路、关闭思考的测试条件下,结构化输出达到 135.5 token/秒,散文输出则为 57.2 token/秒。这里最容易被忽略的限定是:输出类型不同,速度差得很明显,不能把结构化输出的成绩当成所有任务的通用速度。

作者解释,提速依赖“先猜、再验”:小型预测头猜测后续 token,再由完整模型校验。结构化内容更容易猜中,自由文本则更难。他还提到,方案压缩了专家权重,并让 DeepSeek 的 Engram 查找表不进入内存,而在查询时直接从 NVMe 读取。

代价也写在帖里:这套配置只支持两个并发请求,上下文上限为 262k token。作者称,权重加载后剩余内存已经很紧张,提高上下文上限还要继续消耗内存。

对想在桌面跑智能体任务的人来说,这份测试的价值不只是一个速度数字,也是一张容量提醒:桌面能跑,不等于任务可以随便加。

往期 Chatter 报道

帖文称Mistral Large 4开启预览:万亿参数亮相,权重还在路上

账号SunnyAIDock发文称,AI公司Mistral已于2026年10月6日推出Mistral Large 4的公开预览。按该帖文的说法,这款模型采用混合专家架构,总参数达到1.05万亿,激活参数为490亿。

数字确实醒目。帖子还将它与上一代Mistral Large 3对比,称Artificial Analysis Intelligence Index分数从9升至38。不过,帖子同时提醒:现阶段基准结果来自Mistral或其引用的评测方,仍属初步结果,指数分数并不保证真实场景中的表现。

比参数更值得企业用户留意的,是权重发布计划。SunnyAIDock称,Mistral计划在10月底前发布模型权重,以支持私有部署和定制。若计划兑现,用户关注的就不只是模型能答什么,还包括如何部署、如何按自身需求调整。

因此,别把“公开预览”直接读成“权重已经开放”,也别把指数上涨直接读成应用效果已有定论。这则帖文带来的看点,是模型预览与后续权重发布计划;后者仍需等待兑现。

Qwen问「大还是小」,网友猜大小模型同时开放权重

阿里的Qwen大模型把悬念压缩成了一个选择题。QwenDevs账号的引文只写着“big or small?”(大的还是小的?)。vraj_ai在转帖中称,Qwen随后表示两种都做。问题很短,但它本身并没有确认具体型号或开放权重。

vraj_ai称,有人将这则预告解读为Qwen4-27B与Qwen4-Max同时开放权重;他也明确写道,目前没有日期,也没有基准成绩。因此,“大小一起做”是转帖者报告的后续说法,“具体哪两款、是否开放权重”则仍是猜测,不能合并成一份发布公告。

另一条线索来自lemonDefi1引用的Oluwaphilemon1帖文。后者称,阿里据报正用递归自我改进(RSI)优化Qwen模型。该帖描述的流程,是分析实际使用日志中的短板、生成训练数据、由较小模型检查,再用筛选后的数据训练主模型并重复这一过程;它同时强调,这不等于模型随时自主改写自身权重。这里谈的是被报道的训练流程,不是开放权重公告。

对读者而言,悬念不只是模型“大不大”,还在于权重是否真的开放。眼下,官方提问、网友解读和技术流程转述,仍是不同层次的信息:可以期待,但别替官方按下“发布”键。

热议 / MCP

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

来源 · 1 条帖子
  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

来源 · 1 条帖子
  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

来源 · 1 条帖子
  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.'

脉动 / MCP

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