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deepseek
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DeepSeek第二轮融了1000亿，众生相如下：
梁文锋：别人融资是求资本，我这是挑资本。钱可以分，方向盘别碰，五年锁死没投票权，爱投不投。
腾讯宁德时代：老股东续杯，基石位再加码。
完美世界世纪华通：主业做游戏，副业给AI打钱——游戏佬的尽头是算力。
散户：1000亿跟你半毛钱关系没有，股权吃不到，只能去看币圈AI土狗连夜改白皮书，把"AI"两个字加粗三号。
最扎心的是：认购火爆到从500亿翻倍到1000亿，投前估值5000亿纹丝不动——这不是融资，这是发号施令：AI这桌，散户没座位。
评论区开盘：A队AI叙事回暖、币圈AI板块跟涨；B队融资归融资、土狗照样归零。报数。
#DeepSeek #AI
$BTC $ETH $SOL
DeepSeek第二轮融了1000亿，众生相如下：
梁文锋：别人融资是求资本，我这是挑资本。钱可以分，方向盘别碰，五年锁死没投票权，爱投不投。
腾讯宁德时代：老股东续杯，基石位再加码。
完美世界世纪华通：主业做游戏，副业给AI打钱——游戏佬的尽头是算力。
散户：1000亿跟你半毛钱关系没有，股权吃不到，只能去看币圈AI土狗连夜改白皮书，把"AI"两个字加粗三号。
最扎心的是：认购火爆到从500亿翻倍到1000亿，投前估值5000亿纹丝不动——这不是融资，这是发号施令：AI这桌，散户没座位。
评论区开盘：A队AI叙事回暖、币圈AI板块跟涨；B队融资归融资、土狗照样归零。报数。
#DeepSeek #AI
$BTC $ETH $SOL
梁文锋：别人融资是求资本，我这是挑资本。钱可以分，方向盘别碰，五年锁死没投票权，爱投不投。
腾讯宁德时代：老股东续杯，基石位再加码。
完美世界世纪华通：主业做游戏，副业给AI打钱——游戏佬的尽头是算力。
散户：1000亿跟你半毛钱关系没有，股权吃不到，只能去看币圈AI土狗连夜改白皮书，把"AI"两个字加粗三号。
最扎心的是：认购火爆到从500亿翻倍到1000亿，投前估值5000亿纹丝不动——这不是融资，这是发号施令：AI这桌，散户没座位。
评论区开盘：A队AI叙事回暖、币圈AI板块跟涨；B队融资归融资、土狗照样归零。报数。
#DeepSeek #AI
$BTC $ETH $SOL
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美国政府下令清除DeepSeek：盯紧AI聊天机器人，停止采购！
美国政府要求所有政府机构从其系统中移除DeepSeek人工智能聊天机器人，并禁止新的采购。这款开源模型曾引发关注，现在却被列为重点监控对象。盯紧资金流向，了解AI趋势，#DeepSeek #资金追踪派。
美国政府下令清除DeepSeek：盯紧AI聊天机器人，停止采购！
美国政府要求所有政府机构从其系统中移除DeepSeek人工智能聊天机器人，并禁止新的采购。这款开源模型曾引发关注，现在却被列为重点监控对象。盯紧资金流向，了解AI趋势，#DeepSeek #资金追踪派。
美国政府要求所有政府机构从其系统中移除DeepSeek人工智能聊天机器人，并禁止新的采购。这款开源模型曾引发关注，现在却被列为重点监控对象。盯紧资金流向，了解AI趋势，#DeepSeek #资金追踪派。
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刷到路透熟悉情况人士：DeepSeek 正敲定约 1000 亿元人民币（约 150 亿美元）融资，腾讯和宁德时代是本轮最大投资方之一——目标从最初约 500 亿一路上调到 800 亿，再到约 1000 亿，预计数日内收官，条款仍可能变。
彭博此前也写过「两度上调目标后接近千亿」这一档。华尔街见闻梳理：宁德时代拟本轮再加约 100 亿（首轮约 50 亿）；若交割完成，半年内累计融资大约能到 1500 亿量级，同时在推进科创板 IPO。
《The Information》9 月还提过，梁文锋对投资人披露年化收入跑到约 10 亿美元量级——主要靠 API。千亿级融资对中国一级市场很硬，但和 OpenAI、Anthropic 累计千亿美金还不是一个量级。
#DeepSeek #AI #融资
刷到路透熟悉情况人士：DeepSeek 正敲定约 1000 亿元人民币（约 150 亿美元）融资，腾讯和宁德时代是本轮最大投资方之一——目标从最初约 500 亿一路上调到 800 亿，再到约 1000 亿，预计数日内收官，条款仍可能变。
彭博此前也写过「两度上调目标后接近千亿」这一档。华尔街见闻梳理：宁德时代拟本轮再加约 100 亿（首轮约 50 亿）；若交割完成，半年内累计融资大约能到 1500 亿量级，同时在推进科创板 IPO。
《The Information》9 月还提过，梁文锋对投资人披露年化收入跑到约 10 亿美元量级——主要靠 API。千亿级融资对中国一级市场很硬，但和 OpenAI、Anthropic 累计千亿美金还不是一个量级。
#DeepSeek #AI #融资
彭博此前也写过「两度上调目标后接近千亿」这一档。华尔街见闻梳理：宁德时代拟本轮再加约 100 亿（首轮约 50 亿）；若交割完成，半年内累计融资大约能到 1500 亿量级，同时在推进科创板 IPO。
《The Information》9 月还提过，梁文锋对投资人披露年化收入跑到约 10 亿美元量级——主要靠 API。千亿级融资对中国一级市场很硬，但和 OpenAI、Anthropic 累计千亿美金还不是一个量级。
#DeepSeek #AI #融资
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Рост
🚨ESTADOS UNIDOS ORDENAM BANIMENTO DO DEEPSEEK EM AGÊNCIAS GOVERNAMENTAIS: O IMPACTO NO MERCADO DE IA! 🛑🇺🇸
O cenário geopolítico e regulatório da Inteligência Artificial acaba de ter um novo capítulo decisivo: o Departamento de Segurança Interna dos EUA (DHS) emitiu uma ordem direta para que todas as agências civis federais desinstalem o DeepSeek e interrompam imediatamente o uso de tecnologias baseadas no modelo chinês!
📌 PONTOS CHAVE DA DECISÃO:
1️⃣ Restrição Federal: A medida exige a remoção completa de sistemas que utilizem a arquitetura do DeepSeek e bloqueia novos contratos ou compras. 2️⃣ Segurança de Dados e Geopolítica: O movimento reflete a crescente tensão e preocupação das autoridades americanas com a soberania de dados e o avanço da IA chinesa em infraestruturas públicas. 3️⃣ Reflexo nos Tokens de IA: Notícias como esta costumam impactar diretamente o sentimento em torno de memecoins e tokens de ecossistemas ligados ao DeepSeek ou à IA na BNB Chain e outras redes, gerando picos de volatilidade.
💡 PERSPECTIVA PROFISSIONAL:
A regulação e as barreiras governamentais são variáveis críticas que todo investidor de tecnologia e cripto precisa monitorar. Enquanto o desenvolvimento técnico da IA avança rápido, as restrições geopolíticas podem mudar o rumo da adoção institucional da noite para o dia (DYOR).
📊 ACOMPANHE O MERCADO COM ATENÇÃO:
👇 Fique de olho na liquidez e no comportamento dos tokens do setor de Inteligência Artificial no WIDGET abaixo antes de tomar qualquer posição!
$DEEP
Você acredita que sanções governamentais podem atrasar o avanço global da Inteligência Artificial ou o desenvolvimento de código aberto superará essas barreiras? Deixe a sua análise nos comentários! 👇💬
#Write2Earn #BinanceSquare #DeepSeek #AI #CryptoNews
🚨ESTADOS UNIDOS ORDENAM BANIMENTO DO DEEPSEEK EM AGÊNCIAS GOVERNAMENTAIS: O IMPACTO NO MERCADO DE IA! 🛑🇺🇸
O cenário geopolítico e regulatório da Inteligência Artificial acaba de ter um novo capítulo decisivo: o Departamento de Segurança Interna dos EUA (DHS) emitiu uma ordem direta para que todas as agências civis federais desinstalem o DeepSeek e interrompam imediatamente o uso de tecnologias baseadas no modelo chinês!
📌 PONTOS CHAVE DA DECISÃO:
1️⃣ Restrição Federal: A medida exige a remoção completa de sistemas que utilizem a arquitetura do DeepSeek e bloqueia novos contratos ou compras. 2️⃣ Segurança de Dados e Geopolítica: O movimento reflete a crescente tensão e preocupação das autoridades americanas com a soberania de dados e o avanço da IA chinesa em infraestruturas públicas. 3️⃣ Reflexo nos Tokens de IA: Notícias como esta costumam impactar diretamente o sentimento em torno de memecoins e tokens de ecossistemas ligados ao DeepSeek ou à IA na BNB Chain e outras redes, gerando picos de volatilidade.
💡 PERSPECTIVA PROFISSIONAL:
A regulação e as barreiras governamentais são variáveis críticas que todo investidor de tecnologia e cripto precisa monitorar. Enquanto o desenvolvimento técnico da IA avança rápido, as restrições geopolíticas podem mudar o rumo da adoção institucional da noite para o dia (DYOR).
📊 ACOMPANHE O MERCADO COM ATENÇÃO:
👇 Fique de olho na liquidez e no comportamento dos tokens do setor de Inteligência Artificial no WIDGET abaixo antes de tomar qualquer posição!
$DEEP
Você acredita que sanções governamentais podem atrasar o avanço global da Inteligência Artificial ou o desenvolvimento de código aberto superará essas barreiras? Deixe a sua análise nos comentários! 👇💬
#Write2Earn #BinanceSquare #DeepSeek #AI #CryptoNews
O cenário geopolítico e regulatório da Inteligência Artificial acaba de ter um novo capítulo decisivo: o Departamento de Segurança Interna dos EUA (DHS) emitiu uma ordem direta para que todas as agências civis federais desinstalem o DeepSeek e interrompam imediatamente o uso de tecnologias baseadas no modelo chinês!
📌 PONTOS CHAVE DA DECISÃO:
1️⃣ Restrição Federal: A medida exige a remoção completa de sistemas que utilizem a arquitetura do DeepSeek e bloqueia novos contratos ou compras. 2️⃣ Segurança de Dados e Geopolítica: O movimento reflete a crescente tensão e preocupação das autoridades americanas com a soberania de dados e o avanço da IA chinesa em infraestruturas públicas. 3️⃣ Reflexo nos Tokens de IA: Notícias como esta costumam impactar diretamente o sentimento em torno de memecoins e tokens de ecossistemas ligados ao DeepSeek ou à IA na BNB Chain e outras redes, gerando picos de volatilidade.
💡 PERSPECTIVA PROFISSIONAL:
A regulação e as barreiras governamentais são variáveis críticas que todo investidor de tecnologia e cripto precisa monitorar. Enquanto o desenvolvimento técnico da IA avança rápido, as restrições geopolíticas podem mudar o rumo da adoção institucional da noite para o dia (DYOR).
📊 ACOMPANHE O MERCADO COM ATENÇÃO:
👇 Fique de olho na liquidez e no comportamento dos tokens do setor de Inteligência Artificial no WIDGET abaixo antes de tomar qualquer posição!
$DEEP
Você acredita que sanções governamentais podem atrasar o avanço global da Inteligência Artificial ou o desenvolvimento de código aberto superará essas barreiras? Deixe a sua análise nos comentários! 👇💬
#Write2Earn #BinanceSquare #DeepSeek #AI #CryptoNews
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🐳 DeepSeek开源自家API推理引擎DeepInfer，华为昇腾和英伟达同台！
📌 DeepInfer就是支撑DeepSeek V4.1 Flash线上服务的推理框架，Apache 2.0协议开源
📌 首发支持英伟达SM100(Blackwell)和华为昇腾950，Hopper等老架构不在列表里
📌 官方称单个集群每天处理155万亿token，谷时定价下每GPU小时收入约38美元
📌 但这次只放出离线推理：KV缓存、PD分离、负载均衡都没开源，想自建完整服务还得自己补
📌 同一赛道：Mistral Large 4(1T参数)开放权重计划10月底发布
AI算力越来越"国产+开源"，算力和推理成本一降，AI代理链上交易会不会更快普及？$BTC
你觉得开源推理会压低大模型API价格吗？评论区聊聊👇
#AI #DeepSeek #开源 #算力
仅供参考，不构成投资建议
🐳 DeepSeek开源自家API推理引擎DeepInfer，华为昇腾和英伟达同台！
📌 DeepInfer就是支撑DeepSeek V4.1 Flash线上服务的推理框架，Apache 2.0协议开源
📌 首发支持英伟达SM100(Blackwell)和华为昇腾950，Hopper等老架构不在列表里
📌 官方称单个集群每天处理155万亿token，谷时定价下每GPU小时收入约38美元
📌 但这次只放出离线推理：KV缓存、PD分离、负载均衡都没开源，想自建完整服务还得自己补
📌 同一赛道：Mistral Large 4(1T参数)开放权重计划10月底发布
AI算力越来越"国产+开源"，算力和推理成本一降，AI代理链上交易会不会更快普及？$BTC
你觉得开源推理会压低大模型API价格吗？评论区聊聊👇
#AI #DeepSeek #开源 #算力
仅供参考，不构成投资建议
📌 DeepInfer就是支撑DeepSeek V4.1 Flash线上服务的推理框架，Apache 2.0协议开源
📌 首发支持英伟达SM100(Blackwell)和华为昇腾950，Hopper等老架构不在列表里
📌 官方称单个集群每天处理155万亿token，谷时定价下每GPU小时收入约38美元
📌 但这次只放出离线推理：KV缓存、PD分离、负载均衡都没开源，想自建完整服务还得自己补
📌 同一赛道：Mistral Large 4(1T参数)开放权重计划10月底发布
AI算力越来越"国产+开源"，算力和推理成本一降，AI代理链上交易会不会更快普及？$BTC
你觉得开源推理会压低大模型API价格吗？评论区聊聊👇
#AI #DeepSeek #开源 #算力
仅供参考，不构成投资建议
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🐋 DeepSeek把自家推理引擎开源了！中国大厂却还在狂买英伟达？
🔹 DeepSeek开源DeepInfer：就是它自己线上服务在用的推理框架，Apache 2.0协议，同时支持英伟达GPU和华为昇腾NPU，登上Hacker News当日榜首（2000+赞）
🔹 另一边，外媒报道字节、阿里、腾讯合计订购超300万张英伟达RTX PRO 5500，总额或超350亿美元（尚未获所有公司证实）
🔹 一边开源降成本，一边砸钱抢算力——AI军备竞赛还在加速
AI算力需求越猛，对 $BTC 矿工和算力赛道是利好还是抢电抢卡？
💬 你觉得开源模型最终会打败闭源巨头吗？评论区聊聊👇
#AI #DeepSeek #英伟达 #算力
仅供参考，不构成投资建议
🐋 DeepSeek把自家推理引擎开源了！中国大厂却还在狂买英伟达？
🔹 DeepSeek开源DeepInfer：就是它自己线上服务在用的推理框架，Apache 2.0协议，同时支持英伟达GPU和华为昇腾NPU，登上Hacker News当日榜首（2000+赞）
🔹 另一边，外媒报道字节、阿里、腾讯合计订购超300万张英伟达RTX PRO 5500，总额或超350亿美元（尚未获所有公司证实）
🔹 一边开源降成本，一边砸钱抢算力——AI军备竞赛还在加速
AI算力需求越猛，对 $BTC 矿工和算力赛道是利好还是抢电抢卡？
💬 你觉得开源模型最终会打败闭源巨头吗？评论区聊聊👇
#AI #DeepSeek #英伟达 #算力
仅供参考，不构成投资建议
🔹 DeepSeek开源DeepInfer：就是它自己线上服务在用的推理框架，Apache 2.0协议，同时支持英伟达GPU和华为昇腾NPU，登上Hacker News当日榜首（2000+赞）
🔹 另一边，外媒报道字节、阿里、腾讯合计订购超300万张英伟达RTX PRO 5500，总额或超350亿美元（尚未获所有公司证实）
🔹 一边开源降成本，一边砸钱抢算力——AI军备竞赛还在加速
AI算力需求越猛，对 $BTC 矿工和算力赛道是利好还是抢电抢卡？
💬 你觉得开源模型最终会打败闭源巨头吗？评论区聊聊👇
#AI #DeepSeek #英伟达 #算力
仅供参考，不构成投资建议
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DeepSeek V4.1 Flash-1017版本更新解析：许愿式编程引领新风向
DeepSeek V4.1 Flash-1017版本更新，聚焦‘许愿式编程’，技术指标优化显著。关键位分析揭示潜在增长点，投资者需关注。#DeepSeek #技术分析派
DeepSeek V4.1 Flash-1017版本更新解析：许愿式编程引领新风向
DeepSeek V4.1 Flash-1017版本更新，聚焦‘许愿式编程’，技术指标优化显著。关键位分析揭示潜在增长点，投资者需关注。#DeepSeek #技术分析派
DeepSeek V4.1 Flash-1017版本更新，聚焦‘许愿式编程’，技术指标优化显著。关键位分析揭示潜在增长点，投资者需关注。#DeepSeek #技术分析派
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一千次搜索，五块钱。一次半分钱，比打印一张纸还便宜。
DeepSeek 十月十七号把自研搜索做成两个接口，Search 找网页，Fetch 抓正文，索引千亿级网页，每天过几亿次请求。价目挂出来，五元一千次。一块钱两百次。就这么个数。
价钱只是表面。我把公告和价目页对着看了一遍，扎眼的是计费口径。失败不收，超时不算，搜出来空结果也不收。只对成功拿到内容的那一次扣钱。
云厂商的价目表翻一遍，按调用计费是默认做法，请求发过去，成不成先记账。这一手等于把风险从买方挪回卖方。
敢这么干，因为它自己就是判官。判官只有一个。搜索结果是它产的，成没成也是它说了算。
再往下想一层，能想到链上。
很多人以为微支付卡在手续费。一分钱转一次，矿工不干，所以做不成。这话只对一半。手续费能降，现在链上转一笔稳定币，成本已经低到几厘，比这个搜索接口贵不了多少。真正降不下来的东西是计数器。
链上没有服务商，只有一堆各自重算的节点，一笔交易算不算数，要看每个节点各自拿同样的规则重跑一遍，算出来一样才认，谁也没资格替别人签字，谁也没法被授权替另一个人记账。
所以「第五万次调用」这种说法在链上不存在。谁说了算？没人有资格记这个数，也没人认别人记的数。
失败的交易照样扣 gas。一个道理。活儿派出去了，节点算过了，结果没成，账还得结。链上做不了成功才收钱，只能先扣后退。
币圈喊微支付喊了快十年。闪电网络、状态通道、预付费余额，绕来绕去都在解决同一件事，在没有人记账的前提下怎么算清次数。到现在为止，真把半分钱一次做成生意的，是一个中心化接口。有点讽刺。就这。
十一月一号零点是个坎。在这之前，通过 Harness、Claude Code、Codex 走服务端调的那部分搜索，一分不收。之后按次算。
公告只写了单价。这几天已经在跑的调用怎么统计，按天结还是按量结，也没个准话。
这事跟币圈的关系，价格只是个由头。当 AI 开始自己搜、自己抓、自己下单，agent 之间要付的钱会碎到几厘一次。那时候谁来记账？记账的那个人就是清算方。链上想接这门生意，光便宜不够，得先把计数器说清楚。
打开你的 API 账单看一眼。那些被扣掉的调用里，有多少其实什么都没返回。
$TAO $USDC $BTC
#DeepSeek #AI搜索 #微支付 #Agent
一千次搜索，五块钱。一次半分钱，比打印一张纸还便宜。
DeepSeek 十月十七号把自研搜索做成两个接口，Search 找网页，Fetch 抓正文，索引千亿级网页，每天过几亿次请求。价目挂出来，五元一千次。一块钱两百次。就这么个数。
价钱只是表面。我把公告和价目页对着看了一遍，扎眼的是计费口径。失败不收，超时不算，搜出来空结果也不收。只对成功拿到内容的那一次扣钱。
云厂商的价目表翻一遍，按调用计费是默认做法，请求发过去，成不成先记账。这一手等于把风险从买方挪回卖方。
敢这么干，因为它自己就是判官。判官只有一个。搜索结果是它产的，成没成也是它说了算。
再往下想一层，能想到链上。
很多人以为微支付卡在手续费。一分钱转一次，矿工不干，所以做不成。这话只对一半。手续费能降，现在链上转一笔稳定币，成本已经低到几厘，比这个搜索接口贵不了多少。真正降不下来的东西是计数器。
链上没有服务商，只有一堆各自重算的节点，一笔交易算不算数，要看每个节点各自拿同样的规则重跑一遍，算出来一样才认，谁也没资格替别人签字，谁也没法被授权替另一个人记账。
所以「第五万次调用」这种说法在链上不存在。谁说了算？没人有资格记这个数，也没人认别人记的数。
失败的交易照样扣 gas。一个道理。活儿派出去了，节点算过了，结果没成，账还得结。链上做不了成功才收钱，只能先扣后退。
币圈喊微支付喊了快十年。闪电网络、状态通道、预付费余额，绕来绕去都在解决同一件事，在没有人记账的前提下怎么算清次数。到现在为止，真把半分钱一次做成生意的，是一个中心化接口。有点讽刺。就这。
十一月一号零点是个坎。在这之前，通过 Harness、Claude Code、Codex 走服务端调的那部分搜索，一分不收。之后按次算。
公告只写了单价。这几天已经在跑的调用怎么统计，按天结还是按量结，也没个准话。
这事跟币圈的关系，价格只是个由头。当 AI 开始自己搜、自己抓、自己下单，agent 之间要付的钱会碎到几厘一次。那时候谁来记账？记账的那个人就是清算方。链上想接这门生意，光便宜不够，得先把计数器说清楚。
打开你的 API 账单看一眼。那些被扣掉的调用里，有多少其实什么都没返回。
$TAO $USDC $BTC
#DeepSeek #AI搜索 #微支付 #Agent
DeepSeek 十月十七号把自研搜索做成两个接口，Search 找网页，Fetch 抓正文，索引千亿级网页，每天过几亿次请求。价目挂出来，五元一千次。一块钱两百次。就这么个数。
价钱只是表面。我把公告和价目页对着看了一遍，扎眼的是计费口径。失败不收，超时不算，搜出来空结果也不收。只对成功拿到内容的那一次扣钱。
云厂商的价目表翻一遍，按调用计费是默认做法，请求发过去，成不成先记账。这一手等于把风险从买方挪回卖方。
敢这么干，因为它自己就是判官。判官只有一个。搜索结果是它产的，成没成也是它说了算。
再往下想一层，能想到链上。
很多人以为微支付卡在手续费。一分钱转一次，矿工不干，所以做不成。这话只对一半。手续费能降，现在链上转一笔稳定币，成本已经低到几厘，比这个搜索接口贵不了多少。真正降不下来的东西是计数器。
链上没有服务商，只有一堆各自重算的节点，一笔交易算不算数，要看每个节点各自拿同样的规则重跑一遍，算出来一样才认，谁也没资格替别人签字，谁也没法被授权替另一个人记账。
所以「第五万次调用」这种说法在链上不存在。谁说了算？没人有资格记这个数，也没人认别人记的数。
失败的交易照样扣 gas。一个道理。活儿派出去了，节点算过了，结果没成，账还得结。链上做不了成功才收钱，只能先扣后退。
币圈喊微支付喊了快十年。闪电网络、状态通道、预付费余额，绕来绕去都在解决同一件事，在没有人记账的前提下怎么算清次数。到现在为止，真把半分钱一次做成生意的，是一个中心化接口。有点讽刺。就这。
十一月一号零点是个坎。在这之前，通过 Harness、Claude Code、Codex 走服务端调的那部分搜索，一分不收。之后按次算。
公告只写了单价。这几天已经在跑的调用怎么统计，按天结还是按量结，也没个准话。
这事跟币圈的关系，价格只是个由头。当 AI 开始自己搜、自己抓、自己下单，agent 之间要付的钱会碎到几厘一次。那时候谁来记账？记账的那个人就是清算方。链上想接这门生意，光便宜不够，得先把计数器说清楚。
打开你的 API 账单看一眼。那些被扣掉的调用里，有多少其实什么都没返回。
$TAO $USDC $BTC
#DeepSeek #AI搜索 #微支付 #Agent
167
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官方说这是个"小更新"，社区把它拆开之后发现：这分明是大修。
10月17日 DeepSeek 发布 V4.1-Flash-1017，模型卡上写着"缩短任务时间、减少输出长度"，API 名和价格不变，权重 MIT 开源。
有开发者把新权重和 9 月版逐层对比，据报道约 40% 路由专家、30% 记忆、50% 视觉塔专家张量被重写；另一位用两台 DGX Spark 跑量化，据报道 TensorFold 引擎文本 56.8、代码 92.2 tokens/秒，几乎是 vLLM 的两倍——架构没变，改动量却是"大版本"级别。
价格战也打进新维度：据工程师实测，DeepSeek 跑一个真实编码任务只花约 4.5 美分，却烧了约 55 万 tokens（Opus 只用 3 万）。token 便宜到可以"浪费"，最后还是更便宜。OpenRouter 数据显示，它过去 7 天处理了约 38.7T tokens，是第二名的 3 倍。
时间点耐人寻味：放出 MIT 权重的前一天（10 月 16 日），商务部和科技部发布出口管制草案征求意见稿：拟新增 40 项技术管制、23 项涉及 AI；算力达 10²⁶ FLOPs、参数超 2 万亿或全球前十的模型，权重、源码、架构纳入管制；API/SaaS 不受影响，已开源不追溯。意见征集到 11 月 15 日，多家媒体确认。
我觉得这是 AI 叙事"开放 vs 管制"开哨的一周：模型权重第一次被写进出口管制清单。短期看，模型越便宜，AI agent 跑量成本越低，链上 AI 叙事的燃料（比如 $TAO $RENDER）只会更足。
悬念还有 V4.1-Pro：据报道 9 月底就有账号在早期接入里看到它的隐藏模型名，预测市场给 10 月底前发布的概率约 16%。观察点：11 月 15 日草案怎么定稿。
以上不构成投资建议，DYOR，交易有风险。
#DeepSeekReleasesUpdatedAIModel
#DeepSeek #AI
官方说这是个"小更新"，社区把它拆开之后发现：这分明是大修。
10月17日 DeepSeek 发布 V4.1-Flash-1017，模型卡上写着"缩短任务时间、减少输出长度"，API 名和价格不变，权重 MIT 开源。
有开发者把新权重和 9 月版逐层对比，据报道约 40% 路由专家、30% 记忆、50% 视觉塔专家张量被重写；另一位用两台 DGX Spark 跑量化，据报道 TensorFold 引擎文本 56.8、代码 92.2 tokens/秒，几乎是 vLLM 的两倍——架构没变，改动量却是"大版本"级别。
价格战也打进新维度：据工程师实测，DeepSeek 跑一个真实编码任务只花约 4.5 美分，却烧了约 55 万 tokens（Opus 只用 3 万）。token 便宜到可以"浪费"，最后还是更便宜。OpenRouter 数据显示，它过去 7 天处理了约 38.7T tokens，是第二名的 3 倍。
时间点耐人寻味：放出 MIT 权重的前一天（10 月 16 日），商务部和科技部发布出口管制草案征求意见稿：拟新增 40 项技术管制、23 项涉及 AI；算力达 10²⁶ FLOPs、参数超 2 万亿或全球前十的模型，权重、源码、架构纳入管制；API/SaaS 不受影响，已开源不追溯。意见征集到 11 月 15 日，多家媒体确认。
我觉得这是 AI 叙事"开放 vs 管制"开哨的一周：模型权重第一次被写进出口管制清单。短期看，模型越便宜，AI agent 跑量成本越低，链上 AI 叙事的燃料（比如 $TAO $RENDER ）只会更足。
悬念还有 V4.1-Pro：据报道 9 月底就有账号在早期接入里看到它的隐藏模型名，预测市场给 10 月底前发布的概率约 16%。观察点：11 月 15 日草案怎么定稿。
以上不构成投资建议，DYOR，交易有风险。
#DeepSeekReleasesUpdatedAIModel
#DeepSeek #AI
10月17日 DeepSeek 发布 V4.1-Flash-1017，模型卡上写着"缩短任务时间、减少输出长度"，API 名和价格不变，权重 MIT 开源。
有开发者把新权重和 9 月版逐层对比，据报道约 40% 路由专家、30% 记忆、50% 视觉塔专家张量被重写；另一位用两台 DGX Spark 跑量化，据报道 TensorFold 引擎文本 56.8、代码 92.2 tokens/秒，几乎是 vLLM 的两倍——架构没变，改动量却是"大版本"级别。
价格战也打进新维度：据工程师实测，DeepSeek 跑一个真实编码任务只花约 4.5 美分，却烧了约 55 万 tokens（Opus 只用 3 万）。token 便宜到可以"浪费"，最后还是更便宜。OpenRouter 数据显示，它过去 7 天处理了约 38.7T tokens，是第二名的 3 倍。
时间点耐人寻味：放出 MIT 权重的前一天（10 月 16 日），商务部和科技部发布出口管制草案征求意见稿：拟新增 40 项技术管制、23 项涉及 AI；算力达 10²⁶ FLOPs、参数超 2 万亿或全球前十的模型，权重、源码、架构纳入管制；API/SaaS 不受影响，已开源不追溯。意见征集到 11 月 15 日，多家媒体确认。
我觉得这是 AI 叙事"开放 vs 管制"开哨的一周：模型权重第一次被写进出口管制清单。短期看，模型越便宜，AI agent 跑量成本越低，链上 AI 叙事的燃料（比如 $TAO $RENDER ）只会更足。
悬念还有 V4.1-Pro：据报道 9 月底就有账号在早期接入里看到它的隐藏模型名，预测市场给 10 月底前发布的概率约 16%。观察点：11 月 15 日草案怎么定稿。
以上不构成投资建议，DYOR，交易有风险。
#DeepSeekReleasesUpdatedAIModel
#DeepSeek #AI
ABO3ZAM:
تحليل ممتاز يا وحش، فعلاً خفض التكاليف بيحرك سيولة ضخمة للقطاع، راقب TAO عند مناطق الدعم الحالية، إذا ثبت فوقها بنشوف انفجار سعري قريب 🎯
5
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Рост
🚨 BREAKING AI NEWS: DeepSeek Releases an Updated AI Model! 🤖🔥
#DeepSeek has introduced DeepSeek-V4.1-Flash-1017, an upgraded AI model announced on October 17, 2026.
⚡ What's new? ✅ Faster task completion
✅ Improved coding and AI agent performance
✅ Shorter, more efficient responses
✅ Better benchmark results
✅ Search & Fetch APIs now available to users
📊 DeepSeek reported a score of 77.0 on the DeepSWE v1.1 benchmark, up from 74.2 in the previous version.
🌐 The updated model is available through DeepSeek's website, mobile app and API.
💡 Why does it matter? The AI race is heating up, with companies competing to deliver more powerful tools at lower costs.
Will DeepSeek challenge the biggest names in AI? 👀
💬 What do you think? Is DeepSeek becoming a serious competitor in the AI industry?
#DeepSeek #TechNews #Innovation
#deepseekreleasesupdatedaimodel
🚨 BREAKING AI NEWS: DeepSeek Releases an Updated AI Model! 🤖🔥
#DeepSeek has introduced DeepSeek-V4.1-Flash-1017, an upgraded AI model announced on October 17, 2026.
⚡ What's new? ✅ Faster task completion
✅ Improved coding and AI agent performance
✅ Shorter, more efficient responses
✅ Better benchmark results
✅ Search & Fetch APIs now available to users
📊 DeepSeek reported a score of 77.0 on the DeepSWE v1.1 benchmark, up from 74.2 in the previous version.
🌐 The updated model is available through DeepSeek's website, mobile app and API.
💡 Why does it matter? The AI race is heating up, with companies competing to deliver more powerful tools at lower costs.
Will DeepSeek challenge the biggest names in AI? 👀
💬 What do you think? Is DeepSeek becoming a serious competitor in the AI industry?
#DeepSeek #TechNews #Innovation
#deepseekreleasesupdatedaimodel
#DeepSeek has introduced DeepSeek-V4.1-Flash-1017, an upgraded AI model announced on October 17, 2026.
⚡ What's new? ✅ Faster task completion
✅ Improved coding and AI agent performance
✅ Shorter, more efficient responses
✅ Better benchmark results
✅ Search & Fetch APIs now available to users
📊 DeepSeek reported a score of 77.0 on the DeepSWE v1.1 benchmark, up from 74.2 in the previous version.
🌐 The updated model is available through DeepSeek's website, mobile app and API.
💡 Why does it matter? The AI race is heating up, with companies competing to deliver more powerful tools at lower costs.
Will DeepSeek challenge the biggest names in AI? 👀
💬 What do you think? Is DeepSeek becoming a serious competitor in the AI industry?
#DeepSeek #TechNews #Innovation
#deepseekreleasesupdatedaimodel
Taybou:
peut etre
1
4
690
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🤖 DeepSeek Upgrades Again: Is the AI Sector Primed for a Breakout?
DeepSeek has officially rolled out its latest model update (V4.1-Flash), delivering high-speed reasoning and complex coding at a fraction of traditional computing costs.
Here is why this matters for tech and Web3 AI sectors:
💡 1. Efficiency Over Hype High-throughput, lower-cost inference models force established AI giants to drop prices, accelerating global developer adoption.
⚡ 2. Web3 AI & Decentralized Compute Efficient models drive real-world demand for decentralized GPU networks ($RENDER, $AKT) and decentralized intelligence protocols ($TAO, $NEAR,$ASTER).
🎯 3. The Reality Check Headlines create initial spikes, but real value capture comes from developer usage, integration, and actual fee generation—not just hype.
💬 What’s your take? Will open-weights efficiency disrupt closed AI giants, or will big tech hold the throne? Drop your thoughts below! 👇
#DeepSeek #AI #CryptoNews #TAO #NEAR
🤖 DeepSeek Upgrades Again: Is the AI Sector Primed for a Breakout?
DeepSeek has officially rolled out its latest model update (V4.1-Flash), delivering high-speed reasoning and complex coding at a fraction of traditional computing costs.
Here is why this matters for tech and Web3 AI sectors:
💡 1. Efficiency Over Hype High-throughput, lower-cost inference models force established AI giants to drop prices, accelerating global developer adoption.
⚡ 2. Web3 AI & Decentralized Compute Efficient models drive real-world demand for decentralized GPU networks ($RENDER, $AKT) and decentralized intelligence protocols ($TAO, $NEAR,$ASTER).
🎯 3. The Reality Check Headlines create initial spikes, but real value capture comes from developer usage, integration, and actual fee generation—not just hype.
💬 What’s your take? Will open-weights efficiency disrupt closed AI giants, or will big tech hold the throne? Drop your thoughts below! 👇
#DeepSeek #AI #CryptoNews #TAO #NEAR
DeepSeek has officially rolled out its latest model update (V4.1-Flash), delivering high-speed reasoning and complex coding at a fraction of traditional computing costs.
Here is why this matters for tech and Web3 AI sectors:
💡 1. Efficiency Over Hype High-throughput, lower-cost inference models force established AI giants to drop prices, accelerating global developer adoption.
⚡ 2. Web3 AI & Decentralized Compute Efficient models drive real-world demand for decentralized GPU networks ($RENDER, $AKT) and decentralized intelligence protocols ($TAO, $NEAR,$ASTER).
🎯 3. The Reality Check Headlines create initial spikes, but real value capture comes from developer usage, integration, and actual fee generation—not just hype.
💬 What’s your take? Will open-weights efficiency disrupt closed AI giants, or will big tech hold the throne? Drop your thoughts below! 👇
#DeepSeek #AI #CryptoNews #TAO #NEAR
114
🚀 DeepSeek Releases V4.1-Flash-1017: Better AI Performance at Low Cost
🔍 1. What’s New?
$FET — DeepSeek released V4.1-Flash-1017 on October 17, 2026. The update improves reported coding and agent-task benchmark scores while aiming to reduce task completion time and output length.
📊 2. Key Performance Numbers
According to DeepSeek’s published results:
DeepSWE v1.1: 77.0, up from 74.2.
Terminal-Bench 4.0: 42.3, up from 31.2.
API pricing: Off-peak input at $0.15 and output at $0.60 per million tokens.
License: MIT, allowing broad use subject to its terms.
The API continues to use the deepseek-flash model alias. Benchmark scores are self-reported and can vary with testing frameworks.
🤖 3. Why It Matters for Crypto
$RENDER — More capable and affordable AI models could support experimentation with autonomous agents, decentralized computing, and AI-powered blockchain applications.
However, a model release does not automatically increase demand for decentralized infrastructure or guarantee gains for AI-related crypto tokens.
🎯 4. What Should Investors Watch?
$NEAR — Focus on real adoption, developer activity, network usage, and actual demand for decentralized compute. AI-related headlines can influence market sentiment, but price movements are uncertain.
Prime Crypto Lab — No Hype, Just Research.
DYOR | Educational Content | Not Financial Advice
#DeepSeek #Binance #DeepSeekReleasesUpdatedAIModel #BinanceSquareTalks
🚀 DeepSeek Releases V4.1-Flash-1017: Better AI Performance at Low Cost
🔍 1. What’s New?
$FET — DeepSeek released V4.1-Flash-1017 on October 17, 2026. The update improves reported coding and agent-task benchmark scores while aiming to reduce task completion time and output length.
📊 2. Key Performance Numbers
According to DeepSeek’s published results:
DeepSWE v1.1: 77.0, up from 74.2.
Terminal-Bench 4.0: 42.3, up from 31.2.
API pricing: Off-peak input at $0.15 and output at $0.60 per million tokens.
License: MIT, allowing broad use subject to its terms.
The API continues to use the deepseek-flash model alias. Benchmark scores are self-reported and can vary with testing frameworks.
🤖 3. Why It Matters for Crypto
$RENDER — More capable and affordable AI models could support experimentation with autonomous agents, decentralized computing, and AI-powered blockchain applications.
However, a model release does not automatically increase demand for decentralized infrastructure or guarantee gains for AI-related crypto tokens.
🎯 4. What Should Investors Watch?
$NEAR — Focus on real adoption, developer activity, network usage, and actual demand for decentralized compute. AI-related headlines can influence market sentiment, but price movements are uncertain.
Prime Crypto Lab — No Hype, Just Research.
DYOR | Educational Content | Not Financial Advice
#DeepSeek #Binance #DeepSeekReleasesUpdatedAIModel #BinanceSquareTalks
🔍 1. What’s New?
$FET — DeepSeek released V4.1-Flash-1017 on October 17, 2026. The update improves reported coding and agent-task benchmark scores while aiming to reduce task completion time and output length.
📊 2. Key Performance Numbers
According to DeepSeek’s published results:
DeepSWE v1.1: 77.0, up from 74.2.
Terminal-Bench 4.0: 42.3, up from 31.2.
API pricing: Off-peak input at $0.15 and output at $0.60 per million tokens.
License: MIT, allowing broad use subject to its terms.
The API continues to use the deepseek-flash model alias. Benchmark scores are self-reported and can vary with testing frameworks.
🤖 3. Why It Matters for Crypto
$RENDER — More capable and affordable AI models could support experimentation with autonomous agents, decentralized computing, and AI-powered blockchain applications.
However, a model release does not automatically increase demand for decentralized infrastructure or guarantee gains for AI-related crypto tokens.
🎯 4. What Should Investors Watch?
$NEAR — Focus on real adoption, developer activity, network usage, and actual demand for decentralized compute. AI-related headlines can influence market sentiment, but price movements are uncertain.
Prime Crypto Lab — No Hype, Just Research.
DYOR | Educational Content | Not Financial Advice
#DeepSeek #Binance #DeepSeekReleasesUpdatedAIModel #BinanceSquareTalks
362
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一把尺子，十八个刻度，全是别人家的。
10 月 18 日上午，有人把 DeepSeek 刚上线的新模型送进一个叫 ModelTrace 的工具，跑出一行结果，跟 GPT-6 Astra 的相似度 84.66。半天之内，这个数字冲到知乎热榜第七，同一条帖子在 Hacker News 首页拿了 744 分。
评论区下的第一个结论是四个字，实锤蒸馏。
往前倒两天，这家公司刚为一次五小时的宕机赔过钱，按七日消耗全额返赠金。口碑攒回来一点。就两天。结果新模型上线不到一天，账又被翻了一遍。
我去翻了那个工具的说明书。参考库里一共十八个候选模型，全部来自 GPT 和 Claude 两族，DeepSeek 任何版本都不在里面。说明书自己还写着一句更要命的话，没收录的模型照样会被打上已有候选的标签，结果压根不能用来判断身份。
十八个格子，没有一格写着你的名字。你走进去，它必须给你指一个最近的亲戚。就这个逻辑。
有人真去试了。拿纯 Python 生成随机数，喂进去，判成与 GPT-5.5 最相似。随机数也有血统？
有人凭手感说话，说新模型写代码的文风跟 Astra 一个味。手感不算数。
再看样本是怎么采的。GPT 那批取自 Codex 订阅，Claude 那批取自第三方服务。拿两套采集条件不同的样本当标尺，量出来的那个距离只能说明在这份名单里谁排得更近，至于名单外还有多远，它一开始就没打算回答。
反过来的证据也不是没有。新模型实测输出 244 tok/s，个别请求接近 300。这个速度，此前哪一版 Astra 的托管服务跑出来过？权重还挂在 Hugging Face 上，MIT 许可，谁都能下下来自己跑一遍。
用过 API 中转站的人对这场景应该不陌生。你付的是 A 的钱，回来的是 B 的货，账单上看不出任何异常。托管方、场外报价、量化接口，同一个毛病。凡是账本之外的地方，验货都得靠对方配合，他说是什么你就得信什么，查证的路子压根不在你手上，出了事再回头追问，能等到的多半只有一句我们核实过了。认账的不多。
链上能自证的东西其实很土。一个签名，一个区块高度。谁签的，什么时候签的，改不了。可这套东西也有死角，真去逐个核的人太少，多数人看的还是别人核完的结论。自己动手，成本摆在那儿。麻烦就在这。
我琢磨下来，这次争议里最该记住的其实是那把尺子的刻度表。工具能测出相似，测不出血缘。两码事。把相似当成血缘，这口锅在使用的人，不在工具身上。
DeepSeek 到今天傍晚还没回应，训练语料也从来没逐项公开过。这两件事凑在一起，因果到底怎么走的，没人说得清。
分数是真的。跑分涨了，单任务价格从三块三砍到一块三，这两条官方有图有表。血统是另一回事。测不出来。得等第三方复测那套基础设施长出来，眼下还没有。
$TAO $FET $BTC
#DeepSeek #AI模型 #开源 #加密
一把尺子，十八个刻度，全是别人家的。
10 月 18 日上午，有人把 DeepSeek 刚上线的新模型送进一个叫 ModelTrace 的工具，跑出一行结果，跟 GPT-6 Astra 的相似度 84.66。半天之内，这个数字冲到知乎热榜第七，同一条帖子在 Hacker News 首页拿了 744 分。
评论区下的第一个结论是四个字，实锤蒸馏。
往前倒两天，这家公司刚为一次五小时的宕机赔过钱，按七日消耗全额返赠金。口碑攒回来一点。就两天。结果新模型上线不到一天，账又被翻了一遍。
我去翻了那个工具的说明书。参考库里一共十八个候选模型，全部来自 GPT 和 Claude 两族，DeepSeek 任何版本都不在里面。说明书自己还写着一句更要命的话，没收录的模型照样会被打上已有候选的标签，结果压根不能用来判断身份。
十八个格子，没有一格写着你的名字。你走进去，它必须给你指一个最近的亲戚。就这个逻辑。
有人真去试了。拿纯 Python 生成随机数，喂进去，判成与 GPT-5.5 最相似。随机数也有血统？
有人凭手感说话，说新模型写代码的文风跟 Astra 一个味。手感不算数。
再看样本是怎么采的。GPT 那批取自 Codex 订阅，Claude 那批取自第三方服务。拿两套采集条件不同的样本当标尺，量出来的那个距离只能说明在这份名单里谁排得更近，至于名单外还有多远，它一开始就没打算回答。
反过来的证据也不是没有。新模型实测输出 244 tok/s，个别请求接近 300。这个速度，此前哪一版 Astra 的托管服务跑出来过？权重还挂在 Hugging Face 上，MIT 许可，谁都能下下来自己跑一遍。
用过 API 中转站的人对这场景应该不陌生。你付的是 A 的钱，回来的是 B 的货，账单上看不出任何异常。托管方、场外报价、量化接口，同一个毛病。凡是账本之外的地方，验货都得靠对方配合，他说是什么你就得信什么，查证的路子压根不在你手上，出了事再回头追问，能等到的多半只有一句我们核实过了。认账的不多。
链上能自证的东西其实很土。一个签名，一个区块高度。谁签的，什么时候签的，改不了。可这套东西也有死角，真去逐个核的人太少，多数人看的还是别人核完的结论。自己动手，成本摆在那儿。麻烦就在这。
我琢磨下来，这次争议里最该记住的其实是那把尺子的刻度表。工具能测出相似，测不出血缘。两码事。把相似当成血缘，这口锅在使用的人，不在工具身上。
DeepSeek 到今天傍晚还没回应，训练语料也从来没逐项公开过。这两件事凑在一起，因果到底怎么走的，没人说得清。
分数是真的。跑分涨了，单任务价格从三块三砍到一块三，这两条官方有图有表。血统是另一回事。测不出来。得等第三方复测那套基础设施长出来，眼下还没有。
$TAO $FET $BTC
#DeepSeek #AI模型 #开源 #加密
10 月 18 日上午，有人把 DeepSeek 刚上线的新模型送进一个叫 ModelTrace 的工具，跑出一行结果，跟 GPT-6 Astra 的相似度 84.66。半天之内，这个数字冲到知乎热榜第七，同一条帖子在 Hacker News 首页拿了 744 分。
评论区下的第一个结论是四个字，实锤蒸馏。
往前倒两天，这家公司刚为一次五小时的宕机赔过钱，按七日消耗全额返赠金。口碑攒回来一点。就两天。结果新模型上线不到一天，账又被翻了一遍。
我去翻了那个工具的说明书。参考库里一共十八个候选模型，全部来自 GPT 和 Claude 两族，DeepSeek 任何版本都不在里面。说明书自己还写着一句更要命的话，没收录的模型照样会被打上已有候选的标签，结果压根不能用来判断身份。
十八个格子，没有一格写着你的名字。你走进去，它必须给你指一个最近的亲戚。就这个逻辑。
有人真去试了。拿纯 Python 生成随机数，喂进去，判成与 GPT-5.5 最相似。随机数也有血统？
有人凭手感说话，说新模型写代码的文风跟 Astra 一个味。手感不算数。
再看样本是怎么采的。GPT 那批取自 Codex 订阅，Claude 那批取自第三方服务。拿两套采集条件不同的样本当标尺，量出来的那个距离只能说明在这份名单里谁排得更近，至于名单外还有多远，它一开始就没打算回答。
反过来的证据也不是没有。新模型实测输出 244 tok/s，个别请求接近 300。这个速度，此前哪一版 Astra 的托管服务跑出来过？权重还挂在 Hugging Face 上，MIT 许可，谁都能下下来自己跑一遍。
用过 API 中转站的人对这场景应该不陌生。你付的是 A 的钱，回来的是 B 的货，账单上看不出任何异常。托管方、场外报价、量化接口，同一个毛病。凡是账本之外的地方，验货都得靠对方配合，他说是什么你就得信什么，查证的路子压根不在你手上，出了事再回头追问，能等到的多半只有一句我们核实过了。认账的不多。
链上能自证的东西其实很土。一个签名，一个区块高度。谁签的，什么时候签的，改不了。可这套东西也有死角，真去逐个核的人太少，多数人看的还是别人核完的结论。自己动手，成本摆在那儿。麻烦就在这。
我琢磨下来，这次争议里最该记住的其实是那把尺子的刻度表。工具能测出相似，测不出血缘。两码事。把相似当成血缘，这口锅在使用的人，不在工具身上。
DeepSeek 到今天傍晚还没回应，训练语料也从来没逐项公开过。这两件事凑在一起，因果到底怎么走的，没人说得清。
分数是真的。跑分涨了，单任务价格从三块三砍到一块三，这两条官方有图有表。血统是另一回事。测不出来。得等第三方复测那套基础设施长出来，眼下还没有。
$TAO $FET $BTC
#DeepSeek #AI模型 #开源 #加密
226
·
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#GrayscaleAndRepublicLaunchThreeCryptoFunds
🚀 DeepSeek Upgrades AI Performance Without Raising Prices!
DeepSeek-V4.1-Flash-1017, announced on October 17, improves coding, reasoning, and AI-agent performance. Its DeepSWE v1.1 score rose to 77.0 from 74.2, while API pricing remains unchanged.
📊 My Take: Better efficiency, faster execution, and stable pricing could increase competition among AI providers. However, real-world reliability matters more than benchmarks alone.
💬 Will efficient AI models challenge expensive AI services?
Follow for more AI & tech insights!
#DeepSeek #AI #ArtificialIntelligence #TechNews
#GrayscaleAndRepublicLaunchThreeCryptoFunds
🚀 DeepSeek Upgrades AI Performance Without Raising Prices!
DeepSeek-V4.1-Flash-1017, announced on October 17, improves coding, reasoning, and AI-agent performance. Its DeepSWE v1.1 score rose to 77.0 from 74.2, while API pricing remains unchanged.
📊 My Take: Better efficiency, faster execution, and stable pricing could increase competition among AI providers. However, real-world reliability matters more than benchmarks alone.
💬 Will efficient AI models challenge expensive AI services?
Follow for more AI & tech insights!
#DeepSeek #AI #ArtificialIntelligence #TechNews
🚀 DeepSeek Upgrades AI Performance Without Raising Prices!
DeepSeek-V4.1-Flash-1017, announced on October 17, improves coding, reasoning, and AI-agent performance. Its DeepSWE v1.1 score rose to 77.0 from 74.2, while API pricing remains unchanged.
📊 My Take: Better efficiency, faster execution, and stable pricing could increase competition among AI providers. However, real-world reliability matters more than benchmarks alone.
💬 Will efficient AI models challenge expensive AI services?
Follow for more AI & tech insights!
#DeepSeek #AI #ArtificialIntelligence #TechNews
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Проверено
Статья
¡DeepSeek Lanza su Nuevo Modelo de IA Actualizado! ¿Revolución de Código Abierto e Impacto en Token#deepseekreleasesupdatedaimodel
IA en redes blockchain: Se destaca la inversión de $30 millones de dólares realizada por la Fundación Sui para desarrollar su red de datos descentralizada, orientada a acelerar el procesamiento, optimizar el almacenamiento on-chain y reducir los costos de gas en dApps de Inteligencia Artificial y juegos Web3
¿Qué Novedades Trae el Nuevo Modelo Actualizado de DeepSeek? ⚡
La actualización del modelo de #DeepSeek introduce avances arquitectónicos significativos:
Eficiencia de Inferencia Extrema: Capacidad de procesamiento optimizada que reduce drásticamente el consumo de memoria GPU y los costos de infraestructura en servidores.Razonamiento Lógico y Programación Avanzada: Mejoras sustanciales en la generación de código limpio, auditoría de contratos inteligentes (smart contracts) y resolución de problemas complejos sin depender de hardware privativo masivo.Consolidación del Código Abierto (Open Source): Al ofrecer pesos abiertos y arquitecturas accesibles, DeepSeek democratiza el entrenamiento e integración de modelos para desarrolladores globales y protocolos Web3.
¡DeepSeek Lanza su Nuevo Modelo de IA Actualizado! ¿Revolución de Código Abierto e Impacto en Token
#deepseekreleasesupdatedaimodel
IA en redes blockchain: Se destaca la inversión de $30 millones de dólares realizada por la Fundación Sui para desarrollar su red de datos descentralizada, orientada a acelerar el procesamiento, optimizar el almacenamiento on-chain y reducir los costos de gas en dApps de Inteligencia Artificial y juegos Web3
¿Qué Novedades Trae el Nuevo Modelo Actualizado de DeepSeek? ⚡
La actualización del modelo de #DeepSeek introduce avances arquitectónicos significativos:
Eficiencia de Inferencia Extrema: Capacidad de procesamiento optimizada que reduce drásticamente el consumo de memoria GPU y los costos de infraestructura en servidores.Razonamiento Lógico y Programación Avanzada: Mejoras sustanciales en la generación de código limpio, auditoría de contratos inteligentes (smart contracts) y resolución de problemas complejos sin depender de hardware privativo masivo.Consolidación del Código Abierto (Open Source): Al ofrecer pesos abiertos y arquitecturas accesibles, DeepSeek democratiza el entrenamiento e integración de modelos para desarrolladores globales y protocolos Web3.
IA en redes blockchain: Se destaca la inversión de $30 millones de dólares realizada por la Fundación Sui para desarrollar su red de datos descentralizada, orientada a acelerar el procesamiento, optimizar el almacenamiento on-chain y reducir los costos de gas en dApps de Inteligencia Artificial y juegos Web3
¿Qué Novedades Trae el Nuevo Modelo Actualizado de DeepSeek? ⚡
La actualización del modelo de #DeepSeek introduce avances arquitectónicos significativos:
Eficiencia de Inferencia Extrema: Capacidad de procesamiento optimizada que reduce drásticamente el consumo de memoria GPU y los costos de infraestructura en servidores.Razonamiento Lógico y Programación Avanzada: Mejoras sustanciales en la generación de código limpio, auditoría de contratos inteligentes (smart contracts) y resolución de problemas complejos sin depender de hardware privativo masivo.Consolidación del Código Abierto (Open Source): Al ofrecer pesos abiertos y arquitecturas accesibles, DeepSeek democratiza el entrenamiento e integración de modelos para desarrolladores globales y protocolos Web3.
ABO3ZAM:
طرح ممتاز يا بطل، SUI مشروع قوي لكن لا تنسى تأمين أرباحك عند كل مقاومة وإدارة محفظتك بذكاء، السوق لا يعترف بالعواطف. 🤝
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China Released AI Developer Released DeepSeek V4.1-Flash-1017#DeepSeekReleasesUpdatedAIModel
#BinanceSquareTalks #DeepSeek
$BTC $USDT $BTTC
What Traders Should Know About the Latest AI Efficiency Update
The AI sector continues to shift its focus from raw model size to practical efficiency. On October 17, 2026, Chinese AI developer DeepSeek released an update to its Flash series: DeepSeek V4.1-Flash-1017. While the version name suggests a minor revision, the changes carry implications for developers, quantitative analysts, and anyone who relies on AI tools for data processing and automation.
For the crypto community, this release is less about hype and more about the underlying economics of AI compute. Here is a factual breakdown of what was announced and why it matters.
What Was Released?
DeepSeek updated its V4.1 Flash model to the 1017 snapshot (October 17, 2026). The new version is live across the company’s web interface, mobile app, and API. According to DeepSeek’s official documentation, the update delivers a Pareto improvement: better benchmark performance with reduced output length and faster run times. In practical terms, this means lower cost per API call for developers and firms that use the model for tasks such as code generation, data analysis, and agentic automation.
Architecture and Technical Highlights
The V4.1-Flash-1017 is a sparse mixture-of-experts (MoE) model built on DeepSeek’s proprietary Causal Encoder-Decoder architecture. It activates approximately 8 billion parameters on input and 16 billion on output from a 552-billion-parameter backbone. This asymmetric design keeps per-token compute low while maintaining capability.
Key technical features include:
· Native image understanding (multimodal input support)
· Compressed KV caching that reduces cache memory to roughly one-quarter of the previous generation
· Tuning for agentic workloads, meaning the model is optimized for multi-step autonomous tasks
The company also highlighted a capability called “wish-style programming,” which allows users to generate a runnable project from a short prompt with minimal reference material. This is attributed to reinforcement learning based on self-feedback during training.
Benchmark Improvements
DeepSeek published specific benchmark gains to support its efficiency claims. On Terminal-Bench 4.0, a metric for agentic coding, the score increased from 31.2 to 42.3. Other benchmarks showed double-digit percentage improvements:
· ProgramBench: 20.3 → 29.1
· DeepSWE v1.1: 74.2 → 77.0
· Automation-Bench: 54.8 → 60.5
For the crypto industry, improved coding and automation benchmarks are relevant to smart contract auditing, trading algorithm development, and on-chain data analysis. Better performance in these areas can reduce development time and operational overhead.
Pricing and Open-Source Availability
Despite the performance upgrades, DeepSeek has kept API pricing unchanged. The model remains accessible via the deepseek-flash endpoint at $0.10 per million input tokens** and **$0.50 per million output tokens.
The model weights are available on Hugging Face and ModelScope under the MIT License. This open-source approach allows independent developers and decentralized AI projects to fine-tune the model without restrictive licensing fees, which aligns with the transparency and permissionless innovation valued in the crypto ecosystem.
Why This Matters for the Market
From an editorial perspective, this release reinforces two trends shaping the tech-crypto intersection:
1. The efficiency race: Competition is shifting from parameter count to cost-per-task. DeepSeek’s ability to improve benchmarks while reducing output length challenges the cost structures of larger AI providers.
2. Agentic readiness: The specific tuning for agentic tasks suggests that the next wave of AI adoption will involve autonomous agents. In crypto, this could lead to more sophisticated
The Bencmark Increased Not The Pricing.
China Released AI Developer Released DeepSeek V4.1-Flash-1017
#DeepSeekReleasesUpdatedAIModel
#BinanceSquareTalks #DeepSeek
$BTC $USDT $BTTC
What Traders Should Know About the Latest AI Efficiency Update
The AI sector continues to shift its focus from raw model size to practical efficiency. On October 17, 2026, Chinese AI developer DeepSeek released an update to its Flash series: DeepSeek V4.1-Flash-1017. While the version name suggests a minor revision, the changes carry implications for developers, quantitative analysts, and anyone who relies on AI tools for data processing and automation.
For the crypto community, this release is less about hype and more about the underlying economics of AI compute. Here is a factual breakdown of what was announced and why it matters.
What Was Released?
DeepSeek updated its V4.1 Flash model to the 1017 snapshot (October 17, 2026). The new version is live across the company’s web interface, mobile app, and API. According to DeepSeek’s official documentation, the update delivers a Pareto improvement: better benchmark performance with reduced output length and faster run times. In practical terms, this means lower cost per API call for developers and firms that use the model for tasks such as code generation, data analysis, and agentic automation.
Architecture and Technical Highlights
The V4.1-Flash-1017 is a sparse mixture-of-experts (MoE) model built on DeepSeek’s proprietary Causal Encoder-Decoder architecture. It activates approximately 8 billion parameters on input and 16 billion on output from a 552-billion-parameter backbone. This asymmetric design keeps per-token compute low while maintaining capability.
Key technical features include:
· Native image understanding (multimodal input support)
· Compressed KV caching that reduces cache memory to roughly one-quarter of the previous generation
· Tuning for agentic workloads, meaning the model is optimized for multi-step autonomous tasks
The company also highlighted a capability called “wish-style programming,” which allows users to generate a runnable project from a short prompt with minimal reference material. This is attributed to reinforcement learning based on self-feedback during training.
Benchmark Improvements
DeepSeek published specific benchmark gains to support its efficiency claims. On Terminal-Bench 4.0, a metric for agentic coding, the score increased from 31.2 to 42.3. Other benchmarks showed double-digit percentage improvements:
· ProgramBench: 20.3 → 29.1
· DeepSWE v1.1: 74.2 → 77.0
· Automation-Bench: 54.8 → 60.5
For the crypto industry, improved coding and automation benchmarks are relevant to smart contract auditing, trading algorithm development, and on-chain data analysis. Better performance in these areas can reduce development time and operational overhead.
Pricing and Open-Source Availability
Despite the performance upgrades, DeepSeek has kept API pricing unchanged. The model remains accessible via the deepseek-flash endpoint at $0.10 per million input tokens** and **$0.50 per million output tokens.
The model weights are available on Hugging Face and ModelScope under the MIT License. This open-source approach allows independent developers and decentralized AI projects to fine-tune the model without restrictive licensing fees, which aligns with the transparency and permissionless innovation valued in the crypto ecosystem.
Why This Matters for the Market
From an editorial perspective, this release reinforces two trends shaping the tech-crypto intersection:
1. The efficiency race: Competition is shifting from parameter count to cost-per-task. DeepSeek’s ability to improve benchmarks while reducing output length challenges the cost structures of larger AI providers.
2. Agentic readiness: The specific tuning for agentic tasks suggests that the next wave of AI adoption will involve autonomous agents. In crypto, this could lead to more sophisticated
The Bencmark Increased Not The Pricing.
#BinanceSquareTalks #DeepSeek
$BTC $USDT $BTTC
What Traders Should Know About the Latest AI Efficiency Update
The AI sector continues to shift its focus from raw model size to practical efficiency. On October 17, 2026, Chinese AI developer DeepSeek released an update to its Flash series: DeepSeek V4.1-Flash-1017. While the version name suggests a minor revision, the changes carry implications for developers, quantitative analysts, and anyone who relies on AI tools for data processing and automation.
For the crypto community, this release is less about hype and more about the underlying economics of AI compute. Here is a factual breakdown of what was announced and why it matters.
What Was Released?
DeepSeek updated its V4.1 Flash model to the 1017 snapshot (October 17, 2026). The new version is live across the company’s web interface, mobile app, and API. According to DeepSeek’s official documentation, the update delivers a Pareto improvement: better benchmark performance with reduced output length and faster run times. In practical terms, this means lower cost per API call for developers and firms that use the model for tasks such as code generation, data analysis, and agentic automation.
Architecture and Technical Highlights
The V4.1-Flash-1017 is a sparse mixture-of-experts (MoE) model built on DeepSeek’s proprietary Causal Encoder-Decoder architecture. It activates approximately 8 billion parameters on input and 16 billion on output from a 552-billion-parameter backbone. This asymmetric design keeps per-token compute low while maintaining capability.
Key technical features include:
· Native image understanding (multimodal input support)
· Compressed KV caching that reduces cache memory to roughly one-quarter of the previous generation
· Tuning for agentic workloads, meaning the model is optimized for multi-step autonomous tasks
The company also highlighted a capability called “wish-style programming,” which allows users to generate a runnable project from a short prompt with minimal reference material. This is attributed to reinforcement learning based on self-feedback during training.
Benchmark Improvements
DeepSeek published specific benchmark gains to support its efficiency claims. On Terminal-Bench 4.0, a metric for agentic coding, the score increased from 31.2 to 42.3. Other benchmarks showed double-digit percentage improvements:
· ProgramBench: 20.3 → 29.1
· DeepSWE v1.1: 74.2 → 77.0
· Automation-Bench: 54.8 → 60.5
For the crypto industry, improved coding and automation benchmarks are relevant to smart contract auditing, trading algorithm development, and on-chain data analysis. Better performance in these areas can reduce development time and operational overhead.
Pricing and Open-Source Availability
Despite the performance upgrades, DeepSeek has kept API pricing unchanged. The model remains accessible via the deepseek-flash endpoint at $0.10 per million input tokens** and **$0.50 per million output tokens.
The model weights are available on Hugging Face and ModelScope under the MIT License. This open-source approach allows independent developers and decentralized AI projects to fine-tune the model without restrictive licensing fees, which aligns with the transparency and permissionless innovation valued in the crypto ecosystem.
Why This Matters for the Market
From an editorial perspective, this release reinforces two trends shaping the tech-crypto intersection:
1. The efficiency race: Competition is shifting from parameter count to cost-per-task. DeepSeek’s ability to improve benchmarks while reducing output length challenges the cost structures of larger AI providers.
2. Agentic readiness: The specific tuning for agentic tasks suggests that the next wave of AI adoption will involve autonomous agents. In crypto, this could lead to more sophisticated
The Bencmark Increased Not The Pricing.
1
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36
·
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#DeepSeekReleasesUpdatedAIModel
🚀 DeepSeek just shipped V4.1-Flash-1017, an updated checkpoint live since Oct 17 under the same deepseek-flash API alias, with pricing unchanged.
📊 Key numbers (DeepSeek-reported):
• DeepSWE v1.1: 77.0 (up from 74.2)
• Terminal-Bench 4.0: 42.3 (up from 31.2)
• Off-peak API: $0.15 / $0.60 per 1M input / output tokens
• Open weights under the MIT license
💡 Why it matters for crypto: cheaper, stronger AI inference strengthens the case for on-chain AI agents and decentralized compute (DePIN). AI-narrative tokens like $FET, $RENDER and $NEAR often react to headlines like this, but those moves are usually sentiment-driven and short-lived.
⚠️ Watch real usage and on-chain metrics, not just the news. Manage your risk.
Not financial advice.
$FET
#DeepSeek #AI #crypto
#DeepSeekReleasesUpdatedAIModel
🚀 DeepSeek just shipped V4.1-Flash-1017, an updated checkpoint live since Oct 17 under the same deepseek-flash API alias, with pricing unchanged.
📊 Key numbers (DeepSeek-reported):
• DeepSWE v1.1: 77.0 (up from 74.2)
• Terminal-Bench 4.0: 42.3 (up from 31.2)
• Off-peak API: $0.15 / $0.60 per 1M input / output tokens
• Open weights under the MIT license
💡 Why it matters for crypto: cheaper, stronger AI inference strengthens the case for on-chain AI agents and decentralized compute (DePIN). AI-narrative tokens like $FET , $RENDER and $NEAR often react to headlines like this, but those moves are usually sentiment-driven and short-lived.
⚠️ Watch real usage and on-chain metrics, not just the news. Manage your risk.
Not financial advice.
$FET
#DeepSeek #AI #crypto
🚀 DeepSeek just shipped V4.1-Flash-1017, an updated checkpoint live since Oct 17 under the same deepseek-flash API alias, with pricing unchanged.
📊 Key numbers (DeepSeek-reported):
• DeepSWE v1.1: 77.0 (up from 74.2)
• Terminal-Bench 4.0: 42.3 (up from 31.2)
• Off-peak API: $0.15 / $0.60 per 1M input / output tokens
• Open weights under the MIT license
💡 Why it matters for crypto: cheaper, stronger AI inference strengthens the case for on-chain AI agents and decentralized compute (DePIN). AI-narrative tokens like $FET , $RENDER and $NEAR often react to headlines like this, but those moves are usually sentiment-driven and short-lived.
⚠️ Watch real usage and on-chain metrics, not just the news. Manage your risk.
Not financial advice.
$FET
#DeepSeek #AI #crypto
1
218
·
--
#deepseekreleasesupdatedaimodel 🚀 DeepSeeks New AI Model Raises the Competition Bar!
🌕 DeepSeeks V4.1-Flash-1017 update is focused on cheaper AI with stronger coding and agent performance. The reported DeepSWE score went up from 74.2 to 77.0. Automation-Bench increased from 54.8 to 60.5. These are company published benchmarks, not proof of real-world superiority.
💡 Why it matters: Better performance per dollar could mean lower AI development costs and more competition among AI providers. DeepSeek also says Search and Fetch APIs cost $0.75, per 1,000 calls.
🌕 For crypto the connection is not direct: cheaper AI tools might help blockchain analytics, trading bots and Web3 development—. This release alone does not prove a positive market signal.
Will low-cost AI change Web3 development. Will premium models still have the advantage?
Personal analysis, not advice.
#DeepSeek #AI #crypto #Web3
$FET $RENDER $NEAR
{spot}(NEARUSDT)
{spot}(RENDERUSDT)
{spot}(FETUSDT)
#deepseekreleasesupdatedaimodel 🚀 DeepSeeks New AI Model Raises the Competition Bar!
🌕 DeepSeeks V4.1-Flash-1017 update is focused on cheaper AI with stronger coding and agent performance. The reported DeepSWE score went up from 74.2 to 77.0. Automation-Bench increased from 54.8 to 60.5. These are company published benchmarks, not proof of real-world superiority.
💡 Why it matters: Better performance per dollar could mean lower AI development costs and more competition among AI providers. DeepSeek also says Search and Fetch APIs cost $0.75, per 1,000 calls.
🌕 For crypto the connection is not direct: cheaper AI tools might help blockchain analytics, trading bots and Web3 development—. This release alone does not prove a positive market signal.
Will low-cost AI change Web3 development. Will premium models still have the advantage?
Personal analysis, not advice.
#DeepSeek #AI #crypto #Web3
$FET $RENDER $NEAR
🌕 DeepSeeks V4.1-Flash-1017 update is focused on cheaper AI with stronger coding and agent performance. The reported DeepSWE score went up from 74.2 to 77.0. Automation-Bench increased from 54.8 to 60.5. These are company published benchmarks, not proof of real-world superiority.
💡 Why it matters: Better performance per dollar could mean lower AI development costs and more competition among AI providers. DeepSeek also says Search and Fetch APIs cost $0.75, per 1,000 calls.
🌕 For crypto the connection is not direct: cheaper AI tools might help blockchain analytics, trading bots and Web3 development—. This release alone does not prove a positive market signal.
Will low-cost AI change Web3 development. Will premium models still have the advantage?
Personal analysis, not advice.
#DeepSeek #AI #crypto #Web3
$FET $RENDER $NEAR
268
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