[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"news-slug-may-2026-300-llm-release-explosion":3,"topics-all":36,"news-related-a9191131-1fe3-42e4-870d-2621ef5874d1":55},{"id":4,"title":5,"summary":6,"content":6,"original_url":7,"source_id":8,"tags":9,"translations":23,"news_slug":29,"published_at":30,"created_at":31,"modified_at":32,"is_published":33,"publish_type":34,"image_url":13,"view_count":35},"a9191131-1fe3-42e4-870d-2621ef5874d1","5月LLM发布大爆炸：300款模型混战，重塑AI产业格局","2026年5月，LLM战场进入了前所未有的混战模式。据AI-Stat统计，仅前半月就有8款大型模型发布，全月追踪到300余款新模型。这一轮发布的密度和多样性，正在重塑行业格局。\n\n重量级选手的动向中，GPT-5.5 Instant于5月4日发布，随即成为ChatGPT所有用户的默认模型。相比前代，它减少了emoji污染和过度格式化，事实准确性显著提升，并改善了搜索决策能力。OpenAI还宣布GPT-5.3 Instant将继续保留3个月，为过渡期用户提供平滑迁移。Gemini 3.5 Flash于5月18日登场，以Gemini系列最快模型为定位，输入价格为150美元\u002F百万token，低于Gemini 3.1 Pro，主打高吞吐、低延迟场景。xAI则在5月5日发布Grok 4.3，整合X\u002FTwitter实时数据（延迟仅2秒），在推理性能上逼近Claude Opus 4.7，价格为2\u002F15美元\u002F百万token，性价比突出。\n\n开源阵营的反击中，DeepSeek-V4-Pro-Max在SWE-bench上拿下开源模型第一，API价格仅为闭源模型的十分之一到五十分之一。它与Mistral Medium 3.5（128K上下文，Apache 2.0协议）形成开源阵营的双前锋，向闭源格局发起实质挑战。\n\n300+模型涌入的背后，隐藏着更深的行业逻辑：通用模型的军备竞赛正在降温，推理模型、高速模型、多模态模型等细分赛道快速崛起。2026年是LLM从大一统走向专业化的拐点。\n\nGPT-4级别的能力如今只需0.06美元\u002F百万输入token即可获取（通过DeepSeek\u002FDeepInfra），而2024年这个数字是30美元。驱动力来自量化技术、优化推理引擎和更高效的模型架构。这场效率革命比任何新模型发布都更值得关注——它正在让AI能力从奢侈品变成日用品。","https:\u002F\u002Fwww.ai-stat.ru\u002Fnews\u002F2026-05-22-llm-releases-may-2026-overview","d9a70dd1-6423-450c-bf40-b31fc390711f",[10,14,17,20],{"id":11,"name":12,"slug":12,"description":13,"color":13},"0ef8513a-0a26-42f0-b6f9-5b6dadded45c","efficiency",null,{"id":15,"name":16,"slug":16,"description":13,"color":13},"0a93ec8e-ea39-4693-81de-563ca8c173f7","inference",{"id":18,"name":19,"slug":19,"description":13,"color":13},"01598627-1ea6-4b27-a5d8-874971571a71","llm",{"id":21,"name":22,"slug":22,"description":13,"color":13},"7e89b5cc-57db-4f37-bc6d-28919a73931c","model-release",[24],{"id":25,"lang":26,"title":27,"summary":28,"content":13},"61f4f520-dd43-4df7-a7b5-c9a1242a3e72","en","May's LLM explosion: 300 models reshape the AI landscape","AI-Stat provides an overview of the 300+ LLM releases in May 2026. The article analyzes the major trends: closed-source models consolidating around \"Pro\u002FFlash\u002FLite\" tiers, open-source catching up on specific tasks, and the shift from \"model release\" to \"product release.\"","may-2026-300-llm-release-explosion","2026-05-28T08:05:00Z","2026-05-28T16:06:09.824251Z","2026-08-19T02:08:40.142862Z",true,"agent",215,[37,46],{"slug":38,"tag_slug":38,"title_zh":39,"title_en":40,"intro_zh":41,"intro_en":42,"id":43,"is_active":33,"created_at":44,"modified_at":45},"ai-for-science","AI for Science 2026：从 UniPert 到 GPT-Rosalind 的硬核进化","AI for Science 2026: from UniPert to GPT-Rosalind","生命科学、化学材料、物理世界模型——AI 正在从\"语言工具\"变成\"实验伙伴\"。本专题收录 AI 在三大科学方向的关键节点：UniPert 统一基因与化学扰动空间、GPT-Rosalind 端到端生命科学推理、达摩院 AI 智能体 28 小时找到 4 种超导新材料、Anthropic Claude Science 把工作台做成标准品。","From language tool to lab partner — AI is reshaping life sciences, chemistry\u002Fmaterials, and physical world models. This topic covers the key milestones: UniPert unifying genetic-chemical perturbation spaces, GPT-Rosalind's end-to-end life-sciences reasoning, DAMO's AI agent discovering 4 superconducting materials in 28 hours, and Anthropic's Claude Science workbench going mainstream.","988a4300-5fab-41c4-b5d8-63711a2dc757","2026-09-10T01:34:15.296649Z","2026-09-10T01:34:15.296663Z",{"slug":47,"tag_slug":47,"title_zh":48,"title_en":49,"intro_zh":50,"intro_en":51,"id":52,"is_active":33,"created_at":53,"modified_at":54},"h3-series","MiniMax H3 系列：从开源权重到 35 倍吞吐","MiniMax H3 Series: from open weights to 35x throughput","MiniMax H3 自 2026 年 8 月开源以来节奏密集：官方把生成、参考与编辑收回一个模型；ComfyUI 当天压进 RTX 3060；摩尔线程 3 小时完成国产 GPU 适配；fal 后训练版把吞吐拉到 35 倍；FastH3 蒸馏再砍推理成本。本专题持续追踪 H3 的发布—开源—蒸馏—部署全链路。","Since MiniMax open-sourced H3 in August 2026 the pace has been relentless: one unified omni-modal model, same-day ComfyUI support down to an RTX 3060, a 3-hour Day-0 port to Moore Threads GPUs, fal's post-trained H3 Max at 35x throughput, and FastH3 distillation cutting inference cost further. This topic tracks the full H3 chain — release, open weights, distillation, deployment.","83ef0daa-3c31-4cb3-86ed-e5ee58654d5f","2026-09-08T07:33:19.942193Z","2026-09-08T07:33:19.942209Z",{"items":56},[57,62,67,72,77,82],{"id":58,"title":59,"news_slug":60,"published_at":61},"8c6d408b-2913-48b2-bc1f-4e958ad854c5","Space Bunny 谜底揭晓:MiniMax M3.1 Flash,匿名期吞下 200 万亿 token","minimax-m3-1-flash-space-bunny","2026-10-19T21:10:12+00:00",{"id":63,"title":64,"news_slug":65,"published_at":66},"8c27ba0d-9f70-4e4c-9a9b-092eec0db248","Grok 4.3 登陆 OCI：xAI 与 Oracle 的「次日达」合作意味着什么","grok-4-3-oci-oracle-next-day","2026-05-15T04:10:00+00:00",{"id":68,"title":69,"news_slug":70,"published_at":71},"be76fca7-bc02-4a76-a58f-17a661b82b60","SparPR:消费级显卡的KV缓存回收术","sparpr-kv-cache-recovery-consumer-gpu","2026-10-22T01:20:00+00:00",{"id":73,"title":74,"news_slug":75,"published_at":76},"8c579d8d-4114-4d7d-92c1-22f5fab0537b","连续流语言模型跑到 8B：Lafa 单模型自验证解码提速 2.54 倍","large-flow-language-models-lafa-self-speculative-decoding","2026-10-21T03:09:03+00:00",{"id":78,"title":79,"news_slug":80,"published_at":81},"713ebd28-7abc-4664-acd5-8ba7c6b50d97","扩散 LLM 能否 scale?Mercury 3 用 40 倍规模和 1M 上下文作答","mercury-3-diffusion-scaling","2026-10-19T23:09:33+00:00",{"id":83,"title":84,"news_slug":85,"published_at":86},"559df680-f13e-48f0-9263-73116aaff411","上交大DLite免历史投机解码:Agent提速2.74倍","dlite-history-free-speculative-decoding","2026-10-19T17:07:52+00:00"]