不会6月结束还有国产模型编程能力超不过opus 4.6吧？

中国正在形成“双HBM路线”格局。 长鑫HBM3已进入客户验证阶段，而华为则首次公开HiBL/HiZQ自研HBM路线。 从产品定位看，华为HBM更偏向昇腾950等高端AI集群，长鑫则有望承担国产HBM规模化供应任务。

Chinese multimodal powerhouse StepFun just flipped the global AI table. Step 3.7 Flash delivers 400 TPS inference, matching 97% of Claude Opus 4.6 at 1/9 the cost. This isn't a simple update—it's a paradigm shift for the Agent era. What should an Agent-era model look like? Give it a cockpit screenshot, old models just describe dials. Step 3.7 Flash selects the area, identifies instruments, plans steps, and guides a mouse through takeoff. From understanding to executing—that's the divide. The competition has changed. As Agents enter production, latency and token costs explode. Step 3.7 Flash uses sparse MoE (196B total, 11B active) for 400 TPS. Speed is capability—faster means more iterations, better results in multi-step tasks. Real tests: 12 messy receipts auto-extracted into Excel; Blender screenshot teaches you to delete a cube; Jianying interface locates export button, warns about 1080i and full-track export pitfalls. The model is on-site, working as your hands. Even more impressive: emergent behavior. After writing frontend code, it switches to GUI to test rendering, then revises its own code. No one taught it this loop—it figured it out. That's what an Agent should be. The Advisor strategy is the killer feature: small model executes, consults a larger model only at critical junctures. Result: $0.19 per task vs $1.76 for Claude Opus 4.6, with 97% coding capability. Two dimes vs two dollars—any team burning tokens gets it. Step 3.7 Flash isn't a benchmark king, but it dominates the cost-efficiency frontier. Multimodal extreme efficiency near-zero cost makes it the foundation for production-grade Agents. Flash is no longer a budget option—it's the pragmatic force taking over the world.

BYD hits new monthly sales record in May: 383,453 units! Overseas sales surged 80.7% YoY, with cumulative deliveries exceeding 1.4 million in Jan-May. The NEV leader accelerates global expansion as market penetration rises. Supply chain momentum continues.

As far as I know, besides the LogicFolding-enabled EDA tool recently released by Peking University, Huawei has also been working on this technology internally, and several other vendors are developing similar solutions as well. So while it may appear that Huawei is the one introducing the product, the reality is that Chinese semiconductor companies and universities have already been exploring and advancing along this path for quite some time.

Computex 2026 marks AI's shift from cloud to edge: PCs emerge as the prime device for local token generation, with mobile opportunities expected next year. Edge AI chips and AI PC supply chains enter a new growth cycle.

不会再有其他国家通过工业崛起了 未来10年，机器人的成本优势会迅速摧毁全球绝大多数地区的工业体系

华大九天在华为发布韬定律同日推出国内首款Argus 3DIC物理验证平台，填补高端3DIC设计工具空白，成为国内唯一全流程EDA提供商。

评估小米的股价就不能孤立的只看小米 19年的8块的底很大程度上是吃到了菊花制裁的红利 当时雷布斯去深圳找余大嘴承认华为 荣耀的步步紧逼使得当时的小米市占率极速下降 如果制裁再晚半年，这个底就不是8块了 所以现在的一切都并不难理解

A research team from Peking University has reportedly achieved a major breakthrough in “true 3D” EDA tools designed for τ-scaling and 3D logic folding architectures. The team developed what is claimed to be the world’s first “true 3D” physical implementation EDA prototype, aiming to overcome the limitations of traditional “pseudo-3D” design approaches. Instead of treating each die as the minimum optimization unit, the new system treats standard cells as the basic unit, allowing cells within the same module to be freely distributed across multiple dies and optimized collaboratively in 3D space. Reported benchmark results include: • 30% reduction in wire length • 6–12% timing improvement • 3% reduction in peak temperature • Verified at a scale of tens of millions of instances This directly addresses one of the core bottlenecks behind Huawei’s proposed τ-scaling theory: existing EDA tools are not designed to support large-scale logic folding architectures.

北京大学团队在面向“韬定律”3D逻辑折叠设计的“真3D”EDA方向取得关键进展 北大集成电路学院研发出全球首个"真3D"物理实现EDA工具原型，突破传统"赝3D"设计瓶颈。 将标准单元而非die作为最小优化单位，支持模块内单元跨die自由分布，实现三维空间协同布局。实测效果惊人：线长缩减30%、时序改善6-12%、峰值温度下降3% ，已验证千万级实例规模。 这直接回应了华为τ缩放理论的核心挑战——现有EDA无法承载逻辑折叠。

华为麒麟9050Pro（2026）和9060Pro（2027）相比麒麟9030Pro： CPU单核提升15%/44% CPU多核提升24%/56% GPU提升38%/87% NPU提升140%/213% CPU单核能效提升12%/34% GPU能效提升40%/78% NPU能效提升81%/118%

Compared with the Kirin 9030 Pro, the rumored Kirin 9050 Pro (2026) and Kirin 9060 Pro (2027) are expected to deliver: • CPU single-core performance: 15% / 44% • CPU multi-core performance: 24% / 56% • GPU performance: 38% / 87% • NPU performance: 140% / 213% Efficiency improvements: • CPU single-core efficiency: 12% / 34% • GPU efficiency: 40% / 78% • NPU efficiency: 81% / 118% #HUAWEI