AWS Outposts
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AWS Outposts is a fully managed service that offers the same AWS infrastructure, AWS services, APIs, and tools to virtually any datacenter, co-location space, or on-premises facility for a truly consistent hybrid experience. AWS Outposts is ideal for workloads that require low latency access to on-premises systems, local data processing, data residency, and migration of applications with local system interdependencies. AWS compute, storage, database, and other services run locally on Outposts, and you can access the full range of AWS services available in the Region to build, manage, and scale your on-premises applications using familiar AWS services and tools. Coming soon, a VMware variant of AWS Outposts will be available. VMware Cloud on AWS Outposts delivers a fully managed VMware Software-Defined Data Center (SDDC) running on AWS Outposts infrastructure on premises.
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Claude Sonnet 5.5
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Claude Sonnet 5.5 is Anthropic’s mid-tier Claude 5.5 model designed for fast, well-scoped everyday work, coding, and professional document creation. Anthropic says it runs more than 30% faster than Claude Sonnet 5 and typically costs up to 30% less per task while keeping the same base token pricing. The model shows major gains in agentic coding, with a 70.6% score on Terminal-Bench 4.0 and stronger performance on FrontierCode and CursorBench than its predecessor. Sonnet 5.5 also performs strongly on knowledge work, computer use, chart understanding, and long-horizon tasks, in some cases approaching Claude Opus 5.5 at higher effort settings. Anthropic positions it as especially useful for debugging, routine coding, collaboration, and producing polished documents, slides, spreadsheets, and user interfaces. Claude Sonnet 5.5 is available across Anthropic’s platforms as well as AWS, Google Cloud, and Microsoft Azure.
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SWE-2
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SWE-2 is Cognition’s advanced coding model designed to improve software engineering performance while reducing the cost of agentic coding workflows. The model is post-trained from Kimi K3 and uses reinforcement learning to optimize multiple reasoning-effort levels within a single training run. SWE-2 is designed to explore codebases more selectively, begin implementation sooner, and complete tasks with fewer redundant reads and reasoning steps than earlier Cognition models. Its capabilities include code generation, debugging, test creation, verification, repository analysis, and complex terminal-based software engineering tasks. The model also emphasizes stronger engineering judgment, end-to-end test coverage, instruction following, and evidence-based verification of user assumptions. SWE-2 is available through Devin Desktop and Devin CLI, with broader rollout planned across Devin Web and Fusion.
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Kimi K2.7 Code
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Kimi K2.7 Code is an open-source, coding-focused agentic AI model developed by Moonshot AI for long-horizon software engineering tasks. It is designed to improve coding performance, agent workflows, and real-world development assistance compared with earlier Kimi K2 versions. The model supports a 256K context window, making it useful for working with large codebases, long technical documents, and complex multi-step programming tasks. Kimi K2.7 Code is available through Kimi Code and API access, with OpenAI- and Anthropic-compatible options for easier integration into developer workflows. It is also listed on Hugging Face and supports deployment through inference engines such as vLLM, SGLang, and KTransformers. With improved agentic capabilities, long-context support, and reduced thinking-token usage compared with K2.6, Kimi K2.7 Code gives developers a flexible open-source option for AI-assisted coding.
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