ranking

AppWizard
May 21, 2026
Google has updated its "Android Bench" rankings, introducing new AI models for Android app development, including open-weight models. The latest rankings, as of May 18, 2026, show GPT 5.5 at the top, surpassing GPT 5.4 and Gemini 3.1 Pro by nearly 2%. The update provides metrics such as average latency, total tokens used, and average cost per benchmark run. GPT 5.5 has a score of 74, with an average latency of 15.5, total tokens of 64.5, and an average cost of .9. In comparison, GPT 5.4 has a score of 72.4, with an average latency of 21.2, total tokens of 64.2, and an average cost of [openai_gpt model="gpt-4o-mini" prompt="Summarize the content and extract only the fact described in the text bellow. The summary shall NOT include a title, introduction and conclusion. Text: Google has refreshed its “Android Bench” rankings, unveiling a new lineup of AI models tailored for Android app development. This update introduces several “open-weight” models and provides deeper insights into the performance metrics, including token usage and associated costs. Large language models have increasingly demonstrated their prowess in coding, significantly enhancing the app development process. This trend has given rise to what is now known as “vibe coding.” Earlier this year, Google released a benchmark ranking that evaluated the top AI models for Android development, focusing on common tasks and adherence to best practices. Initially, the rankings were led by Gemini 3.1 Pro, with OpenAI’s GPT 5.4 later sharing the spotlight. However, as of the latest update on May 18, 2026, a new contender has emerged. GPT 5.5 has claimed the top position, surpassing GPT 5.4 and Gemini 3.1 Pro by nearly 2%. This update also enhances clarity by presenting average latency, total tokens utilized, and the average cost associated with each AI model. Google has provided documentation detailing the methodology behind these metrics. Average Latency: Time taken to complete 100 tasks across 10 runs Average Total Tokens: Token consumption for a complete benchmark run across 10 iterations Average Cost: Cost per benchmark run in US dollars at the time of testing While GPT 5.5 boasts superior performance, it comes at a cost—over twice that of Gemini 3.1 Pro for equivalent functions. Here’s a look at the top ten models based on Google’s latest data as of May 21, 2026: Model Score Avg Latency Avg Total Tokens Avg Cost New: GPT 5.5 74 15.5 64.5 3.9 GPT 5.4 72.4 21.2 64.2 .7 Gemini 3.1 Pro Preview 72.4 11.5 75.4 .0 New: Claude Opus 4.7 68.7 11.6 90.0 4.3 GPT 5.3 Codex 67.7 11.2 71.4 .6 Claude Opus 4.6 66.6 9.9 69.5 .4 GPT 5.2 Codex 62.5 24.3 124.4 1.9 Claude Opus 4.5 61.9 12.5 79.8 2.5 Gemini 3 Pro Preview 60.4 9.8 117.0 .7 New: GLM 5.1 59.7 33.4 80.2 .7 The rankings now feature a wider array of open-weight models, including Gemma, Qwen, DeepSeek, and MiMo, among others. GLM 5.1 has emerged as the highest scorer among these newcomers, closely followed by Kimi K2.6. Google is committed to updating the “Android Bench” on a monthly basis. With the anticipated release of Gemini 3.5 Pro and the already available 3.5 Flash, the competitive landscape will be intriguing to watch as Google seeks to reclaim its lead against OpenAI's advancements. More on Android: Follow Ben: Twitter/X, Threads, Bluesky, and Instagram FTC: We use income earning auto affiliate links. More." max_tokens="3500" temperature="0.3" top_p="1.0" best_of="1" presence_penalty="0.1" frequency_penalty="frequency_penalty"].7. Gemini 3.1 Pro has the same score as GPT 5.4 but with different latency and token metrics. The rankings also include other models like Claude Opus 4.7, GPT 5.3 Codex, and GLM 5.1, which has emerged as the highest scorer among newcomers. Google plans to update the rankings monthly.
Tech Optimizer
May 18, 2026
Google is integrating artificial intelligence into PostgreSQL engineering while ensuring engineers remain responsible for their code contributions. This initiative aims to improve productivity and streamline processes, particularly in version upgrades, replication behavior, and production recovery. Sailesh Krishnamurthy, Google Cloud's VP of Databases, emphasized the importance of human oversight in this AI-driven approach. Between July and December 2025, Google's PostgreSQL engineering focused on logical replication, improvements to pg_upgrade, and upstream bug fixes. Logical replication allows selective database change transfers, which is beneficial for migrations and upgrades. The roadmap includes Automatic Conflict Detection and logical replication of sequences to minimize manual synchronization issues. Enterprise teams are particularly interested in these developments due to the challenges posed by write collisions and misaligned sequence values. The demand for PostgreSQL services at Google is increasing due to migration needs from Oracle and SQL Server. Recent data shows PostgreSQL's rising popularity, ranking fourth in the DB-Engines ranking and gaining 8.37 points year over year, while its competitors experienced declines.
Tech Optimizer
May 15, 2026
PostgreSQL is widely used across various industries, supported by Microsoft through significant investments, including 345 commits to the latest release and a dedicated team of contributors. It is recognized for its ability to handle complex production challenges, such as transactional integrity and concurrency management. Microsoft operates PostgreSQL globally, informing upstream contributions based on real-world deployment experiences. The database is increasingly integrated into AI applications, with Azure Database for PostgreSQL and Azure HorizonDB focusing on AI functionalities. Microsoft offers multiple deployment models to accommodate different workload needs, including Azure Database for PostgreSQL for open-source workloads and Azure HorizonDB for cloud-native systems. Recent contributions from Microsoft include enhancements in asynchronous I/O, vacuum behavior, and query planning. Azure HorizonDB is designed for high-throughput, low-latency systems requiring horizontal scaling. Microsoft also invests in developer tools, such as a Visual Studio Code extension for PostgreSQL, and sponsors PostgreSQL conferences and user groups globally.
Winsage
May 14, 2026
Microsoft has introduced MDASH (Multi-Model Agentic Scanning Harness), a security solution that uses over 100 specialized AI agents to identify software vulnerabilities. On May 12, 2026, MDASH identified 16 new vulnerabilities (CVEs) in the Windows networking and authentication stack, four of which were critical, including remote code execution vulnerabilities in tcpip.sys, ikeext.dll, netlogon.dll, and dnsapi.dll. Ten of these vulnerabilities can be accessed over the network without authentication. MDASH operates through a four-stage pipeline: analyzing source code, scrutinizing for suspicious elements, debating the exploitability of issues, and attempting to exploit vulnerabilities. The system is model-agnostic and allows integration of new models and domain-specific knowledge. MDASH scored 88.45 percent on the CyberGym benchmark, ranking first among competitors, although the comparison may not be entirely fair as it contrasts a comprehensive framework with individual models. The models used to achieve this score are not specified. MDASH is supported by Microsoft's Autonomous Code Security Team and is currently in a limited private preview for select customers.
AppWizard
May 3, 2026
Marlow became a notable figure in Minecraft's Crystal PvP scene, known for her montage videos and distinctive blue and white-haired skin, attracting a large following. However, concerns arose about the authenticity of her content, leading to a scandal involving allegations of deception regarding her identity, with claims that she might be a man using the alias "Danger Mario." Accusations included cheating in ranked matches, staging PvP recreations, and using AI-generated voice tools to maintain her female persona. A report by Dexerto in May 2026 brought the controversy to wider attention, resulting in significant upheaval within MC Tiers, including staff resignations and credibility issues. Prominent players began distancing themselves from Marlow, raising questions about trust and integrity in the competitive Minecraft community.
AppWizard
May 2, 2026
Subnautica 2 is set for early access release on May 14. Developer Unknown Worlds faced challenges, including a public falling out with publisher Krafton and the dismissal of its management team, but the CEO has been reinstated. Square Glade Games has moved the release of their game Outbound to May 11 to avoid competition with Subnautica 2. Outbound is currently ranked 13th on Steam's Most Wishlisted chart. Subnautica 2 will allow players to explore an open-water environment, featuring solo and multiplayer experiences, and will be available on PC and Xbox Series X/S.
Tech Optimizer
May 1, 2026
Antivirus software protects against various sophisticated malware threats, including ransomware, spyware, phishing attacks, and adware. When selecting antivirus software, consider the number of devices needing protection, the operating systems in use, and whether the protection is for personal or business purposes. Free antivirus options have improved and may suffice for average users, while paid plans typically offer better protection and support. Evaluating products involves reading privacy policies, utilizing free trials, and checking independent test results. The best antivirus software depends on individual needs, devices, budget, and online behavior.
Tech Optimizer
April 28, 2026
Constructive has released agentic-db, an open-source Postgres database aimed at improving AI agents with features like persistent memory, structured knowledge, and hybrid retrieval. This database allows for efficient searching, filtering, and ranking of information, addressing inefficiencies associated with traditional markdown file storage. Key features of agentic-db include long-term memory, conversation tracking, a versioned registry for skills and tools, rules and policies for governance, task orchestration, and runtime observability. It is delivered as a single installable Postgres schema, indexed for multiple retrieval modes, and supports integration with various AI assistants through generated Agent Skills and CLIs. agentic-db is available under the MIT license for local use, with a cloud offering in development for secure, scalable solutions. Developers can access it on npm and GitHub.
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