<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:content="http://purl.org/rss/1.0/modules/content/"><channel><title>LLMs on 梦兽编程</title><link>https://rexai.top/en/ai/llm/</link><description>Recent content in LLMs on 梦兽编程</description><generator>Hugo -- 0.163.3</generator><language>en</language><copyright>梦兽编程</copyright><lastBuildDate>Sun, 19 Apr 2026 10:00:00 +0800</lastBuildDate><atom:link href="https://rexai.top/en/ai/llm/index.xml" rel="self" type="application/rss+xml"/><item><title>Did Claude Opus 4.7 Secretly Raise Prices? 497 Developers Reveal the Truth</title><link>https://rexai.top/en/ai/llm/2026-04-19-opus-47-token-cost-shock/</link><pubDate>Sun, 19 Apr 2026 10:00:00 +0800</pubDate><guid>https://rexai.top/en/ai/llm/2026-04-19-opus-47-token-cost-shock/</guid><description>497 anonymous developer submissions reveal Claude Opus 4.7 consumes 37.3% more tokens than 4.6 on average, with API costs rising proportionally. Here&amp;#39;s what caused the &amp;#39;hidden price hike&amp;#39; and what you can do about it.</description></item><item><title>Your AI Agent Can Think, But It Can't Remember</title><link>https://rexai.top/en/ai/llm/2026-03-26-ghost-agent-memory-postgresql/</link><pubDate>Thu, 26 Mar 2026 00:00:00 +0000</pubDate><guid>https://rexai.top/en/ai/llm/2026-03-26-ghost-agent-memory-postgresql/</guid><description>AI agents can reason, plan, and converse—but forget everything once the session ends. The Ghost project solves this with a pure PostgreSQL-based infrastructure, turning the database into the agent&amp;#39;s memory palace.</description></item><item><title>Cramming a 400B Model into 48GB: The Magic Behind LLM in a Flash</title><link>https://rexai.top/en/ai/llm/2026-03-24-apple-llm-in-flash-moe-local-inference/</link><pubDate>Tue, 24 Mar 2026 00:00:00 +0000</pubDate><guid>https://rexai.top/en/ai/llm/2026-03-24-apple-llm-in-flash-moe-local-inference/</guid><description>An Apple paper from 2023 made it possible to run a 400 billion parameter model on an ordinary MacBook. The core technologies—MoE and quantization—hide an engineering philosophy built around on-demand loading.</description></item><item><title>90 Seconds of Waiting, Gone: How oMLX Buries Ollama on Mac</title><link>https://rexai.top/en/ai/llm/2026-03-23-omlx-apple-silicon-llm-inference/</link><pubDate>Mon, 23 Mar 2026 00:00:00 +0000</pubDate><guid>https://rexai.top/en/ai/llm/2026-03-23-omlx-apple-silicon-llm-inference/</guid><description>oMLX is built for Apple Silicon, using the MLX framework, SSD-backed KV cache, and continuous batching to cut TTFT from 90 seconds to 1-3 seconds in long-context scenarios, comprehensively outperforming Ollama.</description></item><item><title>Don't Build a Thousand Agents: How Ramp Automates Finance with One Agent</title><link>https://rexai.top/en/ai/llm/2026-03-19-ramp-one-agent-financial-automation/</link><pubDate>Thu, 19 Mar 2026 00:00:00 +0000</pubDate><guid>https://rexai.top/en/ai/llm/2026-03-19-ramp-one-agent-financial-automation/</guid><description>Ramp, America&amp;#39;s fastest-growing enterprise finance platform valued at $32B with 50,000+ customers and $100B+ in annual transaction volume, chose a &amp;#39;one Agent + a thousand skills&amp;#39; architecture over building many agents. This is a deep dive into Ramp&amp;#39;s AI实战经验.</description></item><item><title>AI Programming Hits the 'Review Bottleneck'? Mistral Drops an Open-Source Bomb</title><link>https://rexai.top/en/ai/llm/2026-03-17-leanstral-intro/</link><pubDate>Tue, 17 Mar 2026 00:00:00 +0000</pubDate><guid>https://rexai.top/en/ai/llm/2026-03-17-leanstral-intro/</guid><description>Mistral AI releases Leanstral, the first open-source Lean 4 code agent that lets AI both write code and prove its correctness. Let&amp;#39;s talk about formal verification and AI programming.</description></item><item><title>AI Agents Finally Make Literate Programming Worth Trying</title><link>https://rexai.top/en/ai/llm/2026-03-09-ai-literate-programming-agent-era/</link><pubDate>Mon, 09 Mar 2026 10:30:00 +0800</pubDate><guid>https://rexai.top/en/ai/llm/2026-03-09-ai-literate-programming-agent-era/</guid><description>Literate programming has been around for 40 years but never caught on — because maintaining parallel narratives of code and prose is exhausting. AI agents change that equation entirely.</description></item><item><title>Locking Down Your Local AI Agent: An Agent Safehouse Review</title><link>https://rexai.top/en/ai/llm/2026-03-09-agent-safehouse/</link><pubDate>Mon, 09 Mar 2026 00:00:00 +0800</pubDate><guid>https://rexai.top/en/ai/llm/2026-03-09-agent-safehouse/</guid><description>A macOS tool that sandboxes AI agents like Claude Code and Codex, preventing accidental file deletions and credential leaks once and for all.</description></item><item><title>Karpathy's Latest Work: Complete GPT in 200 Lines of Code - The Most Adorable AI Tutorial</title><link>https://rexai.top/en/ai/llm/2026-03-02-microgpt-200-lines-gpt-from-scratch/</link><pubDate>Mon, 02 Mar 2026 08:00:00 +0800</pubDate><guid>https://rexai.top/en/ai/llm/2026-03-02-microgpt-200-lines-gpt-from-scratch/</guid><description>Andrej Karpathy has done it again! This time he implemented a trainable, inferable GPT model in just 200 lines of pure Python with no dependencies. This might be the most concise large language model implementation ever.</description></item><item><title>Neural Network Reverse Engineering: When Machine Learning Becomes a Puzzle Game</title><link>https://rexai.top/en/ai/llm/2026-02-28-neural-network-reverse-engineering-puzzle/</link><pubDate>Sat, 28 Feb 2026 00:00:00 +0000</pubDate><guid>https://rexai.top/en/ai/llm/2026-02-28-neural-network-reverse-engineering-puzzle/</guid><description>Jane Street released a special ML puzzle: given the complete neural network weights, find an input that makes it output non-zero. This isn&amp;#39;t a typical black-box attack - it requires truly understanding what the network is computing. A college student spent days, going from linear programming to SAT solvers, and finally discovered the network was hiding an MD5 hash function.</description></item><item><title>GLM-5 Just Dropped: $1/M Tokens Doing What $5/M Does — Is Your AI Subscription Still Worth It?</title><link>https://rexai.top/en/ai/llm/2026-02-18-glm5-vs-claude-opus-coding/</link><pubDate>Wed, 18 Feb 2026 10:00:00 +0800</pubDate><guid>https://rexai.top/en/ai/llm/2026-02-18-glm5-vs-claude-opus-coding/</guid><description>Zhipu AI&amp;#39;s GLM-5 scores 77.8% on SWE-bench with a 744B MoE architecture, MIT license, and $1/M token pricing — just 3 points behind Claude Opus 4.6 at 1/5 the cost. We ran real benchmarks and code tests to help you decide where your AI budget should go.</description></item><item><title>I Spent $400 on Claude Code, Then Switched to Codex</title><link>https://rexai.top/en/ai/llm/ai-buddy-chat/</link><pubDate>Sun, 11 Jan 2026 00:00:00 +0000</pubDate><guid>https://rexai.top/en/ai/llm/ai-buddy-chat/</guid><description>After a month and $400, I went from being a Claude Code fanatic to a Codex user. This is a real user experience report.</description></item><item><title>How I Use Skills to Turn My AI Assistant into a Loyal Workmate</title><link>https://rexai.top/en/ai/llm/ai-skills-personal-assistant-guide/</link><pubDate>Wed, 17 Dec 2025 00:00:00 +0000</pubDate><guid>https://rexai.top/en/ai/llm/ai-skills-personal-assistant-guide/</guid><description>Step-by-step guide to using Skills so Codex and Claude shift from generalists into assistants that follow your playbook.</description></item><item><title>Mistral 3 Official Release: The Latest Work from Europe’s AI Giant</title><link>https://rexai.top/en/ai/llm/mistral-3-official-release-europe-ai-giant-latest-work/</link><pubDate>Thu, 04 Dec 2025 15:19:00 +0800</pubDate><guid>https://rexai.top/en/ai/llm/mistral-3-official-release-europe-ai-giant-latest-work/</guid><description>While OpenAI, Google, and Anthropic battle it out across the Atlantic, Europe’s AI power is quietly rising. On December 2, Paris-based Mistral AI officially released its third-generation model family, Mistral 3.</description></item><item><title>Bring Kimi K2 Thinking Home with 247GB RAM: Dynamic 1-bit GGUF Field Notes</title><link>https://rexai.top/en/ai/llm/kimi-k2-thinking-dynamic-gguf/</link><pubDate>Tue, 11 Nov 2025 07:41:51 +0000</pubDate><guid>https://rexai.top/en/ai/llm/kimi-k2-thinking-dynamic-gguf/</guid><description>Step-by-step guide to running Unsloth&amp;#39;s Dynamic 1-bit GGUF build of the 1T-parameter Kimi K2 Thinking model on high-end PCs, covering install, download, inference, serving, and troubleshooting.</description></item><item><title>Tokencake: Multi-Agent KV Cache Scheduling That Cuts vLLM Latency by Half</title><link>https://rexai.top/en/ai/llm/tokencake-kv-cache-vllm/</link><pubDate>Thu, 30 Oct 2025 11:49:25 +0800</pubDate><guid>https://rexai.top/en/ai/llm/tokencake-kv-cache-vllm/</guid><description>Beihang/Peking/Alibaba introduce Tokencake, a KV-cache-centric serving framework for multi-agent apps. With time+space scheduling plus CPU buffering and progressive GPU reservation, it trims end-to-end latency by 47%+ versus vLLM and lifts GPU cache utilization by ~17%.</description></item><item><title>Agno-Go: Building AI Agents in Go - What's it Like Being 16x Faster than Python?</title><link>https://rexai.top/en/ai/llm/agno-go-high-performance-agent-framework/</link><pubDate>Sat, 04 Oct 2025 00:00:00 +0000</pubDate><guid>https://rexai.top/en/ai/llm/agno-go-high-performance-agent-framework/</guid><description>Rewriting AI Agent framework in Go brings 16x performance boost, 180ns agent startup, and only 1.2KB memory footprint - this is the extreme experience Agno-Go delivers</description></item><item><title>DeepSeek Drops a Bombshell: V3.2-Exp Sparse Attention Mechanism Debuts, API Prices Slashed in Half Again</title><link>https://rexai.top/en/ai/llm/deepseek-v32-exp-sparse-attention-breakthrough/</link><pubDate>Wed, 29 Jan 2025 10:00:00 +0800</pubDate><guid>https://rexai.top/en/ai/llm/deepseek-v32-exp-sparse-attention-breakthrough/</guid><description>DeepSeek-V3.2-Exp released with groundbreaking DSA sparse attention technology, 2-3x faster inference, 30-40% memory reduction, and API prices cut by over 50%</description></item></channel></rss>