The article compares Claude Opus, OpenAI Codex, and Zhipu's open‑source GLM‑5.1, detailing their strengths, benchmark results, pricing, and ideal use cases, and recommends routing tasks to the model that best fits the complexity and language requirements.
On May 22, Zhipu launched the GLM‑5.1‑highspeed API, delivering 400 tokens per second—about 7× faster than the original model and twice as fast as Gemini 3.5 Flash—through a three‑layer optimization that rewrites the MoE inference path, introduces dynamic scheduling, and leverages TileRT’s AOT engine to cut latency while preserving full flagship capabilities.
The article reviews iFlytek’s Coding Plan, highlighting its three pricing tiers—including a 3.9 CNY entry tier that unlocks GLM‑5.1 for Claude Code—explains how request‑based billing reduces token anxiety, and provides step‑by‑step integration guides for Claude Code, OpenClaw and Cursor along with real‑world skill examples.
The article provides a detailed April 2026 comparison of API pricing for six major AI model families—including DeepSeek, GLM‑5.1, Kimi, Claude, GPT‑5.5, and Gemini—covering official and proxy channels, context limits, discount periods, peak‑time surcharges, and practical selection recommendations for developers.
This article provides a detailed, data‑driven comparison of three 2026 Chinese flagship large language models—GLM-5.1, Qwen3.6 Plus, and MiniMax M2.7—covering knowledge, math, code, long‑task, multimodal performance, pricing, open‑source status, ecosystem support, and scenario‑based recommendations.
The article analyzes how Chinese large language models like GLM‑5.1, Qianwen 3.6‑Plus and Gemma 4 achieve roughly one‑tenth the cost of GPT‑5.4, leading to dramatically higher profit margins, silent migration in Silicon Valley, and a rapid rise in market share backed by a maturing ecosystem.
The AI daily briefing highlights GLM‑5.1’s breakthrough 8‑hour continuous reasoning, its top performance on SWE‑bench and a 10% price hike, while Tencent’s QBotClaw introduces the first domestically free‑configurable large‑model API browser, signaling a shift toward open AI ecosystems in China.
The open‑source GLM‑5.1 model, adapted to Baidu Baige's Kunlun XPU via the vLLM‑Kunlun Plugin, delivers record‑breaking SWE‑bench scores, eight‑hour autonomous coding, long‑context handling up to 64K tokens, and scalable deployment across tens of thousands of chips, showcasing end‑to‑end AI acceleration.
GLM-5.1, the newly open‑sourced large language model, leads global code‑generation benchmarks, excels at eight‑hour continuous long‑term tasks, can build a complete Linux desktop in eight hours, and even creates a short video from an article with just one prompt.
GLM‑5.1, the new 744 B‑parameter open‑source LLM from Zhipu, tops SWE‑Bench Pro with a score of 58.4, outpacing Claude Opus, GPT‑5.4 and Gemini, excels at long‑duration autonomous tasks, yet shows gaps in single‑turn generation and pure mathematical reasoning.
Using the GLM‑5.1 large language model, the author automated the end‑to‑end development of an ontology‑based knowledge‑graph extraction and visualization platform—covering backend, frontend, and graph database—in just 2 hours 47 minutes, consuming 747 k tokens and self‑correcting multiple issues.
The article presents a detailed, hands‑on evaluation of the newly released GLM‑5.1 model, describing the rollout strategy, step‑by‑step testing on complex coding tasks, configuration details, observed performance improvements over previous versions, and practical guidance for developers seeking to leverage the model for real‑world projects.
GLM-5.1 is now available to all Coding Plan subscribers, including the $10/month Lite tier, scoring 45.3 on SWE‑bench—just 5.4% below Claude Opus 4.6’s 47.9—while offering 20+ tool integrations and a manual switch from the default GLM‑4.7 model.
