Zhipu-Ai

Z.ai is Zhipu AI’s international developer platform for the GLM model family, exposing the models through both an Anthropic-compatible and an OpenAI-compatible API (quick start). As of October 2026, the current flagship is GLM-5.3 with the cheaper GLM-5.3-Flash alongside it, and the GLM Coding Plan has moved from quarterly tiers to a credits-based subscription that the vendor advertises as starting at 18 USD per month (plan overview). This revision re-opened the vendor’s own pages on 2026-10-29 and did two things the earlier version did not: it added the key-type rules that took effect on 2026-10-16, and it added the error-handling section a developer needs when a request fails. Endpoints, model names and prices were re-checked rather than rewritten. ...

GLM-5 and GLM-5.1 are Zhipu AI’s frontier open-weight models — 744B-754B parameter MoE architectures trained entirely on Huawei Ascend chips, priced at 5–10x less than GPT-5.5, and licensed under MIT for commercial self-hosting. GLM-5.1 briefly topped SWE-Bench Pro in April 2026 with a 58.4 score, making it the first open-weight model to claim that position. What Are GLM-5 and GLM-5.1? (Zhipu AI / Z.ai Overview) GLM-5 and GLM-5.1 are the fifth-generation General Language Models from Zhipu AI, a Beijing-based AI lab (now operating its API platform under the brand Z.ai) that completed a HKD 4.35 billion (~$558 million) Hong Kong IPO in January 2026. The GLM series has competed with GPT models since 2021; GLM-5 marks the first time Zhipu released a frontier-class model at scale under an MIT license — meaning any developer or company can deploy it commercially without royalty agreements or usage restrictions tied to a single cloud vendor. ...

GLM-5V-Turbo is Zhipu AI’s first native multimodal agent foundation model, released April 1, 2026, purpose-built for vision-driven coding and autonomous GUI workflows — not a text model with a vision adapter bolted on afterward. With a 94.8 Design2Code score versus Claude Opus 4.6’s 77.3, and pricing at $1.20/M input tokens, it competes directly with frontier models at a fraction of the cost. What Is GLM-5V-Turbo? GLM-5V-Turbo is Zhipu AI’s (Z.ai’s) flagship multimodal agent foundation model, launched April 1, 2026, and the first in their GLM series built natively for both vision understanding and autonomous agent operation. Unlike most large vision-language models that graft a CLIP-based image encoder onto an existing text backbone, GLM-5V-Turbo was trained from the ground up with multimodal inputs as a first-class architectural concern. The model targets two specific production workloads where existing LLMs struggle: converting visual design artifacts (Figma mockups, screenshots, PDFs) into executable front-end code, and running autonomous GUI agent pipelines where the model must perceive a screen, plan an action, and execute it without human checkpoints. Zhipu AI — now publicly traded on the Hong Kong Stock Exchange since January 2026 — positions GLM-5V-Turbo as a direct challenger to Claude Opus 4.6 and GPT-4o Vision for developer-facing multimodal tasks, at roughly 76% lower output cost. The model is available via Z.ai’s developer platform and on OpenRouter. ...

GLM-4.7 from Zhipu AI scores 73.8% on SWE-bench and 84.9% on LiveCodeBench V6 — numbers that match or beat Claude Sonnet 4.5 on coding benchmarks. It’s fully open-source (Apache 2.0), runs locally, and costs $0 per token. If you’re paying $20+/month for a commercial coding assistant and your use case is standard development tasks, GLM-4.7 deserves a serious look. What Is GLM-4.7 and Why Are Developers Switching? GLM-4.7 is Zhipu AI’s flagship open-source large language model, optimized for multi-turn reasoning and software development tasks. Launched in early 2026, it sits at the top of the open-source coding benchmark leaderboard: 73.8% on SWE-bench and 84.9% on LiveCodeBench V6, putting it within 2-3 percentage points of Claude Sonnet 4.5. What makes GLM-4.7 different from previous open-source coding models isn’t just benchmark scores — it’s the “Preserved Thinking” architecture that maintains reasoning quality across extended, multi-turn coding sessions. Most open-source models degrade noticeably after 5-6 back-and-forth exchanges as context fills up. GLM-4.7 scores 8.5/10 for complex reasoning consistency across 10+ turns, a gap that shows up directly when you’re doing iterative refactoring or debugging complex systems. Zhipu AI also made a hardware bet: GLM series models are trained entirely on Huawei Ascend chips, not NVIDIA, which matters for organizations concerned about supply chain dependencies. The combination of competitive benchmarks, zero licensing costs, and hardware independence is driving 40% year-over-year growth in open-source coding model adoption according to GitHub’s 2026 developer survey. ...