GLM (ChatGLM)

Zhipu AI’s open-source LLM family, developed in Beijing as a 2019 spinoff of Tsinghua University’s KEG Lab. The consumer product rebranded to Z.ai in early 2026. The current flagship is GLM-5.1, released open-source under MIT license on April 7, 2026, and trained entirely on Huawei Ascend 910B chips with no Nvidia hardware.

GLM-5.1 topped SWE-Bench Pro at 58.4% at launch. The proprietary GLM-5 (February 2026) scored 77.8% on SWE-bench Verified, ahead of Gemini 3 Pro at 76.2% and within reach of Claude Opus 4.6 at 80.9%.

System Verdict

Pick GLM if you need an open-weight coding model near the SWE-Bench frontier. GLM-5.1 is freely downloadable under MIT, runs on consumer Hugging Face hardware or enterprise Ascend clusters, and matches or edges past Claude Opus 4.6 on specific coding benchmarks. OpenAI and Anthropic API compatibility makes it a drop-in backend for Cursor, Cline, and Continue.dev.

Skip it if you want a polished English consumer product or the cheapest API. Z.ai chat is functional but secondary to the Chinese-language experience. DeepSeek undercuts GLM-5 by 3-4x on pure API cost for non-coding chat. Zhipu raised prices 30% at GLM-5’s launch and another 10% at GLM-5.1, so cost predictability trails Qwen and DeepSeek.

Who uses which surface: Free Flash models for hobbyists and light tasks, GLM-5 API for production coding workloads, Coding Plan subscription (~$10 to $80/month) for IDE users, self-hosted GLM-5.1 weights for teams avoiding vendor lock-in.

Key Facts

Every data point above was verified on 2026-04-17. See Sources.

What it actually is

A single LLM family covering two audiences: developers calling the API or self-hosting weights, and consumers chatting at z.ai or chatglm.cn. The model family is optimized for agentic engineering and long-horizon coding, not generalist chat.

GLM-5.1 ships as open weights under MIT on Hugging Face. That combination, MIT license plus frontier SWE-Bench scores, is rare. Most labs at this benchmark tier keep weights closed.

The real moats are the open-weight coding lead and the Huawei Ascend training stack. GLM is the first Chinese frontier model trained without Nvidia, which matters for customers evaluating supply-chain independence. The consumer chat product is secondary to that positioning.

When to pick GLM

• Agentic coding workloads. GLM-5.1’s 58.4% SWE-Bench Pro score is the current open-weight leader, edging past closed frontier models on that specific benchmark.
• Cursor, Cline, or Continue.dev backend swap. GLM supports OpenAI-compatible and Anthropic-compatible API formats. Drop-in replacement against paid Claude or GPT endpoints.
• Self-hosted frontier coding. MIT-licensed weights permit local deployment, fine-tuning, and commercial use without licensing fees.
• Huawei Ascend infrastructure. Enterprises on domestic Chinese compute get a native-stack option that does not require Nvidia.
• Bilingual Chinese-English technical work. Legal, finance, and engineering teams operating across both languages get trained-in-parallel fluency.

When to pick something else

• Cheapest API for general chat: DeepSeek at ~$0.28/M input is 3-4x cheaper than GLM-5.
• Polished English writing: Claude Opus 4.7 or ChatGPT. GLM’s English is functional, not best-in-class.
• Broadest open-weight coverage: Qwen. Apache 2.0 across more sizes, wider language coverage, more active monthly releases.
• Google Workspace integration: Gemini. GLM has no Workspace hooks.
• Consumer-grade product polish: ChatGPT or Claude. Z.ai chat is developer-adjacent, not consumer-first.

Pricing

Subscription pricing via Zhipu AI Open Platform and bigmodel.cn pricing.

Prices verified 2026-04-17 via Zhipu AI Open Platform pricing and Vibecoding pricing breakdown. Zhipu raised GLM prices 30% in February 2026 and another 10% on the GLM-5.1 release.

Against the alternatives

Failure modes

• Price increases at each major release. Zhipu raised API rates 30% at GLM-5 and 10% at GLM-5.1. Cost predictability is lower than at DeepSeek or Qwen.
• Z.ai consumer UX lags. The chat interface is functional in English but built for a Chinese-first audience. Menu labels, error messages, and onboarding trail ChatGPT or Claude.
• Thin competitive moat. SWE-Bench leaderboard positions shift monthly. DeepSeek, Qwen, and Kimi are all active challengers with comparable release cadence.
• API cost undercut by DeepSeek. At $1/M input, GLM-5 is ~3.5x DeepSeek’s rate. The benchmark advantage is coding-specific; on general chat, DeepSeek wins on value.
• Huawei Ascend training is a signal, not a benefit. For most Western developers, it does not change the product. For Chinese enterprises it matters materially.
• Third-party tutorials are thinner. Smaller global developer community than ChatGPT or Claude. Fewer Stack Overflow threads, fewer YouTube walkthroughs.
• Hosted API runs on Chinese infrastructure. Western teams with strict data residency rules cannot use bigmodel.cn. Self-hosted weights are the workaround.

Methodology

This page was produced by the aipedia.wiki editorial pipeline, an automated system that ingests vendor documentation, verifies pricing and model details against primary sources, and generates the editorial analysis you are reading. No individual human wrote this review. Scoring follows the four-dimension rubric at /about/scoring/ (Utility, Value, Moat, Longevity; unweighted average). Last verified 2026-04-17 against GLM-5.1 on Hugging Face, Zhipu AI Open Platform pricing, Modem Guides GLM-5.1 benchmark coverage, and TrendForce price-hike coverage.

FAQ

Is GLM free to use? Partially. GLM-4.7-Flash and GLM-4.5-Flash are free for registered users on the Zhipu AI platform. GLM-5 and GLM-5.1, the SWE-Bench leaders, require either a paid API ($1/M input) or a Coding Plan subscription starting at ~$10/month.

What changed between GLM-5 and GLM-5.1? GLM-5 launched February 11, 2026 as a proprietary API. GLM-5.1 shipped April 7, 2026 with a 10% price increase and full open-source release under MIT license. GLM-5.1 also took the SWE-Bench Pro lead at 58.4%.

Can I use GLM with Cursor or VS Code? Yes. GLM exposes OpenAI-compatible and Anthropic-compatible API formats. Set a custom endpoint in Cursor, Cline, Continue.dev, or any editor that accepts a custom OpenAI endpoint, using your Zhipu API key.

What does “trained on Huawei Ascend” mean in practice? GLM-5 and GLM-5.1 were trained end-to-end on Huawei Ascend 910B chips with the MindSpore framework, with no Nvidia hardware. For most users the output is indistinguishable. For Chinese enterprises and compliance buyers, it is a supply-chain independence signal.

Is GLM faster or slower than Claude or GPT? Inference latency performance varies with regional load.

Sources

• GLM-5 / GLM-5.1 on Hugging Face: open-weight release, MIT license, benchmarks
• Zhipu AI Open Platform pricing: current API and Coding Plan rates
• Modem Guides: GLM-5.1 Open Source: SWE-Bench Pro leaderboard details
• TrendForce: China LLM price jump: 30% price increase at GLM-5 launch
• Lushbinary GLM-5 developer guide: Huawei Ascend training stack
• Z.AI Developer Documentation: API and model reference

Related

• Category: AI Chatbots · AI Coding
• Comparisons: ChatGPT vs GLM

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