# Zhipu Qingyan (ChatGLM) vs Cursor

Zhipu Qingyan (ChatGLM) records 5,119,422 monthly visits with -3.9% month-over-month growth and Freemium, Free pricing. Cursor records 23,297,751 monthly visits with +8.4% growth and Freemium pricing.

| Metric | [Zhipu Qingyan (ChatGLM)](https://openaitools.app/tool/chatglm-cn) | [Cursor](https://openaitools.app/tool/cursor) |
| :--- | :--- | :--- |
| Website URL | https://chatglm.cn | https://www.cursor.com |
| Categories | AI Chatbot, Large Language Models (LLMs), AI Image Generator, AI Video Generator | AI Code Assistant, AI Developer Tools, AI Agent |
| Pricing Model | Freemium, Free | Freemium |
| Monthly Visits | 5,119,422 | 23,297,751 |
| MoM Growth Rate | -3.9% | +8.4% |
| Primary Market | China | United States |
| Direct Visits | 4,066,967 | 14,683,770 |
| Review Score | 4.6 | 4.7 |
| Saved Count | 3 | 29 |
| Supported Platforms | Website | Website |

## Zhipu Qingyan (ChatGLM)

Zhipu Qingyan — often referred to internationally as ChatGLM — is Zhipu AI's consumer-facing AI workspace at chatglm.cn. It runs on the company's GLM large model family and presents itself not just as a chatbot but as an agent that understands a goal, breaks it into steps, calls the right tools and hands back a deliverable rather than a wall of text.

The platform bundles a wide range of capabilities into one account: conversational dialogue and web search, AI image and video generation, slide creation, document and data analysis, code assistance and voice interaction. Because Zhipu also publishes open-weight GLM models, the same underlying research shows up both in this hosted product and in developer-facing APIs.

The interface is primarily Chinese and tuned for Chinese-language tasks and domestic content, which makes it a strong fit for users working in that context. A free tier covers everyday chat and basic tools, with paid tiers for higher quotas and advanced models.

**Pricing & Plans:** Freemium with a free tier for everyday chat and standard tools, plus paid subscription tiers for higher limits and advanced model access.

- **Agentic task execution:** Describe an objective and the assistant plans steps, invokes tools and produces an actual deliverable rather than just advice.
- **Multimodal creation:** Generate images, short videos, presentations and written content from prompts inside the same workspace.
- **Web search and reading:** Pull in live search results and summarize long documents or pages to ground answers in current information.
- **Code and data assistance:** Get help writing code and analyzing datasets, useful for developers and analysts alike.
- **GLM model foundation:** Powered by Zhipu's in-house GLM models, the same research family also released as open-weight models for developers.

**Strengths:** Broad toolbox in one account: chat, search, image, video, slides and analysis; Strong Chinese-language understanding and locally relevant content; Free tier covers most everyday usage; Backed by Zhipu's own GLM model research

**Limitations:** Interface and content are primarily Chinese, which limits non-Chinese users; Advanced models and higher quotas require a paid plan; Some features are region-specific and may not work everywhere

[Profile (Markdown)](https://openaitools.app/tool/chatglm-cn.md)

## Cursor

Cursor's editor looks familiar to anyone who has used a modern IDE, but the center of gravity is the agent. Instead of only suggesting the next line, it can read a task description, inspect the repository, produce an implementation plan, modify many files, run commands, and report back with a summary of what changed. Developers keep control by approving plans, reviewing diffs, and stepping in wherever judgment is needed.

The product has expanded well beyond a single application. Cloud agents can run on their own machines for extended periods, Cursor ships a CLI, and integrations bring the same agent into Slack and GitHub so work can be handed off without switching tools. A model picker lets you use frontier models from several providers, or rely on automatic selection per task.

This makes Cursor a good fit for teams that want measurable velocity gains on large codebases while keeping human review in the loop. The trade-offs are mostly about cost and process: capable agents consume quota, remote indexing raises questions for security-conscious organizations, and teams need light conventions for when to delegate versus write code directly.

**Pricing & Plans:** Cursor uses a freemium model: you can start for free with limited usage, then move to paid Pro, team, and enterprise tiers that unlock higher model limits, cloud agents, and administrative controls. Exact seats and credit allowances change over time, so check cursor.com/pricing for current numbers.

- **Agent-driven code changes:** An agentic mode that plans changes, edits several files at once, runs tests, and iterates until the task is complete.
- **Cloud and parallel agents:** Background agents spin up their own environments to build, test, and demo features in parallel, then hand back results for review.
- **Tab completion and codebase context:** Fast inline suggestions plus codebase-wide semantic search and indexing so answers reflect your actual repository.
- **Multi-model flexibility:** Switch between leading frontier models from multiple providers, or let Cursor select a model automatically for each task.
- **CLI, Slack and GitHub workflows:** Run Cursor from the terminal, chat with it in Slack, and let it review or open pull requests in GitHub without leaving your workflow.

**Strengths:** Strong repository-wide context and multi-file edits; Agent runs in the editor, cloud, CLI, Slack, and GitHub; Choose from multiple frontier models in one place; Familiar IDE experience for developers coming from other editors

**Limitations:** Requires a paid plan for the most capable models and higher usage; Learning curve to use agentic workflows effectively; Heavy cloud agent usage can consume plan quota quickly; Codebase indexing sends code to remote services, which some compliance teams must review

[Profile (Markdown)](https://openaitools.app/tool/cursor.md)

## Frequently Asked Questions

### How do Zhipu Qingyan (ChatGLM) and Cursor compare in monthly traffic?

Zhipu Qingyan (ChatGLM) has 5,119,422 monthly visits, while Cursor has 23,297,751. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

Zhipu Qingyan (ChatGLM) has a month-over-month growth rate of -3.9%; Cursor has +8.4%.

### How does pricing compare?

Zhipu Qingyan (ChatGLM): Freemium, Free. Freemium with a free tier for everyday chat and standard tools, plus paid subscription tiers for higher limits and advanced model access. Cursor: Freemium. Cursor uses a freemium model: you can start for free with limited usage, then move to paid Pro, team, and enterprise tiers that unlock higher model limits, cloud agents, and administrative controls. Exact seats and credit allowances change over time, so check cursor.com/pricing for current numbers.

## Alternatives

| # | Tool Name | Monthly Visits | MoM Growth Rate | Pricing Model | Summary | Profile (Markdown) |
| :--- | :--- | :--- | :--- | :--- | :--- | :--- |
| 1 | [Character.AI](https://openaitools.app/tool/character-ai) | 154,156,370 | +2.2% | Freemium | Provides engaging conversational roleplay with custom characters, but is not designed for general Chinese search and productivity tasks. | [.md](https://openaitools.app/tool/character-ai.md) |
| 2 | [Venice AI](https://openaitools.app/tool/venice-ai) | 25,088,401 | +23.8% | Freemium | Prioritizes private open-source text and image generation with developer APIs, but lacks consumer-focused Chinese assistant workflows. | [.md](https://openaitools.app/tool/venice-ai.md) |
| 3 | [Google Antigravity](https://openaitools.app/tool/google-antigravity) | 16,054,109 | +8.1% | Freemium | Provides powerful parallel AI coding agents via a desktop command center, but is less integrated into a traditional editor. | [.md](https://openaitools.app/tool/google-antigravity.md) |
| 4 | [OpenArt](https://openaitools.app/tool/openart) | 12,394,629 | +15.8% | Freemium, Free Trial | Specializes in diverse third-party image and video generation models, but offers less robust general conversational capabilities than ChatGLM. | [.md](https://openaitools.app/tool/openart.md) |
| 5 | [Replit](https://openaitools.app/tool/replit) | 10,016,437 | -7.7% | Freemium, Paid | Enables instant cloud-based full-stack app building from natural language, but is less suited for local offline repositories. | [.md](https://openaitools.app/tool/replit.md) |
| 6 | [DeepAI](https://openaitools.app/tool/deepai-org) | 8,407,615 | +0.9% | Freemium | Offers versatile multi-modal generation tools in the browser, but lacks deep conversational Chinese language assistance capabilities. | [.md](https://openaitools.app/tool/deepai-org.md) |
| 7 | [VS Code](https://openaitools.app/tool/vs-code) | 7,397,370 | -3.8% | Freemium | Offers unmatched extension support and official Copilot integration, but lacks Cursor's out-of-the-box deep codebase indexing and agentic editing. | [.md](https://openaitools.app/tool/vs-code.md) |
| 8 | [Qoder](https://openaitools.app/tool/qoder) | 5,145,040 | +81.8% | Freemium, Free Trial, Free | Features advanced multi-file planning and codebase reading, but lacks Cursor's smooth chat-to-edit inline workflows. | [.md](https://openaitools.app/tool/qoder.md) |
| 9 | [Kiro](https://openaitools.app/tool/kiro) | 3,330,476 | +4.6% | Freemium | Focuses on spec-driven engineering and structured agent planning, but offers less fluid ad-hoc inline code generation than Cursor. | [.md](https://openaitools.app/tool/kiro.md) |
| 10 | [Devin](https://openaitools.app/tool/devin) | 2,549,346 | +1% | Paid | Operates as a fully autonomous software engineer for complex tasks, but lacks the snappy interactive inline editing of Cursor. | [.md](https://openaitools.app/tool/devin.md) |

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Source: https://openaitools.app/compare/chatglm-cn-vs-cursor

More Markdown: [Categories](https://openaitools.app/categories.md) · [Traffic rankings](https://openaitools.app/rankings.md) · [llms.txt](https://openaitools.app/llms.txt)