# Cursor vs stagewise

Cursor records 23,297,751 monthly visits with +8.4% month-over-month growth and Freemium pricing. stagewise records 1,110 monthly visits with -73% growth and Free, Enterprise (contact for pricing) pricing.

| Metric | [Cursor](https://openaitools.app/tool/cursor) | [stagewise](https://openaitools.app/tool/stagewise) |
| :--- | :--- | :--- |
| Website URL | https://www.cursor.com | https://stagewise.io |
| Categories | AI Code Assistant, AI Developer Tools, AI Agent | AI Agent, AI Developer Tools, AI Code Assistant, AI Design Assistant |
| Pricing Model | Freemium | Free, Enterprise (contact for pricing) |
| Monthly Visits | 23,297,751 | 1,110 |
| MoM Growth Rate | +8.4% | -73% |
| Primary Market | United States | Italy |
| Direct Visits | 14,683,770 | 430 |
| Review Score | 4.7 | 4.4 |
| Saved Count | 29 | 0 |
| Supported Platforms | Website | Website |

## 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)

## stagewise

stagewise describes itself as a next-gen agent orchestrator rather than a simple autocomplete plugin. The core idea is "model sovereignty": you choose the model behind every agent, whether that is a frontier model such as Claude, GPT or Gemini, an open-weight model like DeepSeek, Qwen, GLM, Kimi or MiniMax, or something running locally through Ollama, vLLM or llama.cpp. The IDE ships with an optional cloud inference layer so you can start without any API keys, but you can swap in your own keys or a custom endpoint at any time.

The engineering focus is on running agents for long stretches without burning through tokens. stagewise keeps the conversation prefix stable between turns to maximize prompt cache hits and sends a compact state delta when the environment changes instead of rebuilding the whole context. It also compresses context automatically as a task grows, which keeps agents aware of terminal output and browser state at a fraction of the usual cost. The site advertises an average cache hit rate of roughly 87%.

The codebase is published under AGPLv3 on GitHub, the company is stagewise GmbH and is backed by Y Combinator, and an enterprise offering is available for teams that need to run stagewise on their own infrastructure with their own models. The team has also announced Klex Bots, a related product aimed at end-to-end coding tasks from planning through to a merged pull request.

**Pricing & Plans:** The stagewise agentic IDE is open source and free to use (AGPLv3), with an optional hosted account that provides preconfigured cloud inference access without your own API keys. You can also bring your own provider keys or a custom endpoint. Enterprise pricing is quoted on request for on-premises or self-hosted deployments.

- **Parallel multi-agent orchestration:** Run several agents at the same time, each independently implementing a feature or fixing a bug, from a single command center.
- **Full model sovereignty:** Point each agent at frontier APIs, open-weight models or local inference through Ollama, vLLM and llama.cpp, as long as the provider speaks a compatible API.
- **Cache-optimized runtime:** A stable conversation prefix and compact state deltas keep prompt cache hit rates high, making long-running agent sessions considerably cheaper.
- **Bring your own subscription:** Connect existing coding subscriptions and providers such as OpenAI, Anthropic, Google Gemini, DeepSeek, Kimi, Qwen and MiniMax, or use an aggregator.
- **Open source and self-hostable:** The full AGPLv3 codebase is on GitHub, and enterprises can run stagewise on their own infrastructure with their own model endpoints.

**Strengths:** Free and open source under AGPLv3, with the code publicly available; Genuine model choice, including local and open-weight models, not a single-vendor lock-in; Deliberate engineering for token efficiency on long-running agent tasks; Backed by Y Combinator and offering an enterprise deployment path

**Limitations:** Aimed at developers — non-technical users will find the setup heavy; Local model use depends on your own hardware, which gets expensive at scale; Requires a reasonably large context window (around 150k tokens recommended) for good results

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

## Frequently Asked Questions

### How do Cursor and stagewise compare in monthly traffic?

Cursor has 23,297,751 monthly visits, while stagewise has 1,110. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

Cursor has a month-over-month growth rate of +8.4%; stagewise has -73%.

### How does pricing compare?

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. stagewise: Free, Enterprise (contact for pricing). The stagewise agentic IDE is open source and free to use (AGPLv3), with an optional hosted account that provides preconfigured cloud inference access without your own API keys. You can also bring your own provider keys or a custom endpoint. Enterprise pricing is quoted on request for on-premises or self-hosted deployments.

## Alternatives

| # | Tool Name | Monthly Visits | MoM Growth Rate | Pricing Model | Summary | Profile (Markdown) |
| :--- | :--- | :--- | :--- | :--- | :--- | :--- |
| 1 | [Google Antigravity](https://openaitools.app/tool/google-antigravity) | 16,054,109 | +8.1% | Freemium | Google's agent-first development platform for building and shipping software with AI agents | [.md](https://openaitools.app/tool/google-antigravity.md) |
| 2 | [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) |
| 3 | [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) |
| 4 | [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) |
| 5 | [Kiro](https://openaitools.app/tool/kiro) | 3,330,476 | +4.6% | Freemium | A spec-driven AI IDE and agent platform that plans, builds, reviews, and verifies real engineering work. | [.md](https://openaitools.app/tool/kiro.md) |
| 6 | [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) |
| 7 | [Command Code](https://openaitools.app/tool/command-code) | 2,358,177 | -12.1% | Freemium, Contact for Pricing | The coding agent that learns your coding taste | [.md](https://openaitools.app/tool/command-code.md) |
| 8 | [Orca](https://openaitools.app/tool/orca) | 1,025,891 | +1% | Free, Open Source, Enterprise on request | Run many coding agents in parallel, each in its own worktree | [.md](https://openaitools.app/tool/orca.md) |
| 9 | [Trae](https://openaitools.app/tool/trae) | 702,366 | -7.8% | Freemium | An AI IDE and coding agent that works on your project, not just your cursor | [.md](https://openaitools.app/tool/trae.md) |
| 10 | [Warp](https://openaitools.app/tool/warp-ai) | 657,372 | -9.3% | Freemium, Contact for Pricing | AI-powered terminal and agentic software factory for development teams | [.md](https://openaitools.app/tool/warp-ai.md) |

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Source: https://openaitools.app/compare/cursor-vs-stagewise

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