These three tools get compared as if they are the same product. They are not. They are three different bets about how you want to work and, more importantly, about where your code goes when an AI reads it. That second question is the one that should decide your choice, and for a business it sits next to a second one: what each seat costs.
We have run all three here, along with the other open-source agents people put on the same shortlist: Aider, Cline and OpenHands. Here is the honest read.
What are OpenCode, Pi, and Cursor?
- Cursor is a closed, paid, cloud desktop app. A polished fork of VS Code with an agent built in. The most refined experience, and the one that sends your code to someone else’s servers.
- Pi is an open, terminal-first agent for people who live in the shell and want an extensible agent they can shape.
- OpenCode is an open desktop app (with optional CLI and IDE modes) that can point at a cloud model or a model on your own machine. The open answer to Cursor’s experience.
Where do Aider, Cline and OpenHands fit?
If your shortlist is open-source agents only, three more names come up, and each one answers a different question about where you want to work.
- Aider is the terminal-first one: a mature, git-aware pair programmer you drive from the shell. It proposes, you approve, it commits.
- Cline is the VS Code one: the same agentic loop inside your editor, where every file open and every diff is visible in a side panel.
- OpenHands is the sandbox one: an autonomous engineer running in a Docker container that can build whole tasks end to end with minimal supervision.
Two questions sit underneath the feature lists. The first is location. Aider lives in your terminal, Cline lives in VS Code, OpenCode lives in its own app window, and OpenHands lives in a browser tab pointed at a Docker container. None of these is better in the abstract. They are better for different people in different chairs.
The second is autonomy, and most comparisons skip it. Aider and Cline are collaborative by design: they propose a change, you approve it, then they act. That rhythm keeps you in the loop on every edit. OpenCode follows the same approval-based shape. OpenHands is the outlier. It runs in a sandbox and can complete an entire multi-step task with very little supervision, which means more power, less oversight and a heavier setup to match.
Which coding agent keeps your code private?
Strip away the feature lists and one decision sits underneath everything: does your code leave your machine?
With Cursor, it does. That is not a flaw, it is the design. The quality comes partly from routing your context to strong cloud models. If your work is not sensitive and you want the smoothest agent on the market, that trade can be worth it.
With OpenCode pointed at a local model through Ollama, your code does not leave the building. Same agentic behavior, same “read files, edit, run commands” loop, zero cloud calls. The ceiling is your local model rather than a frontier cloud model, but for most day-to-day work that ceiling is high enough.
Pi sits where you put it. Point it at a local model and it is private; point it at a cloud API and it is not. It gives you the control, and the responsibility.
Aider, Cline and OpenHands are model-agnostic too, and each can point at a local model through Ollama, which keeps your code on your machine. OpenHands carries one caution: it mounts the Docker socket, so its container can spawn other containers on your host. That is a real security consideration, and a reason not to feed it untrusted prompts. The other agents here carry no comparable risk.
There is a simple way to make this concrete. Open the tool, give it a task, and watch your network indicator. With OpenCode on a local model it stays at zero; with Cursor it lights up the moment the agent reads your files, because reading them means sending them. Neither is wrong, but only one of them lets you prove where your code went.
How do OpenCode, Pi, and Cursor compare?
Where you work. Cursor is an editor you live inside. Pi is a terminal you drive. OpenCode is a normal app window you open, and it also offers CLI and editor modes if you want them. If “we do not want to learn another shell tool” describes you, OpenCode and Cursor are the candidates and Pi is not.
Setup cost. Cursor: download, sign in, pay. OpenCode: download, pick a provider, done; add Ollama if you want it local. Pi: comfortable if you already work in a terminal, more friction if you do not.
Privacy. OpenCode (local) and Pi (local) keep code on your machine. Cursor does not. This is the cleanest line between them.
Cost. Cursor is a monthly subscription. OpenCode and Pi are free and open source; your only cost is the hardware you already own, or a cloud API you opt into per task.
Quality ceiling. Cursor, riding frontier cloud models, has the highest ceiling on the hardest problems. OpenCode and Pi inherit whatever model you point them at. On a strong local coding model they are very capable; on the hardest tasks a frontier cloud model still pulls ahead.
Extensibility. Pi is the most shapeable for people who want to build their own workflows around the agent. OpenCode leans on its app polish and its LSP-aware reading of your code. Cursor is the most finished but the least open.
Lock-in. Cursor ties you to its app and its billing; cancel and the agent goes with it. OpenCode and Pi are open source, so the tool itself cannot be taken away, and the model is a file you already hold. For anything you intend to depend on for years, that difference outlasts any feature gap.
How do the open-source agents compare with each other?
Setup cost runs from light to heavy. OpenCode is the lightest: download the app, pick a provider, type. Cline is nearly as easy if you already run VS Code, since it is just an extension. Aider is one pip install and a git repo, comfortable if the terminal is home. OpenHands is the heaviest by a wide margin. It needs Docker Desktop with real memory allocated, and a sandbox image alongside the main one. That setup buys autonomy, but it is setup.
Visibility is where Cline leads. It opens files in tabs, shows diffs with approve and reject buttons, and surfaces every command before it runs. That is the whole reason it exists, and it is why it shows so well in a demo. Aider shows its work too, but as terminal output rather than a live editor. OpenHands shows a file pane and a terminal pane as it works. OpenCode shows the work in its app window.
Git is Aider’s strength. It expects a repo, and it commits changes with clean, descriptive messages by default. If your mental model of “AI did work” is “there is now a tidy commit in the log,” Aider fits that instinct best.
The model is the ceiling for every one of them. A weak model makes a weak agent regardless of the wrapper. The agentic loop of read, propose and edit exposes a model’s limits fast, especially in Cline and OpenHands where steps stack up. Locally, reach for a strong coder model in the 32B class.
Which coding agent should you pick?
Pick Cursor if your code is not sensitive, you want the single most polished agent available, and a monthly bill is fine. You are buying refinement and a frontier ceiling, and paying with a subscription and your code leaving your machine.
Pick OpenCode if you want an agent in a normal app window, you care that your code stays on your laptop, and you would rather not pay monthly. Wire it to Ollama and you have Cursor’s shape with a local model underneath. It is the only one of the open agents here that ships as a double-click desktop app. This is the one we reach for most.
Pick Pi if you live in the terminal, you want maximum control, and you intend to extend the agent rather than just use it. Pi moves quickly: version 0.85.1 added GPT-6 Astra two days after OpenAI’s launch.
When does Aider, Cline or OpenHands make more sense?
Pick Aider if you live in the terminal, you work in git, and you want a mature, precise pair programmer that commits its work cleanly. It is the production developer’s choice when in-editor completion is not enough and full autonomy is too much.
Pick Cline if you live in VS Code and you want to see the agent work. Watching files open and diffs appear, approving each step, is the value. It is also the friendliest to show a client or a less terminal-comfortable teammate.
Pick OpenHands if you want maximum autonomy and the sight of an AI building a working app from a single prompt, and you are willing to run Docker to get it. It suits exploration and demos more than careful day-to-day work.
What does OpenCode vs Cursor cost a 10-person team?
Cursor’s published price, read on 17 October 2026, lists its Teams plan at $30 or more per user per month. Ten developers on it cost at least $300 a month, or $3,600 a year (10 seats at $30, times 12). OpenCode and Pi have no licence fee. Their cost is the hardware, and on a local model the hardware decides the quality ceiling, so a team that already runs 16GB laptops should test what a model of that size does on its own code before it cancels anything.
Cursor’s published plan terms say privacy mode “can be enabled in settings or by a team admin”, and that with it on, code data is not used for training by Cursor or its model providers. That is a promise about training. It does not keep code on your machine, because the agent still sends what it reads to the cloud to answer. A business with client code under contract, or with a rule that source must not leave its own machines, gets the guarantee it needs only from OpenCode or Pi pointed at a local model.
A mixed setup is common and reasonable. Keep a few Cursor seats for the people whose work is not sensitive and who hit the hardest problems, and put everyone else on OpenCode with a local model. The bill then scales with the seats that need a frontier model, not with headcount.
How should a team test the agents on a real repo?
We have not run Aider, Cline, OpenCode and OpenHands on the same task in the same repository at the same commit with the same local model on our test machine, so we have no wall-clock times, intervention counts, discarded changes or token costs to publish, and the choice above rests on where each agent works rather than on a timed result. That run is on our list.
A team can run that test in a day. Use one real task from your backlog, small enough to finish in a session and with a test that proves it is done. Give each agent a fresh checkout at the same commit, the same model and the same written instructions. Record the wall-clock time from first prompt to passing test, how often a person had to step in, and every change that had to be thrown away. Run each agent more than once, because the same model can take a different path through the same task.
When the agents share one local model, the model costs the same for each, so time is where they differ, and the agent’s own prompt is part of that time. OpenCode’s system prompt measured about 51,700 tokens on our machine, as recorded in agent skills vs MCP servers, and Gemma 4 31B processed cold prompts at about 65 tokens a second on our test machine, an M4 Pro with 48 GB of memory, as measured in agent system prompt tokens. On those figures the first request of a session waits about 13 minutes before the first token (51,700 / 65 = 795 seconds). After that the cached prefix is reused, so the wait is paid once per session, not once per turn. We have not measured the other agents’ prompts, so we cannot say which starts sooner.
If the agents will use a paid cloud model instead, add the provider’s published token prices to each run’s record. The comparison then becomes cost per finished task, which is the figure a team budget needs.
Which do we actually run?
OpenCode pointed at Ollama, with glm-4.7-flash as the model, is the setup we recommend for most teams. The reason is not a benchmark. The privacy story is intact, the bill is zero, and it opens like an app instead of demanding a terminal or a Docker container. When a task is genuinely hard, OpenCode can switch to a cloud provider for that one job and switch straight back, so the default stays local. It is also the one to hand to people who will never open a terminal.
The other open agents each have a job. Aider suits terminal work such as refactors, scripting and custom tools, and its git-aware commits and architect-then-code split make it clear what is about to change. Cline is the one to pick when you want to watch an agent work, or when someone less at home in a terminal wants to take part. OpenHands makes the point fastest when someone needs to see what autonomous AI looks like, but for day-to-day precision Aider or Cline is the better choice.
That is the honest hierarchy: Cursor is the most polished and the least private, Pi is the most controllable and the least approachable, and OpenCode is the one that gives most people the best of both, an app you open, running a model you own. Among the other open agents, Aider is the most precise, Cline the most watchable and OpenHands the most autonomous.
The gap that used to justify the cloud option keeps narrowing. As local coding models improve, the main reason to send your code away, raw capability, shrinks, while the reasons to keep it home, privacy, cost, and control, stay exactly where they are.
We do not tell you which to use. You watch the work, you make your own call. But if your code is worth keeping on your own machine, that should weigh more than a feature checklist.
