Cursor, Cline, Roo Code on a third-party model: one config matrix

The short answer

All three can be pointed at the same model. They differ in three ways:

One line to tell them apart: Cursor is AI built into the IDE; Cline and Roo Code are agents that live inside your editor. The first competes with you for the editor; the second does the work for you inside it.

The config matrix

All three take the same three values:

• Base URL: https://api.kimiseek.app/v1
• API key: your ks- key
• Model ID: the full catalog id, e.g. deepseek-v4-pro-0813

Note the /v1 in the Base URL — all three append /chat/completions themselves.

Cursor

1. Open Settings and go to the Models panel.
2. Enter your OpenAI API key and enable Override OpenAI Base URL, set to https://api.kimiseek.app/v1.
3. With the override enabled, Cursor treats custom models as OpenAI-compatible, which means you add the model name manually.
4. Save, start a new chat, and ask which model it is to confirm the link.

Cursor's trap is the model name. It ships a built-in list, and names outside it sometimes save without taking effect. If the settings save but nothing answers, try a conventionally named id first.

Cline

1. Open Settings in the Cline panel.
2. Set API Provider to OpenAI Compatible.
3. Base URL https://api.kimiseek.app/v1, API key your ks- key.
4. Model ID deepseek-v4-pro-0813.
5. Save and send a message to verify.

Cline's trap is context length. It infers the context window from the model name and falls back to a conservative number when it does not recognise it — commonly 128K, sometimes 64K. So you have 1M available and the client truncates early. There are community issues on exactly this. If a task reports running out of context halfway, raise it in the settings first rather than doubting the model.

Roo Code

Roo Code is a Cline fork with the same steps:

1. API Provider: OpenAI Compatible.
2. Base URL, API key and Model ID as above.
3. Set the context window and max output tokens manually in the model config.

What Roo adds is per-mode model selection (Code, Architect, Ask and so on). Point the light modes at deepseek-v4.1-flash to save money.

The two problems nobody avoids

A hardcoded context window

All three share this one. The symptom: "the model supports 1M, but the client cuts off at 128K".

The cause is structural. The client needs to know the context length to decide when to compress history, and most clients match the model name against a built-in table, falling back to a conservative default.

Fix it by setting it explicitly. Cline and Roo Code both allow it in settings; Cursor infers from the name, so pick a model name whose documented context is larger and then override the endpoint.

Incompatible tool-call formats

An agent works by calling tools: read a file, write a file, run a command. Different models format those calls slightly differently, and the gateway is responsible for normalising them.

The failure is not an error message. It is "the model said it edited the file, but edited the wrong one" or "it keeps reading the same file". When that happens, confirm you are on the native protocol path, then try a different model — tool-call quality varies a lot, and reasoning models are usually steadier.

Verification checklist

Check in this order:

1. Ordinary question gets an answer → auth and network are fine.
2. Ask it to read a file → tool calls work.
3. Ask it to edit a file → write access and diffs work.
4. Ask it to run a test command → the execution loop works.

If a step fails, see the error reference.

When to switch tools

• Completion and single-file edits → Cursor is enough, and lighter.
• Cross-file refactors with a test loop → Cline or Roo Code, which are built for multi-step work.
• Long tasks in a terminal → Claude Code or Codex.

Versions and verification

• Cursor 1.x, Cline 3.x, Roo Code 3.x
• Verified: 2026-10-26
• Sources: each tool's official settings documentation and actual UI fields; the context-window issue is documented in community issue threads