Cline is what most people mean when they say "a coding agent inside VS Code". It reads your files, runs commands, edits code, asks before doing anything destructive, and it has a property the hosted agents do not: the model is a setting. Pick "OpenAI Compatible" as the provider, paste a base URL and a key, and Cline runs on whatever is behind that URL.
That is exactly the shape of the ParalonCloud inference API: an OpenAI-compatible endpoint serving open models. Cline plus ParalonCloud is a full agentic coding loop with no Anthropic or OpenAI account anywhere in the stack, on a prepaid key that costs cents. Here is the whole setup, every field, for the VS Code and JetBrains extensions and for the CLI.
1. Install Cline
- VS Code: Extensions, search Cline, install. The Cline icon appears in the activity bar.
- JetBrains (IntelliJ, PyCharm, WebStorm, GoLand, …): Plugins marketplace, search Cline, install.
- CLI, for the terminal or CI:
npm i -g cline
2. Get a key and ask the API what it serves
Create a key in the Console: sign in, API keys, Create
key, copy the prlc_ token. A free key comes with a 100,000-token trial,
no card. Then list the models rather than guessing IDs:
curl -s https://paraloncloud.com/v1/models \
-H "Authorization: Bearer prlc_your_api_key" | python3 -m json.tool
{
"data": [
{ "id": "qwen3.8-27b", "name": "Qwen 3.8 27B (Vision)", "max_context": 32768, "supports_vision": true }
]
}
The id is what goes into Cline.
3. Configure the provider in the extension
Open Cline, click the settings gear, and fill in:
| Field | Value |
|---|---|
| API Provider | OpenAI Compatible |
| Base URL | https://paraloncloud.com/v1 |
| API Key | your prlc_… key |
| Model | qwen3.8-27b |
Then expand Model Configuration. Cline cannot ask an arbitrary endpoint what the model can do, so you tell it, and these values change how it behaves:
| Model Configuration | Value | Why |
|---|---|---|
| Context Window size | 32768 | Cline uses this to decide when to condense the conversation. Set it higher than the model allows and requests start failing with a context error instead of being condensed. |
| Max Output Tokens | 8192 | Enough for a large file rewrite in one go. |
| Image Support | on | Qwen 3.8 27B accepts images; Cline can then read screenshots you paste. |
| Computer Use | off | Browser control; leave it off unless you want Cline driving a browser. |
| Input Price / Output Price | 0.12 / 1.70 per million | Only used for Cline's cost display; the list price. |
Leave Use Azure Identity Authentication unchecked. Save, and the next message you send goes through ParalonCloud.
4. Plan and Act
Cline has two modes. Plan reads the codebase, searches, and discusses an approach without touching a file. Act executes it, with the conversation carried over. The toggle is at the bottom of the chat.
There is a setting, Use different models for Plan and Act, that switches model automatically when you switch mode. With a single model behind the API, leave it off. If you later have a stronger reasoning model on the same key, this is where you put it on Plan and keep the fast one on Act.
5. The CLI
The same configuration works from the terminal. Run the setup once:
cline auth
Choose your own provider, give it the base URL, the key and the model as
above. The configuration lands in ~/.cline/data/settings/providers.json;
cline config shows what is set, cline doctor checks it. Then:
# interactive
cline
# one task, from the shell
cline "add input validation to the signup handler and write a test for it"
# plan first, act after you approve
cline -p "migrate the config loader from JSON to TOML"
# machine-readable, for scripts and CI
cline --json "list every TODO comment with its file and line"
One flag to know: --auto-approve defaults to true in the CLI, so Cline
edits and runs commands without asking. In a repo you care about, start
with --auto-approve false until you trust the loop.
What a session costs
This is the part the other guides skip. A coding agent is not a chat: every turn resends its system prompt, the tool definitions and the whole conversation so far. Cline's system prompt alone is on the order of ten thousand tokens. A twenty-turn task with a 20k-token working set is about 400,000 input tokens.
At the list price that is $0.05 of input plus a few cents of output. The 100k-token free trial is enough to confirm the setup and finish one small task; for daily use you top up from $5 in Add Credits and create a premium key. Billing is per token, settled the moment a response completes, and the Console shows spend per key.
Why Qwen 3.8 27B behind it
Cline drives its tools through the model's replies, so what matters is
whether the model follows the tool protocol reliably turn after turn, and
whether it holds enough context to keep a working set of files in view.
Qwen 3.8 27B does both, with a 32k context on the standard workers. It is
served on consumer and pro GPUs across the network; where a node has the
room, the same model runs with a longer context, and long prompts are
routed to those nodes automatically. Check what is live anytime via
/v1/models.
Troubleshooting
| Symptom | Fix |
|---|---|
| 401 Unauthorized | wrong or revoked key; rotate it in the Console |
| 404 model not found | the Model field must match an id from /v1/models exactly |
| "context length exceeded" from the API | Context Window size is set above what the model allows; set it to 32768 |
402 with free_quota_exhausted | the free trial is used up; top up and create a premium key |
429 with Retry-After | every worker for the model is busy; Cline retries on its own |
| Responses cut off mid-file | raise Max Output Tokens |
| Cline says the model does not support images | turn Image Support on in Model Configuration |
The recipe is the same for any OpenAI-compatible backend, a vLLM box in the office included: swap the base URL, the key and the model ID. If you would rather not run GPUs at all, the endpoint above is live, and your coding agent runs on the open cloud. The same setup for pi, the terminal coding agent, is in an earlier post.
