LLM API for coding agents that need predictable costs.
Run coding agents, IDE tools, and automation workflows against an OpenAI-compatible LLM API with free testing and flat-rate unlimited access.
Agent-friendly pricing
Flat-rate access handles long sessions better than per-token anxiety.
Tool compatibility
Use clients that support custom OpenAI-compatible endpoints.
No prompt storage
Code, prompts, and responses are not saved as conversation history.
Quick setup
Create an account, copy your yolo_... API key, set your base URL to https://yolo-auto.com/v1, and use a public model from the models page.
Best next pages
Docs · Pricing · Models · Free AI chat · Cheap LLM API
Why coding agents need different pricing
Agents retry, inspect context, generate patches, and sometimes loop. That behavior can be expensive on per-token APIs. Yolo-Auto makes cost easier to predict.
Works with common agent clients
Yolo-Auto provides docs and config examples for compatible tools, plus a standard /v1 endpoint for custom integrations.
Designed for real development
The API is useful for code review helpers, command-line agents, IDE integrations, repo assistants, and automation scripts.
Who LLM API for Coding Agents is actually for
LLM API for Coding Agents is best for developers and power users who want model access inside tools, agents, scripts, and apps — not just a closed consumer chatbot tab.
- Command-line coding agents that read, plan, edit, and retry.
- IDE helpers and internal automation tools.
- Agentic workflows where predictable pricing and prompt privacy matter.
Agents are not normal API consumers
A human chat session is usually linear. An agent session is messy: it inspects files, reasons, retries, summarizes, and may loop while fixing a problem. That usage pattern makes per-token pricing harder to predict.
Yolo-Auto gives agent builders an OpenAI-compatible model backend with no prompt storage and a flat-rate upgrade path when free testing is not enough.
Try LLM API for Coding Agents with a normal chat completion
The fastest test is a single request against the OpenAI-compatible endpoint. Use your real Yolo-Auto API key, then swap the model ID if the models page shows a newer default.
curl
curl https://yolo-auto.com/v1/chat/completions \
-H "Authorization: Bearer yolo_YOUR_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "qwen3.6-35b-a3b",
"messages": [
{ "role": "user", "content": "Plan the next three safe steps for a coding agent working inside a repository." }
]
}'OpenAI SDK style
import OpenAI from "openai";
const client = new OpenAI({
apiKey: process.env.YOLO_AUTO_API_KEY,
baseURL: "https://yolo-auto.com/v1"
});
const response = await client.chat.completions.create({
model: "qwen3.6-35b-a3b",
messages: [{ role: "user", content: "Plan the next three safe steps for a coding agent working inside a repository." }]
});
console.log(response.choices[0]?.message?.content);When to choose Yolo-Auto
You need OpenAI-compatible LLM access, predictable cost, free testing, and no prompt or response storage.
You need image generation, every model under the sun, a managed IDE, or a consumer-only chatbot with no API workflow.
Read the docs, check models, compare pricing, or review the privacy policy.
LLM API for Coding Agents FAQ
Can my coding agent use Yolo-Auto?
If it supports OpenAI-compatible custom endpoints, usually yes.
Do you store my repository prompts?
No. Prompt and response bodies are not stored.
Why not use a per-token API?
You can, but flat-rate access is easier to budget for long agent runs.
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