两行代码即可接入。

快速开始

curl https://cheapllm.shop/v1/chat/completions \
  -H "Authorization: Bearer $CHEAPLLM_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "deepseek-v4.1-flash-1017",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'

在 Windows 上，使用 PowerShell：

Invoke-RestMethod -Method Post -Uri "https://cheapllm.shop/v1/chat/completions" `
  -Headers @{ Authorization = "Bearer $env:CHEAPLLM_API_KEY" } -ContentType "application/json" `
  -Body '{"model": "deepseek-v4.1-flash-1017", "messages": [{"role": "user", "content": "Hello!"}]}'

Python

from openai import OpenAI

client = OpenAI(base_url="https://cheapllm.shop/v1", api_key="sk-cheap-...")

resp = client.chat.completions.create(
    model="deepseek-v4.1-flash-1017",
    messages=[{"role": "user", "content": "Hello!"}],
)
print(resp.choices[0].message.content)

Node / TypeScript

import OpenAI from "openai";

const client = new OpenAI({ baseURL: "https://cheapllm.shop/v1", apiKey: process.env.CHEAPLLM_API_KEY });

const resp = await client.chat.completions.create({
  model: "deepseek-v4.1-flash-1017",
  messages: [{ role: "user", content: "Hello!" }],
});
console.log(resp.choices[0].message.content);

无需 SDK，直接使用 fetch

const r = await fetch("https://cheapllm.shop/v1/chat/completions", {
  method: "POST",
  headers: { "Authorization": `Bearer ${KEY}`, "Content-Type": "application/json" },
  body: JSON.stringify({ model: "deepseek-v4.1-flash-1017", messages: [{ role: "user", content: "Hello!" }] }),
});
const data = await r.json();

密钥

将你的 key 作为 Authorization: Bearer sk-cheap-... 发送。x-api-key 请求头同样可用，适用于使用它的客户端。

• 在 dashboard 中最多创建 25 个 key，每个应用或每位队友一个。
• key 仅在创建时显示一次。我们只存储指纹。
• 撤销将在下一次请求时生效。
• CORS 已开放，因此浏览器应用可以直接调用 API。不过不要在公开网页中携带 key；任何人都能读取它。

聊天补全

POST /v1/chat/completions 接受与 OpenAI 端点相同的请求体。最常用的字段：

响应携带一个 usage 对象，包含 prompt_tokens 和 completion_tokens，以及一个 x-request-id 请求头，如果你联系我们时值得引用。

上下文窗口： tokens。

流式传输

使用 "stream": true 时你会得到 text/event-stream：每个分块一行 data: {...}，以及最后的 data: [DONE]。添加 "stream_options": {"include_usage": true} 可获得包含 token 计数的最后一个分块。

stream = client.chat.completions.create(
    model="deepseek-v4.1-flash-1017",
    messages=[{"role": "user", "content": "Count to five, slowly."}],
    stream=True,
    stream_options={"include_usage": True},
)
for chunk in stream:
    if chunk.choices:
        print(chunk.choices[0].delta.content or "", end="", flush=True)
    elif chunk.usage:
        print("\n", chunk.usage)

关闭连接会停止生成，因此取消的请求不再消耗时间。

推理

模型在回答前会思考。思考内容与回答分开到达，因此绝不会污染你的输出：

模型

GET /v1/models 列出可用的模型。目前只有一个模型：

{"object": "list", "data": [{"id": "deepseek-v4.1-flash-1017", "object": "model", "owned_by": "cheapllm"}]}

Model names containing deepseek are routed to it too, so tools with a hard-coded DeepSeek model name just work.

Limits

Free tier

During the beta every account is free, with no rate limit. When the beta ends, every account keeps a permanent free tier, with no card: at least 5,000 input tokens and 1,000 output tokens per hour (5,000 and 1,000 today), counted per account over a rolling hour, all keys together. These numbers can go up, never below that minimum. Past the free tier, usage is billed at $0.005 per million input tokens, $0.001 per million cached input tokens and $0.14 per million output tokens, with no rate limit. We'll email every account before the beta ends.

Rate and size limits

Errors

Errors come back as {"error": {"message", "type", "code"}}, like OpenAI's.

Anthropic and Responses formats

Tools built for the Anthropic Messages API (Claude Code, the Anthropic SDKs) can use the same model. Point them at https://cheapllm.shop; they call POST /v1/messages. The key works as x-api-key or Authorization: Bearer. Any model name is accepted and routed to deepseek-v4.1-flash-1017.

curl https://cheapllm.shop/v1/messages \
  -H "x-api-key: $CHEAPLLM_API_KEY" \
  -H "anthropic-version: 2023-06-01" \
  -H "content-type: application/json" \
  -d '{"model": "deepseek-v4.1-flash-1017", "max_tokens": 1024,
       "messages": [{"role": "user", "content": "Hello!"}]}'

Supported: text, images, system prompts, tool use and tool results, streaming events, stop sequences. Thinking blocks are not returned. POST /v1/messages/count_tokens returns an estimate.

Tools built for the OpenAI Responses API (Codex CLI, recent OpenAI SDK code) can call POST /v1/responses on https://cheapllm.shop/v1: text and image input, instructions, function and custom tools, streaming events. Stateless only (store and previous_response_id are not kept).

Your tools

Step-by-step settings for Claude Code, OpenCode, Codex CLI, DeepSeek Harness, Cline, Roo Code, Kilo Code, Continue, Copilot, Cursor, Zed and many more are on the integrations page. In short: anything with an "OpenAI-compatible" or "custom base URL" setting works with the base URL, your key and the model name above.

Environment variables

export OPENAI_BASE_URL=https://cheapllm.shop/v1
export OPENAI_API_BASE=https://cheapllm.shop/v1   # older libraries
export OPENAI_API_KEY=sk-cheap-...

Windows (PowerShell; setx keeps them for new windows):

setx OPENAI_BASE_URL "https://cheapllm.shop/v1"
setx OPENAI_API_BASE "https://cheapllm.shop/v1"
setx OPENAI_API_KEY "sk-cheap-..."

Or let the installer pick, install and configure your tools (all 40 from the integrations page): curl -fsSL https://cheapllm.shop/setup.sh | sh on macOS and Linux, irm https://cheapllm.shop/setup.ps1 | iex in Windows PowerShell.

Open WebUI

Admin settings, Connections, OpenAI API: add a connection with the base URL and your key. The model appears in the picker.

LibreChat

endpoints:
  custom:
    - name: "cheapllm"
      apiKey: "${CHEAPLLM_API_KEY}"
      baseURL: "https://cheapllm.shop/v1"
      models:
        default: ["deepseek-v4.1-flash-1017"]

Continue (VS Code, JetBrains)

models:
  - name: cheapllm
    provider: openai
    model: deepseek-v4.1-flash-1017
    apiBase: https://cheapllm.shop/v1
    apiKey: sk-cheap-...

Aider

aider --openai-api-base https://cheapllm.shop/v1 --openai-api-key sk-cheap-... \
      --model openai/deepseek-v4.1-flash-1017

Cursor

Settings, Models: paste your key in the OpenAI API key field, turn on "Override OpenAI Base URL" with the base URL, then add the model name as a custom model.

LangChain

from langchain_openai import ChatOpenAI
llm = ChatOpenAI(model="deepseek-v4.1-flash-1017", base_url="https://cheapllm.shop/v1", api_key="sk-cheap-...")

Vercel AI SDK

import { createOpenAICompatible } from "@ai-sdk/openai-compatible";
const cheapllm = createOpenAICompatible({ name: "cheapllm", baseURL: "https://cheapllm.shop/v1", apiKey: process.env.CHEAPLLM_API_KEY });
const model = cheapllm("deepseek-v4.1-flash-1017");

Stuck? Write to [email protected] with the x-request-id of the failing call.