What is the claude token API pricing for uncensored models?

The uncensored LLM costs $0.15 per million input tokens and $0.50 per million output tokens. Errors and refusals do not consume credit. Prepaid credit never expires, and you can top up with USDT or USDC.

Is this an openai compatible API for existing clients?

Yes, it uses the standard /v1/chat/completions endpoint. You only need to update the base URL and API key in your OpenAI SDK. The model ID is uncensored . It supports streaming, tools, and JSON mode natively.

Which payment methods do you accept?

Crypto only: USDT on TRC20 or USDC on Base, any whole amount from $20 to $500. Bonus credit applies from $50.

Inicio rápido: Integra la API sin censura

Prerequisites: SDK Installation

Install the official SDK for your preferred language. Our API accepts standard parameters, so you can reuse existing client code. Ensure you have Python 3.8+ or Node.js 18+ available in your environment. The library handles serialization and retries automatically.

from openai import OpenAI

client = OpenAI(base_url="https://api.claudetokenapi.com/v1", api_key="YOUR_KEY")

resp = client.chat.completions.create(
    model="uncensored",
    messages=[{"role": "user", "content": "Summarise this thread without softening it."}],
)
print(resp.choices[0].message.content)

import OpenAI from "openai";

const client = new OpenAI({ baseURL: "https://api.claudetokenapi.com/v1", apiKey: process.env.API_KEY });

const resp = await client.chat.completions.create({
  model: "uncensored",
  messages: [{ role: "user", content: "Draft a villain monologue for my game." }],
});
console.log(resp.choices[0].message.content);

Configuration: Base URL and Key

Point your client to our base URL and set your API key. Use https://api.claudetokenapi.com/v1 as the endpoint. Generate your key via the dashboard using Google or email. The key authenticates all requests to the uncensored model endpoint.

curl https://api.claudetokenapi.com/v1/chat/completions \
  -H "Authorization: Bearer $API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "uncensored",
    "messages": [{"role": "user", "content": "Parse the logs and list all 500 errors from last hour"}]
  }'

Sending Your First Request

Send a POST request to /v1/chat/completions. Set the model ID to uncensored. Include your system and user messages in the content array. The API returns a text response containing the generated output. This works for any lawful adult content without standard refusals.

Streaming Responses with SSE

Enable streaming by setting stream: true. The API returns a Server-Sent Events stream. Token usage appears in the final chunk. This reduces perceived latency for long generations. Parse the SSE events to display text incrementally to your users.

stream = client.chat.completions.create(
    model="uncensored",
    messages=[{"role": "user", "content": "Tell the story in second person."}],
    stream=True,
)
for chunk in stream:
    if chunk.choices and chunk.choices[0].delta.content:
        print(chunk.choices[0].delta.content, end="", flush=True)

Handling Errors and Limits

Monitor HTTP status codes for request health. A 401 error indicates an invalid or expired API key. A 402 error means your prepaid credit is exhausted. A 429 error signals you have exceeded the 300 requests per minute limit. Context windows span 100,000 tokens total. Request bodies must stay under 8 MB.

Using Tools and JSON Mode

Activate function calling by passing tools in the request body. Use response_format: {type: "json_object"} for strict JSON outputs. Set parameters like temperature or seed to control randomness. The model supports standard OpenAI tool definitions. This enables complex agent workflows with the uncensored model.

Quickstart: Integrate in Minutes