GPT-6 Astra · API

OpenAI-compatible chat completions backed by GPT-6 Astra, the next-generation OpenAI flagship: a 1,050,000-token context, up to 128,000 output tokens, reasoning_effort up to xhigh, image input, tool calling and prompt caching. Set model to gpt-6-astra; the same model is also served on /v1/responses. Cached input settles at one tenth of the input rate. This model also returns a reasoning summary: choices[].message.reasoning_content when non-streaming, choices[].delta.reasoning_content when streaming. The answer itself stays in content and is never mixed with the reasoning, so clients that only read content need no changes. When reasoning_effort is omitted the gateway requests the medium tier (the model's own default) and the summary comes back all the same. Billing: thinking tokens are charged at the output rate and are included in usage.completion_tokens; usage.completion_tokens_details.reasoning_tokens breaks out how many were reasoning -- those tokens are billed whether or not you read the field. Note that OpenAI exposes only a summary of the reasoning, never the raw chain of thought, so this field is usually short. Note: this model is served over a ChatGPT-subscription upstream that does not accept temperature / top_p / max_tokens / max_completion_tokens / frequency_penalty / presence_penalty -- sending them is silently ignored (no error). Use reasoning_effort for thinking depth and prompt wording for length. For image input use a base64 data: URI; a public image URL may time out upstream.

📥 Context window (max input)：1,050,000 tokens (OpenAI published figure); up to 128,000 output tokens per call. System-prompt overhead counts toward it.

Authorization: Bearer YOUR_API_KEY
Content-Type: application/json

curl https://nezhagate.com/v1/chat/completions -H "Authorization: Bearer YOUR_API_KEY" -H "Content-Type: application/json" -d '{"model": "gpt-6-astra", "messages": [{"role": "user", "content": "Hello"}], "stream": false}'

from openai import OpenAI

client = OpenAI(api_key="YOUR_API_KEY", base_url="https://nezhagate.com/v1")
res = client.chat.completions.create(
    model="gpt-6-astra",
    messages=[{"role": "user", "content": "Hello"}],
)
print(res.choices[0].message.content)

import OpenAI from "openai";

const client = new OpenAI({ apiKey: "YOUR_API_KEY", baseURL: "https://nezhagate.com/v1" });
const res = await client.chat.completions.create({
  model: "gpt-6-astra",
  messages: [{ role: "user", content: "Hello" }],
});
console.log(res.choices[0].message.content);

{
  "id": "chatcmpl_xxx",
  "object": "chat.completion",
  "model": "gpt-6-astra",
  "choices": [
    {
      "index": 0,
      "message": {
        "role": "assistant",
        "reasoning_content": "**Weighing the options** ... (a summary of how the model reasoned)",
        "content": "Hello!"
      },
      "finish_reason": "stop"
    }
  ],
  "usage": {
    "prompt_tokens": 11,
    "completion_tokens": 105,
    "total_tokens": 116,
    "completion_tokens_details": {"reasoning_tokens": 43}
  }
}

curl https://nezhagate.com/v1/chat/completions -H "Authorization: Bearer YOUR_API_KEY" -H "Content-Type: application/json" -d '{"model": "gpt-6-astra", "messages": [{"role": "user", "content": [{"type": "text", "text": "What is in this picture?"}, {"type": "image_url", "image_url": {"url": "https://example.com/photo.jpg"}}]}]}'