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OpenAI: GPT-6 Astra ProNEW
openai/gpt-6-astra-protextVisionFilesReasoning
GPT-6 Astra Pro is the same underlying model as GPT-6 Astra, served with `reasoning.mode` set to `pro` for higher-quality responses on complex tasks. Learn more in OpenAI's docs: https://developers.openai.com/api/docs/guides/reasoning#reasoning-mode
Price in / out
Cache, read / write
Context / Max output
1.05M / 128K
Released
Sep 4, 2026
Additional rates
Flex, in / out
Web search
Above 272K prompt tokens the upstream charges more: 2× input, 1.5× output. Per-route rates are in the table below.
Parameters
messagesrequiredreasoning_effortlow · medium · high · xhigh · maxmax_tokensoptional · alias max_completion_tokensstreamtrue · falsetoolsfunction calling (OpenAI format)tool_choiceauto · none · requiredresponse_formatjson_object · json_schemaweb_search · · · providerrouting: order · only · ignore · sortservice_tierflexstream_options{"include_usage": true}image_urlimage (data: URL)filePDF · DOCX · TXT · CSV · XLSX · PPTX (data: URL)Fine-tuning · 1
seedoptionalHow to use via API
from openai import OpenAI
client = OpenAI(base_url="https://api.mixen.ai/v1", api_key="mxn-...")
resp = client.chat.completions.create(
model="openai/gpt-6-astra-pro",
messages=[{"role": "user", "content": "Привет"}],
reasoning_effort="low", # low · medium · high · xhigh · max
max_tokens=1024,
stream=False,
)
print(resp.choices[0].message.content)
# Стриминг: stream=True — ответ приходит чанками
for chunk in client.chat.completions.create(
model="openai/gpt-6-astra-pro",
messages=[{"role": "user", "content": "Привет"}],
stream=True,
):
print(chunk.choices[0].delta.content or "", end="", flush=True)
# эконом-тир: тот же ответ вдвое дешевле, но ниже приоритет в очереди
cheap = client.chat.completions.create(
model="openai/gpt-6-astra-pro",
messages=[{"role": "user", "content": "Привет"}],
extra_body={"service_tier": "flex"},
)
# с файлом (PDF · DOCX · TXT · CSV · XLSX · PPTX)
doc = client.chat.completions.create(
model="openai/gpt-6-astra-pro",
messages=[{"role": "user", "content": [
{"type": "text", "text": "Кратко перескажи документ"},
{"type": "file", "file": {
"filename": "doc.pdf",
"file_data": "data:application/pdf;base64,JVBERi0...",
}},
]}],
)
