ERNIE 5.1 API: Baidu's Models for Production
ERNIE 5.1 is Baidu's current flagship text model on Qianfan. The production
API model ID is ernie-5.1; the earlier ERNIE-5.1-Preview label is not an
interchangeable alias.
That small naming detail matters. A model page, a benchmark entry, and an API
identifier can describe the same family without being valid substitutes in a
request. Keep the exact ID in configuration and verify it against the provider
catalog before deployment.
What the API currently exposes
Baidu's developer-facing model list gives ERNIE 5.1 a 128K-token context
window, up to 119K input, and up to 65,536 output tokens. The model is listed as
text-to-text, with tool calling and Qianfan Web Search support.
One official models API example contains larger metadata values. Those fields
do not line up cleanly with the limits in the model list, so 128K is the safer
production planning figure. Do not promise a 248K request until your account
and endpoint have passed a boundary test.
The model is a practical fit for:
- agent workflows that call tools and search;
- Chinese-language retrieval and synthesis;
- long reports that still fit inside a controlled 128K budget;
- applications that already use an OpenAI-shaped client.
It is not yet documented as a multimodal API model. Baidu describes broader
ERNIE family capabilities elsewhere, but the ernie-5.1 API metadata lists
text input and text output.
Direct pricing
Baidu publishes separate mainland China and international rate cards. The
international prices below are in USD per 1M tokens and were checked on
September 11, 2026.
| Input length | Input | Output |
|---|---|---|
| Up to 32K | $0.56 | $2.53 |
| Above 32K, up to 128K | $0.84 | $3.10 |
The mainland Qianfan rates are ¥4 input and ¥18 output per 1M tokens up to 32K,
then ¥6 input and ¥22 output above 32K. These are two regional price lists, not
currency conversions.
No ERNIE 5.1 cache price is published in either current rate-card row. Treat
that as “not documented,” not as a zero-cost cache tier.
First request with the OpenAI SDK
Qianfan provides an OpenAI-compatible v2 endpoint. Keep the credential in an
environment variable:
import os
from openai import OpenAI
client = OpenAI(
api_key=os.environ["QIANFAN_API_KEY"],
base_url="https://qianfan.baidubce.com/v2/",
)
response = client.chat.completions.create(
model="ernie-5.1",
messages=[{"role": "user", "content": "Summarize the deployment risks."}],
)
print(response.choices[0].message.content)
The same request shape works with curl:
curl https://qianfan.baidubce.com/v2/chat/completions \
-H "Authorization: Bearer $QIANFAN_API_KEY" \
-H "Content-Type: application/json" \
-d '{"model":"ernie-5.1","messages":[{"role":"user","content":"Reply with OK"}]}'
Production checks that prevent expensive surprises
Start with a short request, then test the largest payload your application will
actually send. Record input tokens, output tokens, latency, status, and the
price tier selected by input length. A request crossing 32K changes both input
and output rates.
Set an output cap below the documented maximum. A large context window is not
an invitation to fill every token: tool results, retrieved documents, and the
answer all need headroom. Retry only idempotent work, and handle authentication,
balance, rate-limit, and upstream errors separately.
AIWave uses an OpenAI-compatible request shape for Chinese model routes, but
its public catalog did not list ernie-5.1 when this guide was checked. Do not
swap in that ID based on this article alone. Use a currently listed ERNIE model
or wait until the exact route and dated price appear in the public catalog.
That is the production rule worth keeping: documentation tells you what a
provider offers; your live catalog tells you what your account can call today.
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