ERNIE 4.5 Turbo VL
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ERNIE 4.5 Turbo VL

ernie-4.5-turbo-vl
Baidu
The new version of the Wenxin Yiyan large model significantly improves capabilities in image understanding, creation, translation, and coding. It supports a context length of up to 32K tokens for the first time, with a notable reduction in the latency of the first token.

Pricing

  • Input Tokens: $0.400 /M tokens
  • Output Tokens: $1.200 /M tokens

Input Modalities

  • Text
  • Vision

Output Modalities

  • Text

Capabilities

  • Tools
  • Tool calling
  • Structured outputs

Providers

Baidu ernie-4.5-turbo-vl-latest
Pricing$0.400$1.200
Context139K
Max output16K
Latency-
Throughput-
Uptime
0.00% uptime 2 days ago
0.00% uptime yesterday
0.00% uptime today
Baidu ernie-4.5-turbo-vl
Pricing$0.400$1.200
Context139K
Max output16K
Latency0.6S
Throughput24.4TPS
Uptime
0.00% uptime 2 days ago
0.00% uptime yesterday
0.00% uptime today
Baidu ernie-4.5-turbo-vl-32k-preview
Pricing$0.400$1.200
Context43K
Max output16K
Latency-
Throughput-
Uptime
0.00% uptime 2 days ago
0.00% uptime yesterday
0.00% uptime today

Performance for ernie-4.5-turbo-vl

Uptime is the percentage of requests that succeeded over the past 72 hours. AIHubMix continuously monitors every provider and automatically retries with the next-best provider when one returns an error or responds too slowly; Latency is total round-trip time (lower is better); Throughput is how fast the model writes (tokens per second, higher is better).

Uptime
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Latency
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Throughput
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Try this model

Python
import os
from openai import OpenAI

client = OpenAI(
    api_key=os.environ["AIHUBMIX_API_KEY"],
    base_url="https://aihubmix.com/v1",
)

response = client.chat.completions.create(
    model="ernie-4.5-turbo-vl",
    messages=[
      {
        "role": "user",
        "content": "Hello, how are you?"
      }
    ],
    max_tokens=1024,
    stream=False,
)

print(response.choices[0].message.content)

Frequently asked questions

What is ERNIE 4.5 Turbo VL?

The new version of the Wenxin Yiyan large model significantly improves capabilities in image understanding, creation, translation, and coding. It supports a context length of up to 32K tokens for the first time, with a notable reduction in the latency of the first token.