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Baidu: ERNIE 4.5 VL 424B A47B

baidu/ernie-4.5-vl-424b-a47b

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ERNIE-4.5-VL-424B-A47B is a multimodal Mixture-of-Experts (MoE) model from Baidu’s ERNIE 4.5 series, featuring 424B total parameters with 47B active per token. It is trained jointly on text and image data using a heterogeneous MoE architecture and modality-isolated routing to enable high-fidelity cross-modal reasoning, image understanding, and long-context generation (up to 131k tokens). Fine-tuned with techniques like SFT, DPO, UPO, and RLVR, this model supports both “thinking” and non-thinking inference modes. Designed for vision-language tasks in English and Chinese, it is optimized for efficient scaling and can operate under 4-bit/8-bit quantization.

Modalities

Input Price

$0.42per 1M

Output Price

$1.25per 1M

Context

131K

Weekly Tokens

21.6M

Released

Jun 30, 2025

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API

Sample code and API for ERNIE 4.5 VL 424B A47B

OpenRouter normalizes requests and responses across providers for you.

1

Get your API key

Create an API key from your OpenRouter dashboard and set it as an environment variable:

2

Make your first request

Use baidu/ernie-4.5-vl-424b-a47b with the OpenRouter API:

OpenRouter provides an OpenAI-compatible completion API to 400+ models & providers that you can call directly, or using the OpenAI SDK. Additionally, some third-party SDKs are available.

In the examples below, the OpenRouter-specific headers are optional. Setting them allows your app to appear on the OpenRouter leaderboards.

Using third-party SDKs

For information about using third-party SDKs and frameworks with OpenRouter, please see our frameworks documentation.

3

Enable streaming

Add "stream": true to your request body to receive responses as server-sent events:

Endpoint

POSThttps://openrouter.ai/api/v1/chat/completions
AuthorizationBearer $OPENROUTER_API_KEY
Content-Typeapplication/json
HTTP-Refereroptional — your site URL, for rankings
X-Titleoptional — your site name, for rankings
Modelbaidu/ernie-4.5-vl-424b-a47b

Parameters

NameTypeDefaultDescription
reasoningmap—Controls reasoning behavior for models that support thinking tokens, including whether reasoning is enabled, the reasoning effort, maximum reasoning tokens, and whether reasoning is excluded from the response.
include_reasoningboolean—Deprecated alias for reasoning.exclude.
max_tokensinteger—This sets the upper limit for the number of tokens the model can generate in response.
temperaturefloat1This setting influences the variety in the model's responses.
top_pfloat1This setting limits the model's choices to a percentage of likely tokens: only the top tokens whose probabilities add up to P.
stoparray—Stop generation immediately if the model encounter any token specified in the stop array.
frequency_penaltyfloat0This setting aims to control the repetition of tokens based on how often they appear in the input.
presence_penaltyfloat0Adjusts how often the model repeats specific tokens already used in the input.
seedinteger—If specified, the inferencing will sample deterministically, such that repeated requests with the same seed and parameters should return the same result.
top_kinteger0This limits the model's choice of tokens at each step, making it choose from a smaller set.
repetition_penaltyfloat1Helps to reduce the repetition of tokens from the input.