Warp

ERNIE 4.5 VL 28B A3B

ChatInput: TextInput: ImageReleased Jun 28, 2025

Built by Baidu · China · research.baidu.com

The ERNIE 4.5 series of open-source models adopts a Mixture-of-Experts (MoE) architecture, representing an innovative multimodal heterogeneous model structure. It achieves cross-modal knowledge fusion through a parameter-sharing mechanism while retaining dedicated parameter spaces for individual modalities. This architecture is particularly well-suited for the continuous pre-training paradigm from large language models to multimodal models, significantly enhancing multimodal understanding capabilities while maintaining or even improving performance in text-based tasks. The models are efficiently trained, inferred, and deployed using the PaddlePaddle deep learning framework. During the pre-training of large language models, the Model FLOPs Utilization (MFU) reaches 47%. Experimental results demonstrate that this series of models achieves state-of-the-art (SOTA) performance across multiple text and multimodal benchmarks, with particularly outstanding results in instruction following, world knowledge memorizatio

How to use

Just add the suffix. Hard questions still come back from this model; only easy ones drop to something cheaper, and nothing pricier than it gets used.

model: "baidu/ernie-4.5-vl-28b-a3b:auto"

Sets no behavior — whatever your key already stores stays in effect.

Without the suffix, the bare name always goes to this model — no routing, so nothing saved.

Context

30K

Max output

8K

Input $/1M

$0.14

Output $/1M

$0.56

Features

Providers

Novita

Providers

Price, latency, and uptime per provider serving this model. Warp tries them in order of how each host has just been behaving, moving to the next on failure. Click a row for regions and data policies.

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Performance

Measured latency (lower is better) and throughput (higher is better) per provider.

Speed

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Parameter support

What Warp actually does with each parameter when you call this model. The answer differs by serving provider and by API surface.