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## Phi-3-vision-128K-Instruct vs MiniCPM-Llama3-V 2.5
Comparison results of Phi-3-vision-128K-Instruct and MiniCPM-Llama3-V 2.5, regarding the model size, hardware requirements, and performances on multiple popular benchmarks.
我们提供了从模型参数、硬件需求、全面性能指标等方面对比 Phi-3-vision-128K-Instruct 和 MiniCPM-Llama3-V 2.5 的结果。
## Hardeware Requirements （硬件需求）
With in4 quantization, MiniCPM-Llama3-V 2.5 delivers smooth inference of 6-8 tokens/s with only 8GB of GPU memory.
通过 in4 量化，MiniCPM-Llama3-V 2.5 仅需 8GB 显存即可提供 6-8 tokens/s 的流畅推理。
| Model（模型） | GPU Memory（显存） |
|:----------------------|:-------------------:|
| [MiniCPM-Llama3-V 2.5](https://huggingface.co/openbmb/MiniCPM-Llama3-V-2_5/) | 19 GB |
| Phi-3-vision-128K-Instruct | 12 GB |
| [MiniCPM-Llama3-V 2.5 (int4)](https://huggingface.co/openbmb/MiniCPM-Llama3-V-2_5-int4/) | 8 GB |
## Model Size and Peformance （模型参数和性能）
| | Phi-3-vision-128K-Instruct | MiniCPM-Llama3-V 2.5|
|:-|:----------:|:-------------------:|
| Size（参数） | **4B** | 8B|
| OpenCompass | 53.7 | **58.8** |
| OCRBench | 639.0 | **725.0**|
| RealworldQA | 58.8 | **63.5**|
| TextVQA | 72.2 | **76.6** |
| ScienceQA| **90.8** | 89.0 |
| POPE | 83.4 | **87.2** |