Comparison results of Phi-3-vision-128K-Instruct and MiniCPM-Llama3-V 2.5, regarding the model size, hardware requirements, and performances.
我们提供了从模型参数、硬件需求、性能指标等方面对比 Phi-3-vision-128K-Instruct 和 MiniCPM-Llama3-V 2.5 的结果。
With in4 quantization, MiniCPM-Llama3-V 2.5 delivers smooth inference with only 8GB of GPU memory.
通过 int4 量化，MiniCPM-Llama3-V 2.5 仅需 8GB 显存即可推理。
| Model（模型） | GPU Memory（显存） |
|---|---|
| MiniCPM-Llama3-V 2.5 | 19 GB |
| Phi-3-vision-128K-Instruct | 12 GB |
| MiniCPM-Llama3-V 2.5 (int4) | 8 GB |
In most benchmarks, MiniCPM-Llama3-V 2.5 achieves better performance compared with Phi-3-vision-128K-Instruct.
在大多数评测集上， MiniCPM-Llama3-V 2.5 相比于 Phi-3-vision-128K-Instruct 都展现出了更优的性能表现.
| Phi-3-vision-128K-Instruct | MiniCPM-Llama3-V 2.5 | |
|---|---|---|
| Size（参数） | 4B | 8B |
| OpenCompass 2024/05 | 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 |
MiniCPM-Llama3-V 2.5 exhibits stronger multilingual capabilities compared with Phi-3-vision-128K-Instruct on LLaVA Bench.
MiniCPM-Llama3-V 2.5 在对话和推理评测榜单 LLaVA Bench 上展现出了比 Phi-3-vision-128K-Instruct 更强的多语言的性能。
Evaluation results of LLaVABench in multiple languages
多语言LLaVA Bench评测结果