## MiniCPM-V 4.0
> Archieve at: 2025-08-25
**MiniCPM-V 4.0** is the latest efficient model in the MiniCPM-V series. The model is built based on SigLIP2-400M and MiniCPM4-3B with a total of 4.1B parameters. It inherits the strong single-image, multi-image and video understanding performance of MiniCPM-V 2.6 with largely improved efficiency. Notable features of MiniCPM-V 4.0 include:
- 🔥 **Leading Visual Capability.**
With only 4.1B parameters, MiniCPM-V 4.0 achieves an average score of 69.0 on OpenCompass, a comprehensive evaluation of 8 popular benchmarks, **outperforming GPT-4.1-mini-20250414, MiniCPM-V 2.6 (8.1B params, OpenCompass 65.2) and Qwen2.5-VL-3B-Instruct (3.8B params, OpenCompass 64.5)**. It also shows good performance in multi-image understanding and video understanding.
- 🚀 **Superior Efficiency.**
Designed for on-device deployment, MiniCPM-V 4.0 runs smoothly on end devices. For example, it devlivers **less than 2s first token delay and more than 17 token/s decoding on iPhone 16 Pro Max**, without heating problems. It also shows superior throughput under concurrent requests.
- 💫 **Easy Usage.**
MiniCPM-V 4.0 can be easily used in various ways including **llama.cpp, Ollama, vLLM, SGLang, LLaMA-Factory and local web demo** etc. We also open-source iOS App that can run on iPhone and iPad. Get started easily with our well-structured [Cookbook](https://github.com/OpenSQZ/MiniCPM-V-CookBook), featuring detailed instructions and practical examples.
### Evaluation
Click to view single image results on OpenCompass.
model
Size
Opencompass
OCRBench
MathVista
HallusionBench
MMMU
MMVet
MMBench V1.1
MMStar
AI2D
Proprietary
GPT-4v-20240409
-
63.5
656
55.2
43.9
61.7
67.5
79.8
56.0
78.6
Gemini-1.5-Pro
-
64.5
754
58.3
45.6
60.6
64.0
73.9
59.1
79.1
GPT-4.1-mini-20250414
-
68.9
840
70.9
49.3
55.0
74.3
80.9
60.9
76.0
Claude 3.5 Sonnet-20241022
-
70.6
798
65.3
55.5
66.4
70.1
81.7
65.1
81.2
Open-source
Qwen2.5-VL-3B-Instruct
3.8B
64.5
828
61.2
46.6
51.2
60.0
76.8
56.3
81.4
InternVL2.5-4B
3.7B
65.1
820
60.8
46.6
51.8
61.5
78.2
58.7
81.4
Qwen2.5-VL-7B-Instruct
8.3B
70.9
888
68.1
51.9
58.0
69.7
82.2
64.1
84.3
InternVL2.5-8B
8.1B
68.1
821
64.5
49.0
56.2
62.8
82.5
63.2
84.6
MiniCPM-V-2.6
8.1B
65.2
852
60.8
48.1
49.8
60.0
78.0
57.5
82.1
MiniCPM-o-2.6
8.7B
70.2
889
73.3
51.1
50.9
67.2
80.6
63.3
86.1
MiniCPM-V-4.0
4.1B
69.0
894
66.9
50.8
51.2
68.0
79.7
62.8
82.9
Click to view single image results on ChartQA, MME, RealWorldQA, TextVQA, DocVQA, MathVision, DynaMath, WeMath, Object HalBench and MM Halbench.
model
Size
ChartQA
MME
RealWorldQA
TextVQA
DocVQA
MathVision
DynaMath
WeMath
Obj Hal
MM Hal
CHAIRs↓
CHAIRi↓
score avg@3↑
hall rate avg@3↓
Proprietary
GPT-4v-20240409
-
78.5
1927
61.4
78.0
88.4
-
-
-
-
-
-
-
Gemini-1.5-Pro
-
87.2
-
67.5
78.8
93.1
41.0
31.5
50.5
-
-
-
-
GPT-4.1-mini-20250414
-
-
-
-
-
-
45.3
47.7
-
-
-
-
-
Claude 3.5 Sonnet-20241022
-
90.8
-
60.1
74.1
95.2
35.6
35.7
44.0
-
-
-
-
Open-source
Qwen2.5-VL-3B-Instruct
3.8B
84.0
2157
65.4
79.3
93.9
21.9
13.2
22.9
18.3
10.8
3.9
33.3
InternVL2.5-4B
3.7B
84.0
2338
64.3
76.8
91.6
18.4
15.2
21.2
13.7
8.7
3.2
46.5
Qwen2.5-VL-7B-Instruct
8.3B
87.3
2347
68.5
84.9
95.7
25.4
21.8
36.2
13.3
7.9
4.1
31.6
InternVL2.5-8B
8.1B
84.8
2344
70.1
79.1
93.0
17.0
9.4
23.5
18.3
11.6
3.6
37.2
MiniCPM-V-2.6
8.1B
79.4
2348
65.0
80.1
90.8
17.5
9.0
20.4
7.3
4.7
4.0
29.9
MiniCPM-o-2.6
8.7B
86.9
2372
68.1
82.0
93.5
21.7
10.4
25.2
6.3
3.4
4.1
31.3
MiniCPM-V-4.0
4.1B
84.4
2298
68.5
80.8
92.9
20.7
14.2
32.7
6.3
3.5
4.1
29.2
Click to view multi-image and video understanding results on Mantis, Blink and Video-MME.
model
Size
Mantis
Blink
Video-MME
wo subs
w subs
Proprietary
GPT-4v-20240409
-
62.7
54.6
59.9
63.3
Gemini-1.5-Pro
-
-
59.1
75.0
81.3
GPT-4o-20240513
-
-
68.0
71.9
77.2
Open-source
Qwen2.5-VL-3B-Instruct
3.8B
-
47.6
61.5
67.6
InternVL2.5-4B
3.7B
62.7
50.8
62.3
63.6
Qwen2.5-VL-7B-Instruct
8.3B
-
56.4
65.1
71.6
InternVL2.5-8B
8.1B
67.7
54.8
64.2
66.9
MiniCPM-V-2.6
8.1B
69.1
53.0
60.9
63.6
MiniCPM-o-2.6
8.7B
71.9
56.7
63.9
69.6
MiniCPM-V-4.0
4.1B
71.4
54.0
61.2
65.8