aistaging/minicpm-v-4_5

By aistaging

Updated 5 months ago

9B multimodal model with vision, speech, and full-duplex streaming for text, image, video, audio

Model
0

905

aistaging/minicpm-v-4_5 repository overview

MiniCPM-o 4.5

MiniCPM-o 4.5 is a state-of-the-art multimodal language model that delivers Gemini 2.5 Flash-level performance for vision, speech, and full-duplex multimodal live streaming capabilities. Built on an end-to-end architecture combining SigLip2, Whisper-medium, CosyVoice2, and Qwen3-8B, the model totals 9B parameters while surpassing widely used proprietary models like GPT-4o and Gemini 2.0 Pro in vision-language tasks.

The model excels across multiple modalities with leading visual understanding capabilities, achieving an average OpenCompass score of 77.6 across 8 popular benchmarks. It supports both instruct and thinking modes in a single model, offering flexibility for different performance and efficiency trade-offs. MiniCPM-o 4.5 features bilingual real-time speech conversation in English and Chinese with configurable voices, voice cloning, and role-play capabilities. A standout feature is its full-duplex multimodal live streaming, allowing the model to simultaneously process continuous video and audio input streams while generating concurrent text and speech outputs without mutual blocking.

The model demonstrates strong OCR capabilities with state-of-the-art performance for end-to-end English document parsing on OmniDocBench, surpassing specialized tools and proprietary models. It efficiently processes high-resolution images up to 1.8 million pixels and high-FPS videos up to 10fps in any aspect ratio, while supporting multilingual capabilities across more than 30 languages.

MiniCPM-o 4.5 Architecture


Characteristics

AttributeValue
ProviderOpenBMB
ArchitectureQwen3 (SigLip2 + Whisper-medium + CosyVoice2 + Qwen3-8B)
Parameters9B
Context Length40,960 tokens
Languages30+ languages (with bilingual speech support for English and Chinese)
Input modalitiesText, Image, Video, Audio
Output modalitiesText, Speech
LicenseApache 2.0

Using this model with Docker Model Runner

docker model run minicpm-v-4_5

For more information, check out the Docker Model Runner docs.

Benchmarks

MiniCPM-o 4.5 Performance Radar

OpenCompass Visual Understanding (Instruct Mode)
ModelOpenCompassMMBench ENMMBench CNMathVistaMMVetMMMUMMStarHallusionBench
MiniCPM-o 4.5-Instruct77.687.687.280.174.467.673.163.2
Gemini 2.5 Flash78.586.686.075.381.476.375.859.1
InternVL-3.5-8B75.879.580.078.483.173.469.354.5
Qwen3-VL-8B-Instruct76.584.584.777.273.769.670.961.1
Video Understanding
ModelVideo-MME (w/o subs)LVBenchMLVU (M-Avg)LongVideoBenchMotionBench
MiniCPM-o 4.5-Instruct70.450.976.566.061.4
Gemini 2.5 Flash75.662.277.8--
Qwen3-Omni-30B-A3B70.550.275.266.961.7
InternVL-3.5-8B66.0-70.262.162.3
OmniDocBench (Document Parsing)
ModelOverall Edit (EN)Text Edit (EN)Formula Edit (EN)Table TEDS (EN)Read Order Edit (EN)
MiniCPM-o 4.5-Instruct0.1090.0460.25786.80.037
PaddleOCR-VL0.1050.0410.24188.00.045
Gemini 3 Flash0.1550.1380.29786.40.072
DeepSeek-OCR 20.1190.0410.25682.60.055

Note: Lower Edit scores are better; higher TEDS scores are better.

Omni Simplex (Multimodal Understanding)
ModelDaily-OmniWorldSenseVideo-HolmesJointAVBenchAVUT-HumanFutureOmniAvg
MiniCPM-o 4.5-Instruct80.255.764.360.078.656.168.5
Qwen3-Omni-30B-A3B70.754.050.453.174.262.163.7
Gemini 2.5 Flash79.352.651.355.665.455.663.6
Text Capabilities
ModelIFEval-PLSBBHCMMLUMMLUHumanEvalMBPPMath500GSM8KAvg
MiniCPM-o 4.5-Instruct84.781.179.577.086.676.777.094.582.1
Qwen3-8B-Instruct83.069.478.781.786.675.984.093.481.6
Vision Duplex (Full-Duplex Streaming)
ModelLiveSports-3K-CC (Win Rate vs GPT-4o)
MiniCPM-o 4.5-Instruct54.4
StreamingVLM45.6
LiveCC-7B-Instruct41.5

Considerations

  • The model supports both instruct and thinking modes - instruct mode prioritizes efficiency while thinking mode focuses on enhanced performance for complex reasoning tasks
  • Full-duplex multimodal live streaming capabilities require specialized inference frameworks (llama.cpp-omni recommended for local deployment)
  • High-resolution image processing (up to 1.8M pixels) and high-FPS video processing (up to 10fps) may require significant computational resources
  • Voice cloning and role-play features require reference audio clips for optimal performance
  • The model's proactive interaction capabilities in live streaming scenarios are experimental and may require fine-tuning for specific use cases
  • While the model supports 30+ languages for text and vision, speech capabilities are currently limited to English and Chinese
Generated by

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Tag summary

Content type

Model

Digest

sha256:3df6a19bd

Size

5.7 GB

Last updated

5 months ago

docker model pull aistaging/minicpm-v-4_5:9B-Q4_K_M