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MiniCPM 4.0 - Wallfacer Intelligence's open-source, ultra-efficient large-scale edge model

MiniCPM 4.0 is a large edge-side model launched by Wallfacer. The model comes in two parameter scales: 8B and 0.5B. The 8B lightning sparse version employs an innovative sparse architecture, enabling efficient processing of long text tasks; the 0.5B version uses low computational resources...

What is MiniCPM 4.0?

MiniCPM 4.0 is an ultra-efficient edge-side large model launched by Mianbi Intelligence. The model comes in two parameter scales: 8B and 0.5B. The 8B lightning sparse version employs an innovative sparse architecture, enabling efficient processing of long text tasks; the 0.5B version is known for its low computational resource consumption and high performance. The self-developed CPM.cu inference framework can achieve up to 220 times speedup in extreme scenarios and 5 times speedup under normal conditions. MiniCPM 4.0 supports deployment on open-source frameworks such as vLLM, SGLang, and LlamaFactory, and is compatible with mainstream chips such as Intel, Qualcomm, MTK, and Huawei Ascend.

MiniCPM 4.0 Open Source Model Collection

MiniCPM4-8B: The flagship model of MiniCPM4, with 8 billion parameters, trained on 8T tokens.

MiniCPM4-0.5B: A smaller version of MiniCPM4 with 0.5 billion parameters, trained on 1T tokens.

MiniCPM4-8B-Eagle-FRSpec: Eagle header for FRSpec, accelerating speculative inference in MiniCPM4-8B.

MiniCPM4-8B-Eagle-FRSpec-QAT-cpmcu: Uses the Eagle head of FRSpec trained with QAT to efficiently combine inference and quantization, achieving a super-acceleration of MiniCPM4-8B.

MiniCPM4-8B-Eagle-vLLMEagle header in vLLM format accelerates speculative reasoning in MiniCPM4-8B.

MiniCPM4-8B-marlin-Eagle-vLLM: A quantized vLLM format Eagle header that accelerates speculative inference in MiniCPM4-8B.

BitCPM4-0.5B: Application of extreme valuesTernary quantizationIn MiniCPM4-0.5B, the model parameters are compressed into ternary values, achieving a 90% reduction in bit width.

BitCPM4-1B: Applying extreme value ternary quantization to MiniCPM3-1B compresses model parameters into ternary values, achieving a 90% reduction in bit width.

MiniCPM4-Survey: Based on MiniCPM4-8B, it accepts user queries as input and automatically generates credible long-form survey papers.

MiniCPM4-MCP: Based on MiniCPM4-8B, it accepts user queries and available MCP tools as input, and automatically calls the relevant MCP tools to meet user needs.

Main functions of MiniCPM 4.0

  • High-efficiency dual-frequency shifting mechanismMiniCPM version 4.0-8B can automatically switch attention modes based on task characteristics. When processing long text, it enables sparse attention to reduce computational complexity; when processing short text, it switches to dense attention to ensure accuracy.
  • Ultimate reasoning speed boostThrough the self-developed CPM.cu inference framework, it achieves a speedup of up to 220 times in extreme scenarios and a speedup of 5 times in normal scenarios.
  • Model slimming and efficient deploymentEmploying an innovative sparse architecture and ultra-low bit-width quantization technology, it achieves a 90% reduction in model size while maintaining excellent performance. It supports deployment on open-source frameworks such as vLLM, SGLang, and LlamaFactory.
  • End-side inference optimizationIt features a built-in self-developed CPM.cu ultra-fast edge inference framework, which brings a 90% reduction in model size and speed through innovations in speculative sampling, model compression and quantization, and edge deployment framework.
  • Multi-platform compatibilityIt is compatible with mainstream chips such as Intel, Qualcomm, MTK, and Huawei Ascend, and can run smoothly on a variety of edge devices.
  • Multiple versions availableIt offers versions with two parameter scales: 8B and 0.5B, to meet the needs of different scenarios.

Technical Principles of MiniCPM 4.0

  • Sparse attention mechanismMiniCPM 4.0-8B employs an innovative trainable sparse attention mechanism (InfLLM v2), which, when processing long texts, requires each token to perform relevance calculations with less than 5% of other tokens, greatly reducing the computational overhead of long text processing.
  • High-efficiency dual-frequency shiftingAutomatically switch attention modes based on task characteristics. Enable sparse attention when processing long text to reduce computational complexity, and switch to dense attention when processing short text to ensure accuracy.
  • Model Wind Tunnel 2.0The introduction of advanced downstream task scaling prediction methods enables more accurate searching and determination of the optimal model training configuration.
  • BitCPMIt achieves the ultimate ternary quantization technology, compressing the bit width of model parameters by more than 90%, maintaining excellent performance while significantly "slimming down" the model.
  • High-efficiency training projectIt fully adopts FP8 low-precision computing technology and combines it with a multi-token prediction training strategy to further improve training efficiency.
  • Self-developed reasoning frameworkMiniCPM 4.0 incorporates the self-developed CPM.cu ultra-fast edge inference framework, which brings a 90% reduction in model size and speed through innovations in speculative sampling, model compression and quantization, and edge deployment framework.

MiniCPM 4.0 project address

Application Scenarios of MiniCPM 4.0

  • Intelligent tutoring systemMiniCPM 4.0 can serve as the core of an intelligent tutoring system. Through natural language processing technology, it can understand students' questions and provide detailed answers and explanations, helping students better understand and master knowledge.
  • Case Analysis and Diagnostic AidMiniCPM 4.0 can assist doctors in case analysis by using natural language processing technology to understand medical record content, provide doctors with diagnostic suggestions and reference information, and improve the accuracy and efficiency of diagnosis.
  • Medical Literature SearchIt helps doctors and researchers quickly retrieve relevant medical literature and research findings, providing accurate literature recommendations and summaries, saving time and effort.
  • Intelligent Customer ServiceAs the core of financial customer service, it is essential to answer customer inquiries quickly and accurately, provide personalized services and solutions, and improve customer satisfaction.
  • Game story generationMiniCPM 4.0 can automatically generate rich and diverse game storylines and tasks based on game settings and player behavior, increasing the game's fun and replayability.
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