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AIモデルライブラリ/openbmb/MiniCPM4-MCP
モデル情報

MiniCPM4-MCP

openbmb · MiniCPM4-MCP

MiniCPM4 series are highly efficient large language models (LLMs) designed explicitly for end-side devices, which achieves this efficiency through systematic innovation in four key dimensions: model architecture, training data, training algorithms, and inference systems. - MiniCPM4-8B: The flagship of MiniCPM4, with 8B parameters, trained on 8T tokens. - MiniCPM4-0.5B: The small version of MiniCPM4, with 0.5B parameters, trained on 1T tokens. - MiniCPM4-8B-Eagle-FRSpec: Eagle head for FRSpec, accelerating speculative inference for MiniCPM4-8B. - MiniCPM4-8B-Eagle-FRSpec-QAT-cpmcu: Eagle head trained with QAT for FRSpec, efficiently integrate speculation and quantization to achieve ultra acceleration for MiniCPM4-8B. - MiniCPM4-8B-Eagle-vLLM: Eagle head in vLLM format, accelerating speculative inference for MiniCPM4-8B. - MiniCPM4-8B-marlin-Eagle-vLLM: Quantized Eagle head for vLLM format, accelerating speculative inference for MiniCPM4-8B. - BitCPM4-0.5B: Extreme ternary quantization applied to MiniCPM4-0.5B compresses model parameters into ternary values, achieving a 90% reduction in bit width. - BitCPM4-1B: Extreme ternary quantization applied to MiniCPM3-1B compresses model parameters into ternary values, achieving a 90% reduction in bit width. - MiniCPM4-Survey: Based on MiniCPM4-8B, accepts users' quiries as input and autonomously generate trustworthy, long-form survey papers. - MiniCPM4-MCP: Based on MiniCPM4-8B, accepts users' queries and available MCP tools as input and autonomously calls relevant MCP tools to satisfy users' requirements. (**<-- you are here**) **MiniCPM4-MCP** is an open-source on-device LLM agent model jointly developed by THUNLP, Renmin University of China and ModelBest, built on MiniCPM-4 with 8 billion parameters. It is capable of solving a wide range of real-world tasks by interacting with various tool and data resources through MCP. The MCP Servers supported by MiniCPM4-MCP include Airbnb, Amap-Maps, Arxiv-MCP-Server, Calculator, Computer-Control-MCP, Desktop-commander, Filesystem, Github, Gaode, MCP-Code-Executor, MCP-DOCx, PPT, PPTx, Simple-Time-Server, Slack, and Whisper. Follow the instructions provided in each server's reposi

翻訳待ちのため原文を表示しています。

テキスト生成license:apache-2.0
コンテキスト長非公開
入力 → 出力テキスト → テキスト
モデルウェイト未確認
情報更新日時2026/11/2 19:15:48
OVERVIEW

モデル紹介

MiniCPM4 series are highly efficient large language models (LLMs) designed explicitly for end-side devices, which achieves this efficiency through systematic innovation in four key dimensions: model architecture, training data, training algorithms, and inference systems. - MiniCPM4-8B: The flagship of MiniCPM4, with 8B parameters, trained on 8T tokens. - MiniCPM4-0.5B: The small version of MiniCPM4, with 0.5B parameters, trained on 1T tokens. - MiniCPM4-8B-Eagle-FRSpec: Eagle head for FRSpec, accelerating speculative inference for MiniCPM4-8B. - MiniCPM4-8B-Eagle-FRSpec-QAT-cpmcu: Eagle head trained with QAT for FRSpec, efficiently integrate speculation and quantization to achieve ultra acceleration for MiniCPM4-8B. - MiniCPM4-8B-Eagle-vLLM: Eagle head in vLLM format, accelerating speculative inference for MiniCPM4-8B. - MiniCPM4-8B-marlin-Eagle-vLLM: Quantized Eagle head for vLLM format, accelerating speculative inference for MiniCPM4-8B. - BitCPM4-0.5B: Extreme ternary quantization applied to MiniCPM4-0.5B compresses model parameters into ternary values, achieving a 90% reduction in bit width. - BitCPM4-1B: Extreme ternary quantization applied to MiniCPM3-1B compresses model parameters into ternary values, achieving a 90% reduction in bit width. - MiniCPM4-Survey: Based on MiniCPM4-8B, accepts users' quiries as input and autonomously generate trustworthy, long-form survey papers. - MiniCPM4-MCP: Based on MiniCPM4-8B, accepts users' queries and available MCP tools as input and autonomously calls relevant MCP tools to satisfy users' requirements. (**<-- you are here**) **MiniCPM4-MCP** is an open-source on-device LLM agent model jointly developed by THUNLP, Renmin University of China and ModelBest, built on MiniCPM-4 with 8 billion parameters. It is capable of solving a wide range of real-world tasks by interacting with various tool and data resources through MCP. The MCP Servers supported by MiniCPM4-MCP include Airbnb, Amap-Maps, Arxiv-MCP-Server, Calculator, Computer-Control-MCP, Desktop-commander, Filesystem, Github, Gaode, MCP-Code-Executor, MCP-DOCx, PPT, PPTx, Simple-Time-Server, Slack, and Whisper. Follow the instructions provided in each server's reposi

主な特徴

特点摘要待依据来源补齐，不凭模型名称推断能力。

制約と注意点

具体的な制約を判断する出典が不足しています。実際の性能、遅延、データ方針、ライセンス、提供期間を確認してください。

PRICING & COST

出典別料金と費用分析

料金はチャネル・地域・設定によって異なります。各チャネルの料金は個別に表示し、提供元の統一公式料金とは見なしません。

出典・チャネル入力出力課金単位収集日時
確認可能な料金がありません。出典を確認してください。

月額の基本トークン費用を試算

—

試算はキャッシュ割引、段階料金、マルチモーダル追加料金、検索、税金、追加推論出力を含みません。

INDEPENDENT BENCHMARKS

公開評価と実行設定

暂无已采集的可核验公开评分。模型未上榜不代表能力较低。

収録済みの全ランキング →

よくある質問

オープンウェイトなら無料で商用利用できますか？

必ずしもそうではありません。バージョン別のライセンス、商用条件、利用方針を確認してください。自前運用には計算資源と保守費用も必要です。

これはリアルタイムの請求料金ですか？

収集日時付きの料金スナップショットです。最新のバージョン、地域、割引、課金方式は各チャネルで確認してください。

出典と追跡記録

huggingface · openbmb/MiniCPM4-MCP ↗2026/10/30 03:58:17
huggingface · enrich:3a6d17be-267b-4d34-bdb3-25138c99e530 ↗2026/10/30 17:06:51

许可证：apache-2.0。模型介绍与第三方评测均以原来源的具体版本和方法为准。