MODEL PROFILE

Jan-nano-128k-GGUF

unsloth · Jan-nano-128k-GGUF

Jan-Nano-128k represents a significant advancement in compact language models for research applications. Building upon the success of Jan-Nano, this enhanced version features a **native 128k context window** that enables deeper, more comprehensive research capabilities without the performance degradation typically associated with context extension methods. **Key Improvements:** - **🔍 Research Deeper**: Extended context allows for processing entire research papers, lengthy documents, and complex multi-turn conversations - **⚡ Native 128k Window**: Built from the ground up to handle long contexts efficiently, maintaining performance across the full context range - **📈 Enhanced Performance**: Unlike traditional context extension methods, Jan-Nano-128k shows improved performance with longer contexts This model maintains full compatibility with Model Context Protocol (MCP) servers while dramatically expanding the scope of research tasks it can handle in a single session.

Text generationlicense:apache-2.0
Context windowNot disclosed
Input → OutputText → Text
Model weightsNot verified
Profile updated2026/10/30 17:13:08
OVERVIEW

Model overview

Jan-Nano-128k represents a significant advancement in compact language models for research applications. Building upon the success of Jan-Nano, this enhanced version features a **native 128k context window** that enables deeper, more comprehensive research capabilities without the performance degradation typically associated with context extension methods. **Key Improvements:** - **🔍 Research Deeper**: Extended context allows for processing entire research papers, lengthy documents, and complex multi-turn conversations - **⚡ Native 128k Window**: Built from the ground up to handle long contexts efficiently, maintaining performance across the full context range - **📈 Enhanced Performance**: Unlike traditional context extension methods, Jan-Nano-128k shows improved performance with longer contexts This model maintains full compatibility with Model Context Protocol (MCP) servers while dramatically expanding the scope of research tasks it can handle in a single session.

Key features

特点摘要待依据来源补齐,不凭模型名称推断能力。

Limitations & considerations

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PRICING & COST

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INDEPENDENT BENCHMARKS

Public benchmarks & run configuration

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Frequently asked questions

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Sources & traceability

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。