Zero-Click Run Kimi-K2.5-NVFP4 No-Internet Version

Using Docker is the absolute quickest way to install this model on your local machine.

Follow the guidelines below to continue.

The installer auto-downloads and deploys the entire model pack.

The smart installation system will instantly find the perfect configuration for your specific hardware.

📘 Build Hash: e412c5bdd5aee647b9127edfff5c4b3c • 🗓 2026-06-28 Verify CPU: multi-threading optimized for fast prompt processing RAM: high-speed DDR5 memory preferred for CPU offloading Disk Space: at least 100 GB for multiple local LLM variants GPU: modern architecture (Ada Lovelace / Ampere minimum)

The Kimi-K2.5-NVFP4 model introduces a breakthrough in efficient inference for large language tasks. Built on a sparse-attention architecture, it reduces computational load while preserving high contextual understanding. The model achieves state‑of‑the‑art performance on benchmarks such as MMLU and TriviaQA, often outperforming larger parameter counterparts. Its parameter count and memory footprint are optimized for deployment on consumer‑grade hardware, as illustrated in the comparison table below.

The following table provides key metrics including training data size, inference latency, and GPU memory usage, enabling developers to assess suitability for their applications.

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