Launch Kimi-K2.5-NVFP4 Full Speed NPU Mode 5-Minute Setup

The fastest way to get this model running locally is via Optional Features.

Follow the guidelines below to continue.

The framework seamlessly downloads the massive neural network binaries.

There is no manual tuning required; the builder deploys the best matching configuration.

🔐 Hash sum: e95b03011478ad2e51bb5cf65fbefe17 | 📅 Last update: 2026-07-02 Verify Processor: 6-core 3.5 GHz minimum required RAM: enough space for background apps and OS overhead Disk Space: 80 GB NVMe SSD required for fast model weights loading Graphics: 12 GB VRAM minimum required for basic quantization

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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