Quick Run Kimi-K2.5 Locally via LM Studio Zero Config

Running this model locally is fastest when deployed through Docker.

Please follow the instructions listed below to get started.

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

Once launched, the setup wizard will detect your specs to configure the model for maximum efficiency.

📦 Hash-sum → fe6d7d5ad46a00c2987469eda6526d05 | 📌 Updated on 2026-06-28



  • Processor: next-gen chip for heavy context processing
  • RAM: required: 16 GB absolute minimum for small models
  • Disk Space:70 GB free space for full FP16 weights storage
  • Graphics: CUDA Compute Capability 8.0+ required for flash-attention

Kimi-K2.5 is a next‑generation language model that leverages a hybrid architecture combining transformer-based attention with sparse gating mechanisms. It achieves state‑of‑the‑art performance on reasoning, coding, and multilingual tasks while maintaining a compact footprint for deployment. The model incorporates advanced quantization techniques and a novel attention‑sparsification algorithm that reduces computational load by up to 40% without sacrificing accuracy. Kimi-K2.5 also features an enhanced safety layer that dynamically adapts content filters based on contextual cues, ensuring responsible AI behavior. These innovations make Kimi-K2.5 suitable for both enterprise‑scale applications and edge devices, offering developers a versatile tool for building intelligent systems. Below is a quick overview of its core technical specifications.

Parameter Value
Parameters 180B
Context length 8K tokens
Training data 2.5TB
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