Kimi-K2.6 Direct EXE Setup

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Kimi-K2.6 Direct EXE Setup

Docker offers the quickest path to setting up this model locally.

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.

💾 File hash: 1b9082519b7449cb3ef5051bba3dcf36 (Update date: 2026-06-26)
  • Processor: 4.0 GHz+ boost clock recommended for CPU inference
  • RAM: at least 32 GB in dual-channel mode for bandwidth
  • Disk Space:70 GB free space for full FP16 weights storage
  • Graphics: 12 GB VRAM minimum required for basic quantization

Kimi-K2.6 is a next‑generation language model that builds upon the successes of its predecessors with notable improvements in reasoning and multilingual capabilities. It employs a refined transformer architecture featuring sparse attention mechanisms that reduce computational load while preserving long‑range dependencies. The model was trained on an extensive corpus of over 5 trillion tokens, encompassing code, scientific literature, and diverse conversational data. With a parameter count of 180 billion and a context window of 8 K tokens, Kimi-K2.6 achieves state‑of‑the‑art performance across benchmark suites. The model specifications are summarized in the table below:

Parameters 180 B
Context Length 8 K tokens
Training Tokens 5 trillion
Architecture Transformer with sparse attention
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