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Kimi K2.7 Code VRAM Requirements

Developed by Moonshot AI (Kimi)

Find out exactly how much VRAM you need to run Kimi K2.7 Code locally. Calculate the memory footprint of different GGUF quantization variants (like Q4_K_M or Q8_0), estimate your context length KV cache VRAM footprint, and determine if your hardware supports a full GPU VRAM offload or if you will need to rely on slow partial CPU offloading to avoid a CUDA Out of Memory (OOM) error.

Hugging Face Repository

Hardware Configuration

Adjust settings to check compatibility with your system in real time.

GB VRAM

Available: 14.50 GB

GB RAM

Available: 29.00 GB

8,192 tokens
CPU Offloading
MLA Engine Mode
Compatibility Verdict
Out of Memory Risk

This configuration exceeds your system's usable memory capacity. Attempting to run it will cause crashes or freeze your machine.

Requires 631.30 GB total memory (weights: 584.00 GB, context overhead: 0.54 GB, activation overhead: 46.76 GB).

Memory Margin-587.80 GB

Kimi K2.7 Code Quantization Formats & VRAM Compatibility

Select a format to set it as active and calculate your system fit dynamically.

QuantWeightsKV CacheOverheadTotal VRAMStatusLinks
Base (Unquantized)554.27 GB0.54 GB44.38 GB
599.20 GB
Too Large
HF weights
UD-Q4_K_XL584.00 GB0.54 GB46.76 GB
631.30 GB
Too Large
GGUF
UD-Q8_K_XL595.00 GB0.54 GB47.64 GB
643.18 GB
Too Large
GGUF

Kimi K2.7 Code KV Cache Memory Breakdown

How to Setup and Run Kimi K2.7 Code Locally

1

Method A: Ollama (Recommended)

Ollama is the easiest way to run models in the background. First, download it from ollama.com, then execute this terminal command:

ollama run <model-name>
2

Method B: LM Studio (GUI)

If you prefer a full graphical interface with chat UI and local server hosting:

  • Download and install LM Studio.
  • Search for Kimi K2.7 Code in the home page search tab.
  • Select a quantization level (like Q4_K_M) that fits your VRAM, click download, and load it to chat.

Model Specs

  • DeveloperMoonshot AI (Kimi)
  • Parameter Count1000B
  • Base File Size554.3 GB
  • AvailabilityAPI & Local
  • Input Modalities
    TextImageVideo
  • Official SiteVisit site

Standard Benchmark Scores

Coding (SWE-bench Pro)58.6%
Reasoning (GPQA Diamond)90%

Commercial API Pricing

Input Tokens$0.95 / 1M
Output Tokens$4.00 / 1M

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