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Ministral 3 14B VRAM Requirements

Developed by Mistral AI

Find out exactly how much VRAM you need to run Ministral 3 14B 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
Compatibility Verdict
Fits in GPU VRAM

This model's configuration fits fully in your VRAM. You will experience peak speed and performance.

Requires 10.39 GB total memory (weights: 8.37 GB, context overhead: 1.25 GB, activation overhead: 0.77 GB).

Memory Margin+4.11 GB

Ministral 3 14B Quantization Formats & VRAM Compatibility

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

QuantWeightsKV CacheOverheadTotal VRAMStatusLinks
Base (Unquantized)14.65 GB1.25 GB1.27 GB
17.17 GB
CPU Offload
HF weights
UD-Q4_K_XL8.37 GB1.25 GB0.77 GB
10.39 GB
Fits in VRAM
GGUF
UD-Q8_K_XL17.10 GB1.25 GB1.47 GB
19.82 GB
CPU Offload
GGUF

Ministral 3 14B KV Cache Memory Breakdown

How to Setup and Run Ministral 3 14B 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 Ministral 3 14B 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

  • DeveloperMistral AI
  • Parameter Count14B
  • Base File Size14.6 GB
  • AvailabilityLocal-Only
  • Input Modalities
    TextImage
  • Official SiteVisit site

Standard Benchmark Scores

Coding (SWE-bench Pro)N/A
Reasoning (GPQA Diamond)N/A

Commercial API Pricing

Input Tokens$0.20 / 1M
Output Tokens$0.20 / 1M

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