Ministral 3 8B VRAM Requirements
Developed by Mistral AI
Find out exactly how much VRAM you need to run Ministral 3 8B 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.
Hardware Configuration
Adjust settings to check compatibility with your system in real time.
Available: 14.50 GB
Available: 29.00 GB
This model's configuration fits fully in your VRAM. You will experience peak speed and performance.
Requires 6.86 GB total memory (weights: 5.29 GB, context overhead: 1.06 GB, activation overhead: 0.51 GB).
Ministral 3 8B Quantization Formats & VRAM Compatibility
Select a format to set it as active and calculate your system fit dynamically.
| Quant | Weights | KV Cache | Overhead | Total VRAM | Status | Links |
|---|---|---|---|---|---|---|
| Base (Unquantized) | 9.70 GB | 1.06 GB | 0.86 GB | 11.63 GB | Fits in VRAM | HF weights |
| UD-Q4_K_XL | 5.29 GB | 1.06 GB | 0.51 GB | 6.86 GB | Fits in VRAM | GGUF |
| UD-Q8_K_XL | 11.10 GB | 1.06 GB | 0.97 GB | 13.14 GB | Fits in VRAM | GGUF |
Ministral 3 8B KV Cache Memory Breakdown
How to Setup and Run Ministral 3 8B Locally
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>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 8B 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 Count8B
- Base File Size9.7 GB
- AvailabilityAPI & Local
- Input ModalitiesTextImage
- Official SiteVisit site
Standard Benchmark Scores
Commercial API Pricing
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