👁 Mistral
Mistral
Ministral 3 14B
Frontier
105.9KDownloads294LikesOct 2025Released262K tokensContextApache 2.0License82 StrongQuality
Ministral 3 14B (14B parameters) requires approximately 14.0 GB of VRAM with Q4_K_M quantization. For the best balance of quality and speed, we recommend hardware with at least 17 GB of VRAM.
Get started
— copy & paste to run locallyCopy-paste commands to run Ministral 3 14B on your machine.
Run
docker run --rm -it ghcr.io/ggerganov/llama.cpp:full \
--hf-repo "mistralai/Ministral-3-14B-Instruct-2512" \
--hf-file "Ministral-3-14B-Instruct-2512-Q4_K_M.gguf" \
-c 4096 -ngl 99Quick specs
Parameters14B
Architecturemultimodal
Context262K tokens
Modalitytext+vision
Min RAM5.5 GB
Rec. RAM8.5 GB (Q4_K_M)
LicenseApache 2.0
FamilyMinistral
✓ Vision✓ Chat
About this model
- •13.5B Language Model
- •0.4B Vision Encoder
- •Vision: Enables the model to analyze images and provide insights based on visual content, in addition to text
- •Multilingual: Supports dozens of languages, including English, French, Spanish, German, Italian, Portuguese, Dutch, Chinese, Japanese, Korean, Arabic
- •System Prompt: Maintains strong adherence and support for system prompts
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Quantization options
VRAM estimates by quant level
No hardware detected — fit column shows raw VRAM estimates
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 5.5 GB | Low | — |
Q3_K_S | 3 | 6.9 GB | Low | — |
NVFP4 | 4 | 7.8 GB | Medium | — |
Q4_K_M | 4 | 8.5 GB | Medium | — |
Q5_K_M | 5 | 10.1 GB | High | — |
Q6_K | 6 | 11.5 GB | High | — |
Q8_0 | 8 | 15.0 GB | Very High | — |
F16 | 16 | 28.7 GB | Maximum | — |
Quality benchmarks
Ministral 3 14B benchmark scores
Reasoning
MMLU-Pro—
GPQA Diamond39.9%
MATH-500—
ARC Challenge89.9%
Source: official · 2025-12-01
Hardware compatibility
Fit estimates across all hardware
Computing compatibility...
Memory breakdown
Reference: RTX 2060 6GB
Weights8.5 GB
KV Cache2.4 GB
Runtime2.4 GB
Headroom0.6 GB
Frequently asked questions
FAQ — Ministral 3 14B
See also