Parameters
14B
Context Length
256K
Modality
Multimodal
Auxiliary Parameters
400M
Architecture
Dense
KV Cache Rate
160 KB/tok
License
Apache 2.0
Release Date
2 Dec 2025
Knowledge Cutoff
Jun 2025
API Pricing (per 1M)
Input: $0.20 · Output: $0.20
Precision
Context
Workload Memory: 10.27 GB
INT4 · 8K context
Base Weights: 6.52 GB
KV Cache: 1.25 GB
Runtime & Graphs: 2.50 GB
1x NVIDIA L4 24GB
10.3 / 21.6 GB usable
1x RTX 3060 12GB
10.3 / 10.8 GB usable
Apple M4 24GB
10.3 / 18.0 GB usable
Determine requirements for your specific workload:
Open in VRAM Calculator
Rank
#180
| Benchmark | Score | Rank |
|---|---|---|
Graduate-Level QA | 0.712 | 83 |
Agentic Index | 0.01 | 113 |
Coding Index | 0.14 | 141 |
Intelligence Index | 0.06 | 294 |
General Knowledge Reference | 0.794 | 20 |
Overall Rank
#180
Coding Rank
#145
Ministral 3 14B is a dense multimodal model by Mistral AI engineered via cascade distillation for enterprise edge hardware and private deployments. It delivers advanced reasoning, function calling, and multilingual fluency over a 256K context window.
Attention
Attention Structure
Multi-Head Attention
Attention Heads
32
Key-Value Heads
8
Attention Head Dimension
128
Position Embedding
Absolute Position Embedding
RoPE Theta
1,000,000,000
Normalization
RMS Normalization
Activation Function
SwigLU
Dimensions
Auxiliary Parameters
400M
Hidden Dimension Size
5,120
Number of Layers
40
FFN Intermediate Size (Dense)
16,384
Tokenizer
Vocabulary Size
131,072
Ministral 3 is a family of efficient edge models with vision capabilities, available in 3B, 8B, and 14B parameter sizes. Designed for edge deployment with multimodal and multilingual support, offering best-in-class performance for resource-constrained environments.