Ministral 3 8B
Parameters
8B
Context Length
256K
Modality
Multimodal
Architecture
Dense
License
Apache 2.0
Release Date
2 Dec 2025
Knowledge Cutoff
-
API Pricing (per 1M)
Input: $0.15 · Output: $0.15
System Requirements
VRAM requirements for different quantization methods and context sizes
1,024 tokens
Consumer
1x RTX 4090
24GB VRAM
Datacenter
1x NVIDIA A100
80GB VRAM
Apple Silicon
1x Apple M3 Max
128GB VRAM
256,000 tokens
Consumer
3x RTX 4090
24GB VRAM
Datacenter
1x NVIDIA A100
80GB VRAM
Apple Silicon
1x Apple M3 Max
128GB VRAM
Architecture Diagram
Evaluation Benchmarks
Rank
#155
| Benchmark | Score | Rank |
|---|---|---|
Graduate-Level QA | 0.668 | 83 |
Agentic Index | 0.01 | 110 |
Coding Index | 0.10 | 134 |
Intelligence Index | 0.04 | 224 |
General Knowledge Reference | 0.761 | 21 |
Rankings
Overall Rank
#155
Coding Rank
#125
About Ministral 3 8B
Ministral 3 8B is a multimodal edge foundation model from Mistral AI combining an 8.4B language decoder with an integrated vision encoder. It is optimized for on-device document understanding, structured JSON outputs, and agentic workflows.
Technical Specifications
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
Sliding Window Attention
No
Sliding Window Size
-
Sliding Window Ratio
-
Linear Attention
-
Linear Attention Ratio
-
Normalization
RMS Normalization
Activation Function
Swish
Dimensions
Hidden Dimension Size
4,096
Number of Layers
32
FFN Intermediate Size (Dense)
14,336
Multi-Token Prediction Heads
-
Tokenizer
Vocabulary Size
131,072
About Ministral 3
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.