Mistral-7B-Instruct-v0.1
Parameters
7.3B
Context Length
8K
Modality
Text
Architecture
Dense
License
Apache 2.0
Release Date
27 Sept 2023
Knowledge Cutoff
-
API Pricing (per 1M)
Input: $0.25 · Output: $0.25
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
8,192 tokens
Consumer
1x RTX 4090
24GB VRAM
Datacenter
1x NVIDIA A100
80GB VRAM
Apple Silicon
1x Apple M3 Max
128GB VRAM
Architecture Diagram
Evaluation Benchmarks
Rank
#190
| Benchmark | Score | Rank |
|---|---|---|
General Text | 1110 | 155 |
Intelligence Index | 0.05 | 261 |
Rankings
Overall Rank
#190
Coding Rank
-
About Mistral-7B-Instruct-v0.1
Mistral-7B-Instruct-v0.1 is Mistral AI's foundational instruction-tuned model engineered for efficient conversational assistance and question answering. It incorporates Sliding-Window Attention and Grouped-Query Attention for fast inference.
Technical Specifications
Attention
Attention Structure
Grouped-Query Attention
Attention Heads
32
Key-Value Heads
8
Attention Head Dimension
-
Position Embedding
ROPE
RoPE Theta
10,000
Sliding Window Attention
Yes
Sliding Window Size
4,096
Sliding Window Ratio
-
Linear Attention
-
Linear Attention Ratio
-
Normalization
RMS Normalization
Activation Function
SwigLU
Dimensions
Hidden Dimension Size
4,096
Number of Layers
32
FFN Intermediate Size (Dense)
14,336
Multi-Token Prediction Heads
-
Tokenizer
Vocabulary Size
32,000
About Mistral 7B
Mistral 7B, a 7.3 billion parameter model, utilizes a decoder-only transformer architecture. It features Sliding Window Attention and Grouped Query Attention for efficient long sequence processing. A Rolling Buffer Cache optimizes memory use, contributing to its design for efficient language processing.