Mistral-7B-Instruct-v0.2
Parameters
7.3B
Context Length
33K
Modality
Text
Architecture
Dense
License
Apache 2.0
Release Date
15 Jan 2024
Knowledge Cutoff
Dec 2023
API Pricing (per 1M)
Input: $0.20 · Output: $0.20
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
32,768 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
#216
| Benchmark | Score | Rank |
|---|---|---|
General Text | 1149 | 176 |
Rankings
Overall Rank
#216
Coding Rank
-
About Mistral-7B-Instruct-v0.2
Mistral-7B-Instruct-v0.2 is an enhanced open-weights instruction model from Mistral AI with full attention across an expanded 32K context window. It delivers reliable prompt adherence and low-latency text generation for general NLP workloads.
Technical Specifications
Attention
Attention Structure
Grouped-Query Attention
Attention Heads
32
Key-Value Heads
8
Attention Head Dimension
-
Position Embedding
ROPE
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
Auxiliary Parameters
-
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.