Mistral-7B-Instruct-v0.1
Parameters
7.3B
Context Length
8K
Modality
Text
Architecture
Dense
KV Cache Rate
128 KB/tok
License
Apache 2.0
Release Date
27 Sept 2023
Knowledge Cutoff
-
API Pricing (per 1M)
Input: $0.07 · Output: $0.28
Hardware Sizing
Precision
Context
Workload Memory: 6.90 GB
INT4 · 8K context
Base Weights: 3.40 GB
KV Cache: 1.00 GB
Runtime & Graphs: 2.50 GB
Minimum Required Hardware
1x NVIDIA L4 24GB
6.9 / 21.6 GB usable
1x RTX 3060 12GB
6.9 / 10.8 GB usable
Apple M4 24GB
6.9 / 18.0 GB usable
Determine requirements for your specific workload:
Open in VRAM Calculator
Architecture Diagram
Evaluation Benchmarks
Rank
#228
| Benchmark | Score | Rank |
|---|---|---|
General Text | 1111 | 182 |
Intelligence Index | 0.05 | 313 |
Rankings
Overall Rank
#228
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
Position Embedding
ROPE
RoPE Theta
10,000
Sliding Window Attention
Yes
Sliding Window Size
4,096
Normalization
RMS Normalization
Activation Function
SwigLU
Dimensions
Hidden Dimension Size
4,096
Number of Layers
32
FFN Intermediate Size (Dense)
14,336
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.