Parameters
24B
Context Length
128K
Modality
Text
Architecture
Dense
KV Cache Rate
128 KB/tok
License
Apache 2.0
Release Date
10 Jun 2025
Knowledge Cutoff
Oct 2023
API Pricing (per 1M)
Input: $0.50 · Output: $1.50
Precision
Context
Workload Memory: 14.68 GB
INT4 · 8K context
Base Weights: 11.18 GB
KV Cache: 1.00 GB
Runtime & Graphs: 2.50 GB
1x NVIDIA L4 24GB
14.7 / 21.6 GB usable
2x RTX 4090 24GB
14.7 / 43.2 GB usable · TP 2
Apple M4 24GB
14.7 / 18.0 GB usable
Determine requirements for your specific workload:
Open in VRAM Calculator
Rank
#175
| Benchmark | Score | Rank |
|---|---|---|
StackUnseen | 0.346 | 30 |
Graduate-Level QA | 0.682 | 88 |
Coding Index | 0.15 | 139 |
Intelligence Index | 0.09 | 253 |
Overall Rank
#175
Coding Rank
#130
Magistral Small is an open-source 24B multimodal reasoning model developed by Mistral AI, engineered for transparent, traceable multi-step logic. It supports multilingual reasoning across 24+ languages and native function calling for agentic AI.
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
Hidden Dimension Size
14,336
Number of Layers
32
FFN Intermediate Size (Dense)
32,768
Tokenizer
Vocabulary Size
131,072
Magistral is Mistral AI's first reasoning model series, purpose-built for transparent, step-by-step reasoning with native multilingual capabilities. Features chain-of-thought reasoning in the user's language with traceable thought processes. Excels in domain-specific problems requiring multi-step logic, from legal research and financial forecasting to software development and creative storytelling. Supports reasoning across numerous languages including English, French, Spanish, German, Italian, Arabic, Russian, and Chinese.