Devstral 2 123B Instruct
Parameters
-
Context Length
262K
Modality
Text
Architecture
Dense
License
Modified MIT
Release Date
1 Dec 2025
Knowledge Cutoff
-
API Pricing (per 1M)
Input: $0.00 · Output: $0.00
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
262,144 tokens
Consumer
5x RTX 4090
24GB VRAM
Datacenter
2x NVIDIA A100
80GB VRAM
Apple Silicon
1x Apple M3 Max
128GB VRAM
Architecture Diagram
Evaluation Benchmarks
Rank
#170
| Benchmark | Score | Rank |
|---|---|---|
Software Engineering | 0.54 | 28 |
StackUnseen | 0.364 | 30 |
Web Development | 1197 | 110 |
Agentic Index | 0.02 | 114 |
Coding Index | 0.31 | 116 |
Intelligence Index | 0.09 | 267 |
Rankings
Overall Rank
#170
Coding Rank
#117
About Devstral 2 123B Instruct
Devstral 2 123B Instruct is an agentic dense 123B parameter software engineering model from Mistral AI. It is optimized for multi-file codebase exploration, editing, and powering coding agents, with a 262k context window.
Technical Specifications
Attention
Attention Structure
Multi-Head Attention
Attention Heads
96
Key-Value Heads
8
Attention Head Dimension
128
Position Embedding
Absolute Position Embedding
RoPE Theta
1,000,000
Normalization
RMS Normalization
Activation Function
SwigLU
Dimensions
Hidden Dimension Size
12,288
Number of Layers
88
FFN Intermediate Size (Dense)
28,672
Tokenizer
Vocabulary Size
131,072
About Devstral 2
Devstral 2 is a family of developer-focused models from Mistral AI, optimized for multi-file software engineering tasks and coding agents.
Other Devstral 2 Models
- No related models available