Mellum 2.1 12B A2.5B Thinking
Active Parameters
12B
Context Length
131K
Modality
Text
Architecture
Mixture of Experts (MoE)
License
Apache 2.0
Release Date
20 Sept 2026
Knowledge Cutoff
-
API Pricing (per 1M)
Self-hosted only
System Requirements
VRAM requirements for different quantization methods and context sizes
1,024 tokens
Consumer
2x RTX 4090
24GB VRAM
Datacenter
1x NVIDIA A100
80GB VRAM
Apple Silicon
1x Apple M3 Max
128GB VRAM
131,072 tokens
Consumer
2x RTX 4090
24GB VRAM
Datacenter
1x NVIDIA A100
80GB VRAM
Apple Silicon
1x Apple M3 Max
128GB VRAM
Architecture Diagram
Evaluation Benchmarks
No evaluation benchmarks for Mellum 2.1 12B A2.5B Thinking available.
Rankings
Overall Rank
-
Coding Rank
-
About Mellum 2.1 12B A2.5B Thinking
Mellum 2.1 12B A2.5B Thinking is an MoE reasoning and coding model developed by JetBrains with 2.5B active parameters per token. It is tailored for advanced reasoning traces and software engineering workflows in IDE environments.
Technical Specifications
Attention
Attention Structure
Grouped-Query Attention
Attention Heads
32
Key-Value Heads
4
Attention Head Dimension
128
Position Embedding
ROPE
RoPE Theta
500,000
Sliding Window Attention
Yes
Sliding Window Size
1,024
Sliding Window Ratio
75.0%
Linear Attention
No
Linear Attention Ratio
-
Normalization
RMS Normalization
Activation Function
SwigLU
Dimensions
Auxiliary Parameters
-
Hidden Dimension Size
2,304
Number of Layers
28
FFN Intermediate Size (Dense)
7,168
Multi-Token Prediction Heads
-
Tokenizer
Vocabulary Size
98,304
Mixture of Experts
Total Expert Parameters
2.5B
Number of Experts
64
Active Experts
8
Shared Experts
0
FFN Intermediate Size (per Expert)
896
Dense Layers Before MoE
0
Resources
About Mellum
The Mellum model family developed by JetBrains.
Other Mellum Models
- No related models available