Arete 27B
Parameters
27B
Context Length
262K
Modality
Text
Architecture
Dense
KV Cache Rate
256 KB/tok
License
Apache 2.0
Release Date
6 Nov 2026
Knowledge Cutoff
-
API Pricing (per 1M)
Self-hosted only
Hardware Sizing
Precision
Context
Workload Memory: 17.07 GB
INT4 · 8K context
Base Weights: 12.57 GB
KV Cache: 2.00 GB
Runtime & Graphs: 2.50 GB
Minimum Required Hardware
1x NVIDIA L4 24GB
17.1 / 21.6 GB usable
2x RTX 4090 24GB
17.1 / 43.2 GB usable · TP 2
Apple M4 24GB
17.1 / 18.0 GB usable
Determine requirements for your specific workload:
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Architecture Diagram
Evaluation Benchmarks
No evaluation benchmarks for Arete 27B available.
Rankings
Overall Rank
-
Coding Rank
-
About Arete 27B
Arete 27B is an open-weights LLM developed by Nous Research, trained on high-quality synthetic and curated reasoning data. It is optimized for complex logical deduction, agentic tasks, and coding benchmarks.
Technical Specifications
Attention
Attention Structure
Grouped-Query Attention
Attention Heads
24
Key-Value Heads
4
Attention Head Dimension
256
Position Embedding
ROPE
RoPE Theta
10,000,000
Linear Attention
Yes
Linear Attention Ratio
75.0%
Normalization
RMS Normalization
Activation Function
SwigLU
Dimensions
Hidden Dimension Size
5,120
Number of Layers
64
FFN Intermediate Size (Dense)
17,408
Multi-Token Prediction Heads
0
Tokenizer
Vocabulary Size
248,320
Resources
About Arete
The Arete model family developed by Nous Research.
Other Arete Models
- No related models available