Jan-v3.5-4B is the first Jan personality: a 4-billion parameter fine-tuned variant of Jan-v3-4B-base-instruct, specialized in mathematical reasoning while incorporating a distinct conversational personality developed by Menlo Research.
This model enhances the base Qwen3-4B architecture with improved math problem-solving capabilities and a deliberately crafted identity. Rather than functioning as a neutral assistant, Jan-v3.5-4B uses casual, direct language with lowercase-by-default styling and maintains an authentic conversational tone.
View on Hugging Face →
Key Features
- Base architecture: Qwen3-4B with 36 layers and 4.0B parameters (3.6B non-embedding)
- Context length: 262,144 tokens natively supported
- Training focus: math reasoning datasets and curated identity/personality datasets
- Distinctive voice: self-aware humor, direct communication style, avoids corporate phrasing
- Attention mechanism: 32 query heads with 8 key-value heads (GQA)
Recommended Parameters
temperature: 0.7top_p: 0.8top_k: 20
Usage
Jan-v3.5-4B supports deployment via:
- Transformers library with pipeline or direct model loading
- vLLM server with tool-calling capabilities
- llama.cpp with quantized variants
- Jan Desktop application integration
Limitations & Scope
- Optimized specifically for math-heavy tasks over general purpose
- Personality training may not align with all use cases
- Intended as a starting point for downstream fine-tuning
