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Jan Code 4B by janhq

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Jan Code 4B is an open-source language model by janhq. Features: 4b LLM, VRAM: 8.9GB, Context: 256K, License: apache-2.0, Instruction-Based, LLM Explorer Score: 0.28.

  Agent Base model:finetune:janhq/jan-... Base model:janhq/jan-v3-4b-bas...   Conversational   Deploy:azure   En   Endpoints compatible   Instruct   Qwen3   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/janhq/Jan-code-4b 

Jan Code 4B Benchmarks

LLME Score: 0.27512
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Jan Code 4B (janhq/Jan-code-4b)
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Jan Code 4B Parameters and Internals

LLM NameJan Code 4B
Repository 🤗https://huggingface.co/janhq/Jan-code-4b 
Base Model(s)  Jan V3 4B Base Instruct   janhq/Jan-v3-4B-base-instruct
Model Size4b
Required VRAM8.9 GB
Updated2026-06-08
Maintainerjanhq
Model Typeqwen3
Instruction-BasedYes
Model Files  5.0 GB: 1-of-2   3.9 GB: 2-of-2
Supported Languagesen
Model ArchitectureQwen3ForCausalLM
Licenseapache-2.0
Context Length262144
Model Max Length262144
Transformers Version4.57.1
Tokenizer ClassQwen2Tokenizer
Padding Token<|endoftext|>
Vocabulary Size151936
Errorsreplace

Best Alternatives to Jan Code 4B

Best Alternatives
Context / RAM
Downloads
Likes
FastContext 1.0 4B SFT256K / 8.1 GB5735357
FastContext 1.0 4B RL256K / 8.1 GB455961
Qwen3 4B Instruct 2507256K / 8.1 GB5455321886
Qwen3 4B Instruct 2507 FP8256K / 5.2 GB84028179
Agents K1256K / 8.8 GB60120
CyberSecQwen 4B256K / 8 GB61614
Qwen3 4B Elderly Sft Merged256K / 8.1 GB3780
Qwen3 4B DASD 32K256K / 8 GB850
Qwen3 4B Instruct 2507256K / 8.1 GB4128426
Jan V3.5 4B256K / 8.9 GB45716
Note: green Score (e.g. "73.2") means that the model is better than janhq/Jan-code-4b.

Rank the Jan Code 4B Capabilities

🆘 Have you tried this model? Rate its performance. This feedback would greatly assist ML community in identifying the most suitable model for their needs. Your contribution really does make a difference! 🌟

Instruction Following and Task Automation  
Factuality and Completeness of Knowledge  
Censorship and Alignment  
Data Analysis and Insight Generation  
Text Generation  
Text Summarization and Feature Extraction  
Code Generation  
Multi-Language Support and Translation  

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