What are the hardware requirements for Jan Code 4B?

Jan Code 4B requires approximately 8.9 GB of VRAM and supports a context window of 256K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Jan Code 4B and how large is it?

Jan Code 4B is developed by janhq, a model with 4b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

Where can I download or evaluate Jan Code 4B?

Jan Code 4B is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Jan Code 4B by janhq — VRAM 8.9GB, 256K context

Name: Jan Code 4B
Author: janhq

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: 0.25.

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 Parameters and Internals

LLM Name	Jan 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 Size	4b
Required VRAM	8.9 GB
Updated	2026-06-08
Maintainer	janhq
Model Type	qwen3
Instruction-Based	Yes
Model Files	5.0 GB: 1-of-2 3.9 GB: 2-of-2
Supported Languages	en
Model Architecture	Qwen3ForCausalLM
License	apache-2.0
Context Length	262144
Model Max Length	262144
Transformers Version	4.57.1
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	151936
Errors	replace

Rank the Jan Code 4B capabilities

Have you tried this model? Rate its performance — this feedback helps the ML community find the right model for their needs.

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

Best Alternatives to Jan Code 4B

Best Alternatives	Context / RAM	Downloads	Likes
FastContext 1.0 4B SFT	256K / 8.1 GB	5735	357
Qwen3 4B Instruct 2507	256K / 8.1 GB	3109972	911
Fable Traces	256K / 8.1 GB	375	210
FastContext 1.0 4B RL	256K / 8.1 GB	4559	61
Qwen3 4B Instruct 2507 FP8	256K / 5.2 GB	1100744	78
...pt Full Qwen3 4b Instruct 2507	256K / 8 GB	365	1
Nexa AI 4B Instruct	256K / 8 GB	576	2
Neuron 4B Instruct	256K / 8.1 GB	313	1
Agents K1	256K / 8.8 GB	1098	28
FastContext 1.0 4B SFT	256K / 8.1 GB	273	18

Note: green Score (e.g. "73.2") means that the model is better than janhq/Jan-code-4b.