What are the hardware requirements for Jan V3 4B Base Instruct?

Jan V3 4B Base Instruct 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 V3 4B Base Instruct and how large is it?

Jan V3 4B Base Instruct 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 V3 4B Base Instruct?

Jan V3 4B Base Instruct is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Jan V3 4B Base Instruct by janhq — VRAM 8.9GB, 256K context

Name: Jan V3 4B Base Instruct
Author: janhq

Jan V3 4B Base Instruct 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: 0.24.

Base model:finetune:qwen/qwen3... Base model:qwen/qwen3-4b-instr... Code Conversational En Endpoints compatible Instruct Qwen3 Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/janhq/Jan-v3-4B-base-instruct

Jan V3 4B Base Instruct Parameters and Internals

LLM Name	Jan V3 4B Base Instruct
Repository 🤗	https://huggingface.co/janhq/Jan-v3-4B-base-instruct
Base Model(s)	Qwen3 4B Instruct 2507 Qwen/Qwen3-4B-Instruct-2507
Model Size	4b
Required VRAM	8.9 GB
Updated	2026-07-30
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 V3 4B Base Instruct 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

Quantized Models of the Jan V3 4B Base Instruct

Model	Likes	Downloads	VRAM
Jan V3 4B Base Instruct 4bit	2	279	2 GB
Jan V3 4B Base Instruct 8bit	3	59	4 GB
Jan V3 4B Base Instruct 6bit	1	18	3 GB

Best Alternatives to Jan V3 4B Base Instruct

Best Alternatives	Context / RAM	Downloads	Likes
Oc E Non V1	256K / 8 GB	947	21
Qwen3 4B Instruct 2507	256K / 8.1 GB	3109972	911
FastContext 1.0 4B SFT	256K / 8.1 GB	5735	357
SRA RiskGate 4B	256K / 8 GB	2662	1
Qwen3 4B Instruct 2507 FP8	256K / 5.2 GB	1100744	78
Dwight 4B	256K / 8.1 GB	374	10
FastContext 1.0 4B RL	256K / 8.1 GB	4559	61
...orm3200 Impl Verl S11 Step 039	256K / 8.1 GB	645	1
...n3 4B Instruct 2507 Malevolent	256K / 8.1 GB	166	1
Kanso Satori 1.0 Bf16	256K / 8 GB	408	0

Note: green Score (e.g. "73.2") means that the model is better than janhq/Jan-v3-4B-base-instruct.