What are the hardware requirements for Jan V3 4B Base Instruct 6bit?

Jan V3 4B Base Instruct 6bit requires approximately 3.3 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 6bit and how large is it?

Jan V3 4B Base Instruct 6bit is developed by mlx-community, 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 6bit?

Jan V3 4B Base Instruct 6bit 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 6bit by mlx-community — VRAM 3.3GB, 256K context

Name: Jan V3 4B Base Instruct 6bit
Author: mlx-community

Jan V3 4B Base Instruct 6bit is an open-source language model by mlx-community. Features: 4b LLM, VRAM: 3.3GB, Context: 256K, License: apache-2.0, Quantized, Instruction-Based, LLM Explorer Score: 0.22.

6-bit 6bit Base model:janhq/jan-v3-4b-bas... Base model:quantized:janhq/jan... Code Conversational En Instruct Mlx Quantized Qwen3 Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/mlx-community/Jan-v3-4B-base-instruct-6bit

Jan V3 4B Base Instruct 6bit Parameters and Internals

LLM Name	Jan V3 4B Base Instruct 6bit
Repository 🤗	https://huggingface.co/mlx-community/Jan-v3-4B-base-instruct-6bit
Base Model(s)	Jan V3 4B Base Instruct janhq/Jan-v3-4B-base-instruct
Model Size	4b
Required VRAM	3.3 GB
Updated	2026-08-10
Maintainer	mlx-community
Model Type	qwen3
Instruction-Based	Yes
Model Files	3.3 GB
Supported Languages	en
Quantization Type	6bit
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 6bit 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 V3 4B Base Instruct 6bit

Best Alternatives	Context / RAM	Downloads	Likes
Qwen3 4b Merged Txt	256K / 8.1 GB	535	0
...Instruct 2507 Unsloth Bnb 4bit	256K / 3.5 GB	155962	14
...wen 3 4b Mythos Finetune 16bit	256K / 8.1 GB	92	0
Qwen3 4B Instruct 2507 4bit	256K / 2.3 GB	40955	11
Qwen3 4B INST Code	256K / 8.1 GB	25	0
Qwen3 4B INST Math	256K / 8.1 GB	18	0
...Instruct Haiku 4.5 Merged FP16	256K / 8.1 GB	16	1
Agent 4b	256K / 8.1 GB	16	0
...wen3 4B Instruct 2507 Bnb 4bit	256K / 2.6 GB	6833	5
Jan V3 4B Base Instruct 4bit	256K / 2.3 GB	279	2

Note: green Score (e.g. "73.2") means that the model is better than mlx-community/Jan-v3-4B-base-instruct-6bit.