What are the hardware requirements for Jan Nano 128K?

Jan Nano 128K requires approximately 8.1 GB of VRAM and supports a context window of 128K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Jan Nano 128K and how large is it?

Jan Nano 128K is developed by Menlo, 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 Nano 128K?

Jan Nano 128K is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Jan Nano 128K by Menlo — VRAM 8.1GB, 128K context

Name: Jan Nano 128K
Author: Menlo

Jan Nano 128K is an open-source language model by Menlo. Features: 4b LLM, VRAM: 8.1GB, Context: 128K, License: apache-2.0, LLM Explorer Score: 0.28.

Arxiv:2506.22760 Base model:finetune:menlo/jan-... Base model:menlo/jan-nano Conversational En Endpoints compatible Qwen3 Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/Menlo/Jan-nano-128k

Jan Nano 128K Benchmarks

LLME Score: 0.27937

^nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").

What is the LLM Explorer Rank (Score)

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Jan Nano 128K Parameters and Internals

LLM Name	Jan Nano 128K
Repository 🤗	https://huggingface.co/Menlo/Jan-nano-128k
Base Model(s)	Jan Nano Menlo/Jan-nano
Model Size	4b
Required VRAM	8.1 GB
Updated	2026-07-07
Maintainer	Menlo
Model Type	qwen3
Model Files	5.0 GB: 1-of-2 3.1 GB: 2-of-2
Supported Languages	en
Model Architecture	Qwen3ForCausalLM
License	apache-2.0
Context Length	131072
Model Max Length	131072
Transformers Version	4.52.4
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	151936
Torch Data Type	bfloat16
Errors	replace

Quantized Models of the Jan Nano 128K

Model	Likes	Downloads	VRAM
Jan Nano 128K 4bit	2	25	2 GB

Best Alternatives to Jan Nano 128K

Best Alternatives	Context / RAM	Downloads	Likes
FastContext 1.0 4B SFT	256K / 8.1 GB	5735	357
Fable Traces	256K / 8.1 GB	277	157
Qwen3 4B Instruct 2507	256K / 8.1 GB	5376006	894
GRPO 4 70	256K / 8.1 GB	5	0
FastContext 1.0 4B RL	256K / 8.1 GB	4559	61
Qwen3 4B Thinking 2507	256K / 8.1 GB	529167	601
Lightning 4B	256K / 8.1 GB	13	6
Nexa AI 4B Instruct	256K / 8 GB	274	2
Qwen3 4B Instruct 2507 FP8	256K / 5.2 GB	964481	78
Tac 1	256K / 8.1 GB	635	0

Note: green Score (e.g. "73.2") means that the model is better than Menlo/Jan-nano-128k.

Rank the Jan Nano 128K 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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Jan Nano 128K by Menlo