What are the hardware requirements for Qwen3 4B Concise Merged?

Qwen3 4B Concise Merged requires approximately 8.1 GB of VRAM and supports a context window of 40K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Qwen3 4B Concise Merged and how large is it?

Qwen3 4B Concise Merged is developed by cykai168, 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 Qwen3 4B Concise Merged?

Qwen3 4B Concise Merged is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Qwen3 4B Concise Merged by cykai168 — VRAM 8.1GB, 40K context

Name: Qwen3 4B Concise Merged
Author: cykai168

Qwen3 4B Concise Merged is an open-source language model by cykai168. Features: 4b LLM, VRAM: 8.1GB, Context: 40K, License: apache-2.0, Quantized, LLM Explorer Score: 0.28.

4bit Base model:finetune:unsloth/qw... Base model:unsloth/qwen3-4b-un... Conversational En Endpoints compatible Quantized Qwen3 Region:us Safetensors Sharded Tensorflow Unsloth

Model Card on HF 🤗: https://huggingface.co/cykai168/qwen3-4b-concise-merged

Qwen3 4B Concise Merged Parameters and Internals

LLM Name	Qwen3 4B Concise Merged
Repository 🤗	https://huggingface.co/cykai168/qwen3-4b-concise-merged
Base Model(s)	Qwen3 4B Unsloth Bnb 4bit unsloth/Qwen3-4B-unsloth-bnb-4bit
Model Size	4b
Required VRAM	8.1 GB
Updated	2026-07-26
Maintainer	cykai168
Model Type	qwen3
Model Files	5.0 GB: 1-of-2 3.1 GB: 2-of-2
Supported Languages	en
Quantization Type	4bit
Model Architecture	Qwen3ForCausalLM
License	apache-2.0
Context Length	40960
Model Max Length	40960
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|vision_pad\|>
Vocabulary Size	151936
Torch Data Type	bfloat16
Errors	replace

Rank the Qwen3 4B Concise Merged 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 Qwen3 4B Concise Merged

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	106344	17
Mini Coder 4B OptiQ 4bit	256K / 3 GB	310	1
Qwen3.8 4B Distilled	256K / 8.1 GB	90	0
...wen3 4B Thinking 2507 MLX 4bit	256K / 2.3 GB	53225	14
FastContext 1.0 4B SFT 8bit	256K / 4.3 GB	120	1
...wen3 4B Thinking 2507 MLX 8bit	256K / 4.3 GB	44731	8
Qwen3 4B Instruct 2507 4bit	256K / 2.3 GB	40955	11
...wen 3 4b Mythos Finetune 16bit	256K / 8.1 GB	92	0
EduMentor Qwen3 4B FP16	256K / 8.1 GB	75	1

Note: green Score (e.g. "73.2") means that the model is better than cykai168/qwen3-4b-concise-merged.