What are the hardware requirements for Qwen3 4B Finetune Merged 4bit?

Qwen3 4B Finetune Merged 4bit requires approximately 3.5 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 Qwen3 4B Finetune Merged 4bit and how large is it?

Qwen3 4B Finetune Merged 4bit is developed by bibihhehe, 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 Finetune Merged 4bit?

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

Qwen3 4B Finetune Merged 4bit by bibihhehe — VRAM 3.5GB, 256K context

Name: Qwen3 4B Finetune Merged 4bit
Author: bibihhehe

Qwen3 4B Finetune Merged 4bit is an open-source language model by bibihhehe. Features: 4b LLM, VRAM: 3.5GB, Context: 256K, License: apache-2.0, Quantized, Fine-Tuned, Merged, LLM Explorer Score: 0.23.

Merged Model 4-bit 4bit Base model:bibihhehe/qwen3 4b ... Base model:quantized:bibihhehe... Bitsandbytes Conversational En Endpoints compatible Finetuned Quantized Qwen3 Region:us Safetensors Unsloth

Model Card on HF 🤗: https://huggingface.co/bibihhehe/qwen3_4B_finetune_merged_4bit

Qwen3 4B Finetune Merged 4bit Parameters and Internals

LLM Name	Qwen3 4B Finetune Merged 4bit
Repository 🤗	https://huggingface.co/bibihhehe/qwen3_4B_finetune_merged_4bit
Base Model(s)	Qwen3 4B Finetune Merged 4bit bibihhehe/qwen3_4B_finetune_merged_4bit
Merged Model	Yes
Model Size	4b
Required VRAM	3.5 GB
Updated	2026-08-08
Maintainer	bibihhehe
Model Type	qwen3
Model Files	3.5 GB
Supported Languages	en
Quantization Type	4bit
Model Architecture	Qwen3ForCausalLM
License	apache-2.0
Context Length	262144
Model Max Length	262144
Transformers Version	4.56.2
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|PAD_TOKEN\|>
Vocabulary Size	151936
Torch Data Type	float16
Errors	replace

Rank the Qwen3 4B Finetune Merged 4bit 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 Qwen3 4B Finetune Merged 4bit

Model	Likes	Downloads	VRAM
Qwen3 4B Finetune Merged 4bit	0	9	3 GB

Best Alternatives to Qwen3 4B Finetune Merged 4bit

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	100656	17
Mini Coder 4B OptiQ 4bit	256K / 3 GB	310	1
...wen3 4B Thinking 2507 MLX 4bit	256K / 2.3 GB	53225	14
Qwen3.8 4B Distilled	256K / 8.1 GB	90	0
...wen3 4B Thinking 2507 MLX 8bit	256K / 4.3 GB	44731	8
Qwen3 4B Instruct 2507 4bit	256K / 2.3 GB	40955	11
FastContext 1.0 4B SFT 8bit	256K / 4.3 GB	120	1
...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 bibihhehe/qwen3_4B_finetune_merged_4bit.