What are the hardware requirements for Qwen3 4B Instruct 2507 FP8?

Qwen3 4B Instruct 2507 FP8 requires approximately 4.4 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 Instruct 2507 FP8 and how large is it?

Qwen3 4B Instruct 2507 FP8 is developed by unsloth, 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 Instruct 2507 FP8?

Qwen3 4B Instruct 2507 FP8 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Qwen3 4B Instruct 2507 FP8 by unsloth — VRAM 4.4GB, 256K context

Name: Qwen3 4B Instruct 2507 FP8
Author: unsloth

Qwen3 4B Instruct 2507 FP8 is an open-source language model by unsloth. Features: 4b LLM, VRAM: 4.4GB, Context: 256K, License: apache-2.0, Instruction-Based, LLM Explorer Score: 0.21.

Arxiv:2505.09388 Base model:quantized:qwen/qwen... Base model:qwen/qwen3-4b-instr... Conversational Endpoints compatible Fp8 Instruct Qwen3 Region:us Safetensors Unsloth

Model Card on HF 🤗: https://huggingface.co/unsloth/Qwen3-4B-Instruct-2507-FP8

Qwen3 4B Instruct 2507 FP8 Parameters and Internals

LLM Name	Qwen3 4B Instruct 2507 FP8
Repository 🤗	https://huggingface.co/unsloth/Qwen3-4B-Instruct-2507-FP8
Base Model(s)	Qwen3 4B Instruct 2507 FP8 Qwen/Qwen3-4B-Instruct-2507-FP8
Model Size	4b
Required VRAM	4.4 GB
Updated	2026-07-23
Maintainer	unsloth
Model Type	qwen3
Instruction-Based	Yes
Model Files	4.4 GB
Model Architecture	Qwen3ForCausalLM
License	apache-2.0
Context Length	262144
Model Max Length	262144
Transformers Version	4.57.1
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|vision_pad\|>
Vocabulary Size	151936
Torch Data Type	bfloat16
Errors	replace

Rank the Qwen3 4B Instruct 2507 FP8 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 Instruct 2507 FP8

Best Alternatives	Context / RAM	Downloads	Likes
FastContext 1.0 4B SFT	256K / 8.1 GB	5735	357
Qwen3 4B Instruct 2507	256K / 8.1 GB	3109972	911
Fable Traces	256K / 8.1 GB	578	210
FastContext 1.0 4B RL	256K / 8.1 GB	4559	61
Qwen3 4B Instruct 2507 FP8	256K / 5.2 GB	1100744	78
Neuron 4B Instruct	256K / 8.1 GB	313	1
Tac 1	256K / 8.1 GB	808	0
Nexa AI 4B Instruct	256K / 8 GB	576	2
Agents K1	256K / 8.8 GB	1098	28
FastContext 1.0 4B SFT	256K / 8.1 GB	273	18

Note: green Score (e.g. "73.2") means that the model is better than unsloth/Qwen3-4B-Instruct-2507-FP8.