What are the hardware requirements for GPT Oss 120B Distill Qwen3 4B Thinking?

GPT Oss 120B Distill Qwen3 4B Thinking requires approximately 8.1 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 GPT Oss 120B Distill Qwen3 4B Thinking and how large is it?

GPT Oss 120B Distill Qwen3 4B Thinking is developed by Jackrong, 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 GPT Oss 120B Distill Qwen3 4B Thinking?

GPT Oss 120B Distill Qwen3 4B Thinking is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

GPT Oss 120B Distill Qwen3 4B Thinking by Jackrong — VRAM 8.1GB, 256K context

Name: GPT Oss 120B Distill Qwen3 4B Thinking
Author: Jackrong

GPT Oss 120B Distill Qwen3 4B Thinking is an open-source language model by Jackrong. Features: 4b LLM, VRAM: 8.1GB, Context: 256K, License: apache-2.0, LLM Explorer Score: 0.21.

Base model:finetune:qwen/qwen3... Base model:qwen/qwen3-4b Dataset:jackrong/natural-reaso... Dataset:jackrong/sharegpt-gpt-... En Qwen3 Region:us Safetensors Sharded Tensorflow Zh

Model Card on HF 🤗: https://huggingface.co/Jackrong/gpt-oss-120b-Distill-Qwen3-4B-Thinking

GPT Oss 120B Distill Qwen3 4B Thinking Parameters and Internals

LLM Name	GPT Oss 120B Distill Qwen3 4B Thinking
Repository 🤗	https://huggingface.co/Jackrong/gpt-oss-120b-Distill-Qwen3-4B-Thinking
Base Model(s)	Qwen/Qwen3-4B Qwen/Qwen3-4B
Model Size	4b
Required VRAM	8.1 GB
Updated	2026-08-28
Maintainer	Jackrong
Model Type	qwen3
Model Files	5.0 GB: 1-of-2 3.1 GB: 2-of-2
Supported Languages	en zh
Model Architecture	Qwen3ForCausalLM
License	apache-2.0
Context Length	262144
Model Max Length	262144
Transformers Version	4.56.2
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|vision_pad\|>
Vocabulary Size	151936
Torch Data Type	bfloat16
Errors	replace

Rank the GPT Oss 120B Distill Qwen3 4B Thinking 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 GPT Oss 120B Distill Qwen3 4B Thinking

Best Alternatives	Context / RAM	Downloads	Likes
GRPO 4 70	256K / 8.1 GB	10	0
FastContext 1.0 4B SFT	256K / 8.1 GB	5735	357
Qwen3 4B Instruct 2507	256K / 8.1 GB	3109972	911
Lightning 4B	256K / 8.1 GB	13	6
Fable Traces	256K / 8.1 GB	333	210
Qwen3 4B Thinking 2507	256K / 8.1 GB	291023	606
FastContext 1.0 4B RL	256K / 8.1 GB	4559	61
Qwen3 4B Sft Prm	256K / 17.6 GB	602	0
...fetensors.chatgpt GPT Codex V2	256K / 8.1 GB	666	2
Qwen3 4B Instruct 2507 FP8	256K / 5.2 GB	1100744	78

Note: green Score (e.g. "73.2") means that the model is better than Jackrong/gpt-oss-120b-Distill-Qwen3-4B-Thinking.