What are the hardware requirements for Scope Guard 4B Q 2601?

Scope Guard 4B Q 2601 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 Scope Guard 4B Q 2601 and how large is it?

Scope Guard 4B Q 2601 is developed by principled-intelligence, 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 Scope Guard 4B Q 2601?

Scope Guard 4B Q 2601 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Scope Guard 4B Q 2601 by principled-intelligence — VRAM 8.1GB, 256K context

Name: Scope Guard 4B Q 2601
Author: principled-intelligence

Scope Guard 4B Q 2601 is an open-source language model by principled-intelligence. Features: 4b LLM, VRAM: 8.1GB, Context: 256K, License: apache-2.0, Instruction-Based, LLM Explorer Score: 0.22.

Base model:finetune:unsloth/qw... Base model:unsloth/qwen3-4b-in... De En Es Fr Guardrailing Guardrails Instruct It Qwen3 Region:us Safetensors Safety Scope Sharded Tensorflow Text-embeddings-inference

Model Card on HF 🤗: https://huggingface.co/principled-intelligence/scope-guard-4B-q-2601

Scope Guard 4B Q 2601 Parameters and Internals

LLM Name	Scope Guard 4B Q 2601
Repository 🤗	https://huggingface.co/principled-intelligence/scope-guard-4B-q-2601
Base Model(s)	Qwen3 4B Instruct 2507 unsloth/Qwen3-4B-Instruct-2507
Model Size	4b
Required VRAM	8.1 GB
Updated	2026-08-01
Maintainer	principled-intelligence
Model Type	qwen3
Instruction-Based	Yes
Model Files	5.0 GB: 1-of-2 3.1 GB: 2-of-2
Supported Languages	en it fr es de
Model Architecture	Qwen3ForCausalLM
License	apache-2.0
Context Length	262144
Model Max Length	262144
Transformers Version	4.57.3
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|vision_pad\|>
Vocabulary Size	151936
Torch Data Type	bfloat16
Errors	replace

Rank the Scope Guard 4B Q 2601 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 Scope Guard 4B Q 2601

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	334	210
FastContext 1.0 4B RL	256K / 8.1 GB	4559	61
Qwen3 4B Sft Prm	256K / 17.6 GB	602	0
Qwen3 4B Instruct 2507 FP8	256K / 5.2 GB	1100744	78
...pt Full Qwen3 4b Instruct 2507	256K / 8 GB	365	1
Nexa AI 4B Instruct	256K / 8 GB	576	2
Neuron 4B Instruct	256K / 8.1 GB	313	1
Agents K1	256K / 8.8 GB	1098	28

Note: green Score (e.g. "73.2") means that the model is better than principled-intelligence/scope-guard-4B-q-2601.