What are the hardware requirements for Zen Ingress 1 3B Sft Merged?

Zen Ingress 1 3B Sft Merged requires approximately 6.2 GB of VRAM and supports a context window of 32K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Zen Ingress 1 3B Sft Merged and how large is it?

Zen Ingress 1 3B Sft Merged is developed by AllenGXM, a model with 3b 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 Zen Ingress 1 3B Sft Merged?

Zen Ingress 1 3B Sft Merged is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Zen Ingress 1 3B Sft Merged by AllenGXM — VRAM 6.2GB, 32K context

Name: Zen Ingress 1 3B Sft Merged
Author: AllenGXM

Zen Ingress 1 3B Sft Merged is an open-source language model by AllenGXM. Features: 3b LLM, VRAM: 6.2GB, Context: 32K, License: apache-2.0, Fine-Tuned, LLM Explorer Score: 0.33.

Conversational Custom-finetune Dpo En Finetuned Math Qwen Qwen2 Reasoning Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/ZenithLLM/zen-ingress-1-3b-sft-merged

Zen Ingress 1 3B Sft Merged Parameters and Internals

LLM Name	Zen Ingress 1 3B Sft Merged
Repository 🤗	https://huggingface.co/ZenithLLM/zen-ingress-1-3b-sft-merged
Model Size	3b
Required VRAM	6.2 GB
Updated	2026-09-26
Maintainer	AllenGXM
Model Type	qwen2
Model Files	4.0 GB: 1-of-2 2.2 GB: 2-of-2
Supported Languages	en
Model Architecture	Qwen2ForCausalLM
License	apache-2.0
Context Length	32768
Model Max Length	32768
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|vision_pad\|>
Vocabulary Size	151936
Torch Data Type	bfloat16
Errors	replace

Rank the Zen Ingress 1 3B Sft 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

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Note: green Score (e.g. "73.2") means that the model is better than ZenithLLM/zen-ingress-1-3b-sft-merged.