What are the hardware requirements for Crazy AI Model?

Crazy AI Model requires approximately 15.2 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 Crazy AI Model and how large is it?

Crazy AI Model is developed by Alireza1913, a model with 7b 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 Crazy AI Model?

Crazy AI Model is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Crazy AI Model by Alireza1913 — VRAM 15.2GB, 32K context

Name: Crazy AI Model
Author: Alireza1913

Crazy AI Model is an open-source language model by Alireza1913. Features: 7b LLM, VRAM: 15.2GB, Context: 32K, License: apache-2.0, Quantized, Instruction-Based, LLM Explorer Score: 0.24.

4bit Base model:finetune:unsloth/qw... Base model:unsloth/qwen2.5-7b-... Conversational Finetuned Instruct Lateral-thinking Quantized Qwen2 Reasoning Region:us Safetensors Sharded Startup-ideas Tensorflow Unsloth

Model Card on HF 🤗: https://huggingface.co/Alireza1913/Crazy-AI-Model

Crazy AI Model Parameters and Internals

LLM Name	Crazy AI Model
Repository 🤗	https://huggingface.co/Alireza1913/Crazy-AI-Model
Base Model(s)	unsloth/Qwen2.5-7B-Instruct-bnb-4bit unsloth/Qwen2.5-7B-Instruct-bnb-4bit
Model Size	7b
Required VRAM	15.2 GB
Updated	2026-09-18
Maintainer	Alireza1913
Model Type	qwen2
Instruction-Based	Yes
Model Files	4.9 GB: 1-of-4 4.9 GB: 2-of-4 4.3 GB: 3-of-4 1.1 GB: 4-of-4
Quantization Type	4bit
Model Architecture	Qwen2ForCausalLM
License	apache-2.0
Context Length	32768
Model Max Length	32768
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|vision_pad\|>
Vocabulary Size	152064
Torch Data Type	float16
Errors	replace

Rank the Crazy AI Model 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 Crazy AI Model

Best Alternatives	Context / RAM	Downloads	Likes
Qwen2.5 7B Instruct 1M 4bit	986K / 4.3 GB	444	11
...wen2.5 7B Instruct 1M Bnb 4bit	986K / 5.5 GB	267	1
Qwen2.5 7B Instruct 1M 8bit	986K / 8.1 GB	63	4
Qwen2.5 7B Instruct 1M 6bit	986K / 6.2 GB	52	2
...B Instruct 1M Unsloth Bnb 4bit	986K / 7.5 GB	37	3
Alisia 7B Instruct V1	128K / 15.4 GB	114	2
...5 7B Instruct SFT Meme LoRA V7	128K / 15.2 GB	6	0
Gte Qwen2 7B Instruct 4bit DWQ	128K / 4.3 GB	88	3
Grok Demon 7b	32K / 15.2 GB	852	1
Qwen2.5 7B Security Cot	32K / 15.2 GB	364	2

Note: green Score (e.g. "73.2") means that the model is better than Alireza1913/Crazy-AI-Model.