What are the hardware requirements for Qwen2.5 7B Instruct Autoround Safetensors?

Qwen2.5 7B Instruct Autoround Safetensors requires approximately 4.7 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 Qwen2.5 7B Instruct Autoround Safetensors and how large is it?

Qwen2.5 7B Instruct Autoround Safetensors is developed by simaai, 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 Qwen2.5 7B Instruct Autoround Safetensors?

Qwen2.5 7B Instruct Autoround Safetensors is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Qwen2.5 7B Instruct Autoround Safetensors by simaai — VRAM 4.7GB, 32K context

Name: Qwen2.5 7B Instruct Autoround Safetensors
Author: simaai

Qwen2.5 7B Instruct Autoround Safetensors is an open-source language model by simaai. Features: 7b LLM, VRAM: 4.7GB, Context: 32K, License: apache-2.0, Instruction-Based, LLM Explorer Score: 0.24.

Autoround Base model:quantized:qwen/qwen... Base model:qwen/qwen2.5-7b-ins... Compressed-tensors Conversational Endpoints compatible Gptq Instruct Multilingual Quantized Qwen2 Region:us Safetensors Sima-ai

Model Card on HF 🤗: https://huggingface.co/simaai/Qwen2.5-7B-Instruct-Autoround-Safetensors

Qwen2.5 7B Instruct Autoround Safetensors Parameters and Internals

LLM Name	Qwen2.5 7B Instruct Autoround Safetensors
Repository 🤗	https://huggingface.co/simaai/Qwen2.5-7B-Instruct-Autoround-Safetensors
Base Model(s)	Qwen/Qwen2.5-7B-Instruct Qwen/Qwen2.5-7B-Instruct
Model Size	7b
Required VRAM	4.7 GB
Updated	2026-10-22
Maintainer	simaai
Model Type	qwen2
Instruction-Based	Yes
Model Files	4.7 GB
Model Architecture	Qwen2ForCausalLM
License	apache-2.0
Context Length	32768
Model Max Length	32768
Transformers Version	5.10.1
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	152064
Errors	replace

Rank the Qwen2.5 7B Instruct Autoround Safetensors capabilities

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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 Qwen2.5 7B Instruct Autoround Safetensors

Best Alternatives	Context / RAM	Downloads	Likes
Qwen2.5 7B Instruct 1M	986K / 15.4 GB	52534	373
Rewnozom	986K / 30.5 GB	742	1
Hush Qwen2.5 7B RP V1.4 1M	986K / 15.2 GB	10	2
Qwen2.5 7B RRP 1M	986K / 15.2 GB	5	6
Qwen2.5 7B CelestialHarmony 1M	986K / 14.8 GB	8	7
Q2.5 Instruct 1M Harmony	986K / 15.2 GB	4	2
Impish QWEN 7B 1M	986K / 15.2 GB	4	6
COCO 7B Instruct 1M	986K / 15.2 GB	9	4
Apollo 7B	986K / 15.2 GB	8	0
Graph R1 7B	986K / 15.3 GB	7	3

Note: green Score (e.g. "73.2") means that the model is better than simaai/Qwen2.5-7B-Instruct-Autoround-Safetensors.