What are the hardware requirements for Qwen2 7B Alpacha Q8 0?

Qwen2 7B Alpacha Q8 0 requires approximately 9.1 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Qwen2 7B Alpacha Q8 0 and how large is it?

Qwen2 7B Alpacha Q8 0 is developed by dbands, a model with 7b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

How does Qwen2 7B Alpacha Q8 0 perform on standard benchmarks?

Qwen2 7B Alpacha Q8 0 has the following published scores: LMSYS ELO 1347. Compare against reference models on this page or on the LLM Explorer leaderboards.

Qwen2 7B Alpacha Q8 0 by dbands — VRAM 9.1GB

Name: Qwen2 7B Alpacha Q8 0
Author: dbands

Qwen2 7B Alpacha Q8 0 is an open-source language model by dbands. Features: 7b LLM, VRAM: 9.1GB, License: apache-2.0, Quantized, LLM Explorer Score: 0.26, ELO: 1347.

4bit Base model:quantized:unsloth/q... Base model:unsloth/qwen2-7b-bn... En Endpoints compatible Gemma Gguf Q8 Q8 0 Quantized Qwen2 Region:us Unsloth

Model Card on HF 🤗: https://huggingface.co/dbands/Qwen2-7b-Alpacha-Q8_0

Qwen2 7B Alpacha Q8 0 Benchmarks

LMSys ELO 1347 vs 1272 (so35) 5.9%

^nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").

What is the LLM Explorer Rank (Score)

Qwen2 7B Alpacha Q8 0 Parameters and Internals

Model Type

text-generation-inference, transformers, unsloth, qwen2, gguf

Additional Notes

This qwen2 model was trained 2x faster with Unsloth and Huggingface's TRL library.

LLM Name	Qwen2 7B Alpacha Q8 0
Repository 🤗	https://huggingface.co/dbands/Qwen2-7b-Alpacha-Q8_0
Base Model(s)	Qwen2 7B Bnb 4bit unsloth/Qwen2-7B-bnb-4bit
Model Size	7b
Required VRAM	9.1 GB
Updated	2026-07-29
Maintainer	dbands
Model Type	gemma
Model Files	9.1 GB
Supported Languages	en
GGUF Quantization	Yes
Quantization Type	gguf\|q8\|q8_0\|4bit
Model Architecture	AutoModel
License	apache-2.0

Rank the Qwen2 7B Alpacha Q8 0 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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