---
title: Qwen2.5-VL-7B-Instruct-GGUF
canonical_url: "https://www.modelscope.cn/models/IAILabs/Qwen2.5-VL-7B-Instruct-GGUF"
md_url: "https://www.modelscope.cn/models/IAILabs/Qwen2.5-VL-7B-Instruct-GGUF.md"
repository: IAILabs/Qwen2.5-VL-7B-Instruct-GGUF
last_updated: 2025-03-04
base_model:
  - Qwen/Qwen2.5-VL-7B-Instruct
base_model_relation: quantized
library_name:
  - gguf
  - pytorch
frameworks:
  - pytorch
downloads: 13073
stars: 7
tags:
  - gguf
---

# Qwen2.5-VL-7B-Instruct-GGUF

> Qwen2.5-VL-7B-Instruct-GGUF - IAILabs 在 ModelScope 开源的模型。NOTE: OLDER / OTHER VERSIONS OF THIS MODEL ARE ERRONEOUSLY PRODUCED Qwen2VLxQwen2.5 HYBRIDS!!!

IAILabs/Qwen2.5-VL-7B-Instruct-GGUF 是 ModelScope 魔搭社区上的机器学习模型，基于 Qwen/Qwen2.5-VL-7B-Instruct 构建。

- **Repository**: IAILabs/Qwen2.5-VL-7B-Instruct-GGUF
- **Base model**: Qwen/Qwen2.5-VL-7B-Instruct
- **Tags**: gguf
- **Downloads**: 13073
- **Stars**: 7
- **Last updated**: 2025-03-04

Source: https://www.modelscope.cn/models/IAILabs/Qwen2.5-VL-7B-Instruct-GGUF

---

# NOTE: OLDER / OTHER VERSIONS OF THIS MODEL ARE ERRONEOUSLY PRODUCED Qwen2VLxQwen2.5 HYBRIDS!!!

## Although these models have seemingly better performance than Qwen2VL, they are not the real deal! True Qwen2.5VL GGML support is still being added.


![](https://private-user-images.githubusercontent.com/6534243/418389672-10a77230-62b7-4763-84f1-35085eca3b18.png?jwt=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.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.tuaANrkwXXvZ1pHZ5RHVqhjTzw7HaRLG_7uzKXPYDR8)

# To test it out:
https://github.com/Independent-AI-Labs/llama.cpp/commits/debug/build/

You will have to build llama.cpp with CLIP hardware acceleration enabled to get the new architecture running.

Monitor our progress in merging this upstream here:
https://github.com/ggml-org/llama.cpp/pull/12119

# Official release and benchmarks coming soon!