Model overview
This is an **UNOFFICIAL** GPTQ-Int4 quantized version of the `Qwen2.5-VL` model using `gptqmodel` library. The model is compatible with the latest `transformers` library (which can run non-quantized Qwen2.5-VL models). Response: > 这张图片展示了一个中文和英文的标志，内容为“中文LLaMA & Alpaca大模型”和“Chinese LLaMA & Alpaca Large Language Models”。标志左侧有两个卡通形象，一个是红色围巾的羊驼，另一个是白色毛发的羊驼，背景是一个绿色的草地和一座红色屋顶的建筑。标志右侧有一个数字3，旁边有一些电路图案。整体设计简洁明了，使用了明亮的颜色和可爱的卡通形象来吸引注意力。
Key features
特点摘要待依据来源补齐，不凭模型名称推断能力。
Limitations & considerations
Sources are insufficient to establish specific limitations. Verify task performance, latency, data policies, licensing and version lifecycle.
Source prices & cost analysis
Prices vary by channel, region and configuration. Channel quotes are listed independently and are not treated as a single official provider price.
| Source / channel | Input | Output | Billing unit | Collected at |
|---|---|---|---|---|
| No verified prices yet. Check the source channel. | ||||
Estimate monthly base token costs
Estimates exclude cache discounts, tiered pricing, multimodal surcharges, web search, taxes and additional reasoning output.
Public benchmarks & run configuration
暂无已采集的可核验公开评分。模型未上榜不代表能力较低。
View full indexed rankings →Frequently asked questions
Do open weights permit free commercial use?
Not necessarily. Check the version license, commercial conditions and usage policies. Self-hosting incurs compute and maintenance costs.
Are these real-time billing prices?
These are timestamped source snapshots, not live billing prices. Check the channel for current versions, regions, discounts and billing methods.
Sources & traceability
许可证：apache-2.0。模型介绍与第三方评测均以原来源的具体版本和方法为准。