Model overview
**What's new in Vintern-3B-beta!** - **We successfully reproduced the training process of InternVL from scratch.** - The model is the result of integrating Qwen/Qwen2.5-3B-Instruct and InternViT-300M-448px through an MLP layer. - Trained with more than 10 Milion Vietnamese QnAs, Descriptions, and 10% English, Chinese Data from OpenGVLab/InternVL-Chat-V1-2-SFT-Data. We surpassed GPT-4o and are approaching Gemini 1.5 Pro on the MTVQA dataset for Vietnamese. The benchmark result in MTVQA from open_vlm_leaderboard. The current results are at a quite good level, and we are expanding the training set in English and other languages to approach models within a comparable parameter range.
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：来源未披露，须进一步核验。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。