MODEL PROFILE

Ovis1.6-Llama3.2-3B

ATH-MaaS · Ovis1.6-Llama3.2-3B

We are thrilled to announce the open-sourcing of **Ovis1.6-Llama3.2-3B**, an integral part of the Ovis1.6 family. This cutting-edge model currently sets the benchmark as the state-of-the-art (SOTA) solution for edge-side multimodal tasks. The Ovis family employs an innovative Multimodal Large Language Model (MLLM) architecture, specifically designed to structurally align visual and textual embeddings. Ovis1.6-Llama3.2-3B excels in common industry benchmarks, surpassing numerous open-source and proprietary multimodal models. Moreover, it is also particularly well-suited for local intelligence, on-device computing, and edge computing scenarios. Built upon Ovis1.5, **Ovis1.6** further enhances high-resolution image processing, is trained on a larger, more diverse, and higher-quality dataset, and refines the training process with DPO training following instruction-tuning.

Visual QAlicense:apache-2.0
Context windowNot disclosed
Input → OutputText、Image → Text
Model weightsNot verified
Profile updated2026/11/2 19:16:38
OVERVIEW

Model overview

We are thrilled to announce the open-sourcing of **Ovis1.6-Llama3.2-3B**, an integral part of the Ovis1.6 family. This cutting-edge model currently sets the benchmark as the state-of-the-art (SOTA) solution for edge-side multimodal tasks. The Ovis family employs an innovative Multimodal Large Language Model (MLLM) architecture, specifically designed to structurally align visual and textual embeddings. Ovis1.6-Llama3.2-3B excels in common industry benchmarks, surpassing numerous open-source and proprietary multimodal models. Moreover, it is also particularly well-suited for local intelligence, on-device computing, and edge computing scenarios. Built upon Ovis1.5, **Ovis1.6** further enhances high-resolution image processing, is trained on a larger, more diverse, and higher-quality dataset, and refines the training process with DPO training following instruction-tuning.

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.

PRICING & COST

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.

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Estimate monthly base token costs

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Estimates exclude cache discounts, tiered pricing, multimodal surcharges, web search, taxes and additional reasoning output.

INDEPENDENT BENCHMARKS

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。

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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?

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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。