Model overview
**Molmo2-ER** (Embodied Reasoning) is a 4B vision–language model specialized for the embodied perception skills that downstream action models depend on: scene understanding, pixel-accurate pointing, multi-image and egocentric–exocentric correspondence, and video temporal reasoning. It is built on top of Molmo2 (Qwen3-4B backbone + SigLIP2 vision encoder) and serves as the vision–language backbone of the **MolmoAct2** action reasoning model. - **Outperforms every open-weight baseline** as well as the strongest closed-source models — including **Gemini Robot-ER 1.5 Thinking** and **GPT-5** — on **9 of 13** established embodied reasoning benchmarks (Point-Bench, RefSpatial, BLINK, CV-Bench, ERQA, EmbSpatial, MindCube, SAT, VSI-Bench). - **Overall average 63.8%**, a **+17 point** improvement over the Molmo2 starting point.
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。
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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。