Qwen3 VL 30B A3B Instruct vs SAM 3
Compare Qwen3 VL 30B A3B Instruct and SAM 3 side-by-side.
Compare Qwen3 VL 30B A3B Instruct vs SAM 3 live
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These models don't share enough common tasks for a side-by-side demo. See the comparison table below for their capabilities.
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Qwen3 VL 30B A3B Instruct vs SAM 3 Comparison Table
Evals updated October 13, 2026Pricing updated October 16, 2026
| Property | Qwen3 VL 30B A3B Instruct | SAM 3 |
|---|---|---|
| Organization | Qwen | Meta |
| Category | open | open |
| Modality | multimodal | multimodal |
| Release Date | Oct 2025 | Nov 2025 |
| Context Window | 262K | — |
| Parameters | 31B | Unknown |
| License | Apache 2.0 | Custom |
| Commercial use | free for commercial use | See license terms |
| Pricing per 1M tokens | ||
| Input $/1M | $0.150 | No published price |
| Output $/1M | $0.600 | No published price |
| Vision Tasks | ||
| Object Detection | Supported | Demo |
| Captioning | Demo | Not listed |
| Chart Question Answering | Supported | Not listed |
| Classification | Supported | Not listed |
| Document Question Answering | Supported | Not listed |
| Image Tagging | Supported | Not listed |
| Instance Segmentation | Not listed | Supported |
| Multi-Label Classification | Supported | Not listed |
| OCR | Demo | Not listed |
| Open Vocabulary Object Detection | Not listed | Supported |
| Promptable Concept Segmentation | Not listed | Demo |
| Video Object Tracking | Not listed | Supported |
| Vision Language | Supported | Not listed |
| Visual Question Answering | Demo | Not listed |
| Zero Shot Segmentation | Not listed | Supported |
| Model Features | ||
| Foundation Vision | Supported | Supported |
| Multimodal Vision | Supported | Supported |
| LLMs with Vision Capabilities | Supported | Not listed |
| Zero-shot Detection | Not listed | Supported |
Qwen3 VL 30B A3B Instruct vs SAM 3: Overview
Qwen3 VL 30B A3B Instruct is an open-weight multimodal large language model developed by Alibaba as part of the Qwen family, built for instruction-following tasks that unify text generation with visual and video understanding. Released around October 2025 under the Apache-2.0 license, it targets efficient, high-fidelity vision-language reasoning across very long contexts.
The model accepts text and image inputs and produces text outputs, with strong performance in OCR, spatial reasoning, long-video understanding, and agentic or GUI-centric visual tasks. It uses a Mixture-of-Experts (A3B) design with ~31.1B total parameters and ~3B active per token, paired with Qwen3-VL’s unified multimodal stack (including Interleaved-MRoPE and DeepStack fusion) to process text, images, and video in a single architecture. OCR support expands to 32 languages, enhancing document workflows. With a native ~262K token context window (extendable further), it stands out today for its balance of scale, efficiency, long-context support, and open accessibility in multimodal systems.
Released on November 19th, 2025, Segment Anything 3 (SAM 3) is a zero-shot image segmentation model that “detects, segments, and tracks objects in images and videos based on concept prompts.” This model was developed by Meta as the third model in the Segment Anything series.
Unlike its previous SAM models (Segment Anything and Segment Anything 2), you can provide SAM 3 with the prompt “shipping container” and it will generate precise segmentation masks for all shipping containers in an image. SAM 3 generates segmentation masks that correspond to the location of the objects found with a text prompt.
