Qwen3.5 397B A17B vs SAM 3
Compare Qwen3.5 397B A17B and SAM 3 side-by-side.
Compare Qwen3.5 397B A17B vs SAM 3 live
Run the same image across every model that supports a task and compare their outputs side-by-side.
These models don't share enough common tasks for a side-by-side demo. See the comparison table below for their capabilities.
Models in this comparison
Qwen3.5 397B A17B vs SAM 3 Comparison Table
Evals updated October 13, 2026Pricing updated October 16, 2026
| Property | Qwen3.5 397B A17B | SAM 3 |
|---|---|---|
| Organization | Qwen | Meta |
| Category | open | open |
| Modality | multimodal | multimodal |
| Release Date | Feb 2026 | Nov 2025 |
| Context Window | 262K | — |
| Parameters | 397B | Unknown |
| License | Apache 2.0 | Custom |
| Commercial use | free for commercial use | See license terms |
| Pricing per 1M tokens | ||
| Input $/1M | $0.500 | No published price |
| Output $/1M | $3.60 | 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 |
Qwen3.5 397B A17B vs SAM 3: Overview
Qwen3.5-397B-A17B is a 397B-parameter (17B active) open-weight multimodal model developed by Alibaba’s Qwen team, released on 2026-02-16 under Apache-2.0. It supports text and image inputs with text outputs, combining a sparse Mixture-of-Experts architecture with Gated Delta Networks for efficient scaling. The model provides native vision-language reasoning and a large ~262K token context window, extendable to ~1M tokens.
As the first open-weight release in the Qwen3.5 family, it positions itself as a high-capacity, long-context alternative in the large vision-language space, balancing scale and efficiency via sparse activation. It is designed for advanced reasoning, coding, agent workflows, and multimodal understanding tasks.
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.