Qwen3.8 Max vs SAM 3
Compare Qwen3.8 Max and SAM 3 side-by-side. See how these vision models stack up in Object Detection.
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Qwen3.8 Max vs SAM 3 Comparison Table
Evals updated September 22, 2026Pricing updated September 23, 2026
| Property | Qwen3.8 Max | SAM 3 |
|---|---|---|
| Organization | Qwen | Meta |
| Category | closed | open |
| Modality | multimodal | multimodal |
| Release Date | Aug 2026 | Nov 2025 |
| Context Window | 984K | — |
| Parameters | 2.4T total, ~95B active | |
| License | Apache 2.0 | Custom |
| Vision Tasks | ||
| Object Detection | Demo | Demo |
| Captioning | Demo | |
| Chart Question Answering | ||
| Classification | Demo | |
| Document Question Answering | ||
| Image Tagging | ||
| Instance Segmentation | ||
| Multi-Label Classification | ||
| OCR | Demo | |
| Open Vocabulary Object Detection | ||
| Promptable Concept Segmentation | Demo | |
| Video Object Tracking | ||
| Vision Language | ||
| Visual Question Answering | Demo | |
| Zero Shot Segmentation | ||
| Model Features | ||
| Foundation Vision | ||
| Multimodal Vision | ||
| LLMs with Vision Capabilities | ||
| Zero-shot Detection | ||
Vision Evalsground-truth scores across 6 vision tasks, pooled at low effort | ||
| Overall | 83.9% | Not evaluated |
| Avg cost / sample | $0.0074 | – |
| Avg speed / sample | 17.25s | – |
| By task | ||
| Object Detection (low) | 76.7% ±0.3, Mean of 3 runs, range 76.5 to 77.1 | – |
| Object Detection (high) | 78.4% ±0.4, Mean of 3 runs, range 78.1 to 78.9 | – |
| Counting (low) | 81.1% ±2.0, Mean of 3 runs, range 78.4 to 82.4 | – |
| Counting (high) | 81.1% ±0.0, Mean of 3 runs, range 81.1 to 81.1 | – |
| Identification (low) | 88.5% ±1.6, Mean of 3 runs, range 87.5 to 90.6 | – |
| Identification (high) | 89.6% ±1.6, Mean of 3 runs, range 87.5 to 90.6 | – |
| OCR (low) | 93.3% ±0.5, Mean of 3 runs, range 92.8 to 93.9 | – |
| OCR (high) | 91.3% ±0.5, Mean of 3 runs, range 90.7 to 91.7 | – |
| Data Extraction (low) | 87.6% ±0.0, Mean of 3 runs, range 87.6 to 87.6 | – |
| Data Extraction (high) | 89.3% ±1.0, Mean of 3 runs, range 88.7 to 90.7 | – |
| Reasoning (low) | 75.9% ±2.0, Mean of 3 runs, range 73.5 to 77.5 | – |
| Reasoning (high) | 80.3% ±2.0, Mean of 3 runs, range 78.2 to 82.1 | – |
Qwen3.8 Max vs SAM 3: Overview
Qwen3.8 Max is the flagship tier of Alibaba's Qwen3.8 family, a sparse mixture-of-experts multimodal model with roughly 2.4 trillion total parameters of which about 95 billion activate per token, which keeps serving cost and latency well below what the total parameter count would imply. It builds on the architectural foundation established by Qwen3.5 and accepts text, images, video, and documents as input while producing text output. Reported context handling reaches close to one million tokens, with a maximum generation length of 131,072 tokens, so the model is aimed at long-horizon agentic work such as repository-scale coding, multi-step research, data analysis, and office document workflows.
For vision work the model performs image and video understanding, document and chart interpretation, text recognition inside images, and grounded visual question answering, and Alibaba reports gains concentrated in multimodal and agentic evaluation categories rather than general reasoning. Published figures include 86.6 on Terminal-Bench 2.1, 67.7 on SWE-bench Pro, 93.0 on PaperBench, 82.8 on IFBench, and 92.6 on GPQA Diamond. It is the first model in the Max tier of the Qwen line for which the team states weights will be released publicly, alongside a smaller Qwen3.8 27B checkpoint. No training or safety model card has been published.
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.
Frequently Asked Questions
SAM 3 has not yet been evaluated on Roboflow's current Vision Evals, so this comparison shows specs, licensing, and pricing rather than benchmark scores.
Qwen3.8 Max is released under Apache 2.0, while SAM 3 uses Custom. Licensing often matters more than raw accuracy for commercial deployments, so check the terms against how you plan to ship.
Yes. The comparison demo on this page runs both models on the same image side by side for object detection in the free Roboflow Playground. You can try it instantly, and a free account unlocks unlimited runs.
