GPT-6.1 Sol vs SAM 3
GPT-6.1 Sol: 81.7% average across five Vision Evals tasks (#9 of 69 models). We have not run SAM 3 through Roboflow's Vision Evals, so there is no head-to-head score. Run both on your own image below.
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GPT-6.1 Sol vs SAM 3 Comparison Table
Evals updated November 12, 2026Pricing updated November 13, 2026
| Property | GPT-6.1 Sol | SAM 3 |
|---|---|---|
| Organization | OpenAI | Meta |
| Category | closed | open |
| Modality | multimodal | multimodal |
| Release Date | Sep 2026 | Nov 2025 |
| Context Window | 1.1M | — |
| Parameters | undisclosed | Unknown |
| License | Proprietary | Custom |
| Commercial use | commercial use per vendor terms | See license terms |
| Pricing per 1M tokens | ||
| Input $/1M | $2.00 | No published price |
| Output $/1M | $10.00 | No published price |
| Vision Tasks | ||
| Captioning | Demo | Not listed |
| Chart Question Answering | Supported | Not listed |
| Classification | Demo | 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 |
| Video Object Tracking | Not listed | Supported |
| Vision Language | Supported | Not listed |
| Visual Question Answering | Demo | Not listed |
| Zero Shot Segmentation | Not listed | Supported |
Both support 2 more tasks | ||
| Model Features | ||
| LLMs with Vision Capabilities | Supported | Not listed |
| Zero-shot Detection | Not listed | Supported |
Both support 2 more features | ||
Vision Evalsground-truth scores across 5 vision tasks, pooled at low effort | ||
| Overall | 81.7% | Not evaluated |
| Avg cost / sample | $0.0068 | – |
| Avg speed / sample | 12.82s | – |
| By task | ||
| Object Detection (low) | 80.8% ±0.1, Mean of 3 runs, range 80.7 to 80.9 | – |
| Object Detection (high) | 81.6% ±0.4, Mean of 3 runs, range 81.1 to 82.0 | – |
| Counting (low) | 78.8% ±3.4, Mean of 3 runs, range 75.7 to 82.4 | – |
| Counting (high) | 80.2% ±3.4, Mean of 3 runs, range 77.0 to 83.8 | – |
| Identification (low) | 89.6% ±1.6, Mean of 3 runs, range 87.5 to 90.6 | – |
| Identification (high) | 88.5% ±1.6, Mean of 3 runs, range 87.5 to 90.6 | – |
| OCR (low) | 75.8% | – |
| by category |
| |
| OCR (high) | 75.8% | – |
| by category |
| |
| Reasoning (low) | 83.7% ±1.3, Mean of 3 runs, range 82.1 to 84.8 | – |
| Reasoning (high) | 88.7% ±2.0, Mean of 3 runs, range 87.4 to 91.4 | – |
GPT-6.1 Sol vs SAM 3: Overview
GPT-6.1 Sol is a reasoning model in OpenAI's GPT-6 series that accepts text and image input and returns text. It is an upgrade to GPT-6 Sol positioned to approach the intelligence of the larger GPT-6 Astra model on agentic coding, computer use, and professional knowledge work. The model exposes an adjustable reasoning effort control, ranging from low settings for simple turns to maximum settings for harder tasks, and can be driven with tool use enabled or disabled. It operates over a context window of roughly one million tokens and emits up to 128,000 output tokens in a single response, which supports long-running agent loops over large codebases and multi-document collections. Audio and video inputs are not supported.
OpenAI reports that GPT-6.1 Sol performs on par with or better than GPT-6 Sol across its image input safety evaluations, and that the share of responses containing a factual error at low reasoning effort falls from 11.4 percent to 7.7 percent.
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
GPT-6.1 Sol is released under Proprietary, while SAM 3 uses Custom. In practice: GPT-6.1 Sol: commercial use per vendor terms. 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 and segmentation in the free Roboflow Playground. You can try it instantly, and a free account unlocks unlimited runs.