Gemini 3.5 Flash-Lite vs SAM 3
Gemini 3.5 Flash-Lite: 61.7% average across five Vision Evals tasks (#35 of 65 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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Gemini 3.5 Flash-Lite vs SAM 3 Comparison Table
Evals updated October 26, 2026Pricing updated November 8, 2026
| Property | Gemini 3.5 Flash-Lite | SAM 3 |
|---|---|---|
| Organization | Meta | |
| Category | closed | open |
| Modality | multimodal | multimodal |
| Release Date | Jul 2026 | Nov 2025 |
| Context Window | 1.0M | — |
| Parameters | Unknown | Unknown |
| License | Proprietary | Custom |
| Commercial use | commercial use per vendor terms | See license terms |
| Pricing per 1M tokens | ||
| Input $/1M | $0.300 | No published price |
| Output $/1M | $2.50 | 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 |
| Promptable Concept Segmentation | Not listed | Demo |
| Video Classification | Supported | Not listed |
| 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 1 more task | ||
| 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 | 61.7% | Not evaluated |
| Avg cost / sample | $0.0014 | – |
| Avg speed / sample | 3.92s | – |
| By task | ||
| Object Detection | 57.5% | – |
| Counting | 52.7% | – |
| Identification | 84.4% | – |
| OCR (low) | 65.8% | – |
| by category |
| |
| OCR (high) | 71.2% | – |
| by category |
| |
| Reasoning (low) | 48.3% | – |
| Reasoning (high) | 68.9% | – |
Gemini 3.5 Flash-Lite vs SAM 3: Overview
Gemini 3.5 Flash-Lite is a natively multimodal reasoning model developed by Google DeepMind, released on July 21, 2026 as part of the Gemini 3.5 model family. It is the fastest model in the 3.5 series, designed for both low-latency tasks and high-throughput production workloads such as agentic search, document processing, receipt translation, and large-scale data extraction. The model accepts text, images, audio, and video as inputs, with a context window of up to 1 million tokens, and produces text output. It supports configurable thinking levels, allowing developers to tune the balance between response quality, cost, and latency depending on workload requirements.
31%), GDM-MRCR v2 long-context (72.2% vs. 60.1%), and real-world task execution as measured by GDPval-AA v2 (1140 vs. 642). 65.1%). According to the Artificial Analysis Index, the model generates output at approximately 350 tokens per second. It is built on the Gemini 3.5 Flash foundation and is evaluated across reasoning, coding, multimodal understanding, multilingual performance, and long-context tasks. The model is developed under Google's Frontier Safety Framework.
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
Gemini 3.5 Flash-Lite is released under Proprietary, while SAM 3 uses Custom. In practice: Gemini 3.5 Flash-Lite: 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 in the free Roboflow Playground. You can try it instantly, and a free account unlocks unlimited runs.