Gemini 3.5 Flash vs Gemini 3 Flash
Compare Gemini 3.5 Flash and Gemini 3 Flash side-by-side. See how these vision models stack up in Open Prompt, Image Captioning, OCR, Classification, and Object Detection.
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Gemini 3.5 Flash vs Gemini 3 Flash on Vision Evals
Gemini 3.5 Flash scores higher on 5 of the six Vision Evals tasks.
The widest gap is Object Detection, where Gemini 3.5 Flash leads 61.7% to 39.3%.
Overall, Gemini 3.5 Flash averages 86.0% (#1 of 16) against 77.2% (#4 of 16) for Gemini 3 Flash.
Gemini 3 Flash is both cheaper ($0.0017 vs $0.0082 per sample) and faster (3.9s vs 4.8s per sample).
Gemini 3.5 Flash vs Gemini 3 Flash Comparison Table
Evals updated July 10, 2026Pricing updated July 21, 2026
| Property | Gemini 3.5 Flash | Gemini 3 Flash |
|---|---|---|
| Organization | ||
| Category | closed | closed |
| Modality | multimodal | multimodal |
| Release Date | May 2026 | Dec 2025 |
| Context Window | 1.0M | 1.0M |
| Parameters | ||
| License | Proprietary | Proprietary |
| Pricing per 1M tokens | ||
| Input $/1M | $1.50 | $0.500 |
| Output $/1M | $9.00 | $3.00 |
| Vision Tasks | ||
| Captioning | Demo | Demo |
| Classification | Demo | Demo |
| Object Detection | Demo | Demo |
| OCR | Demo | Demo |
| Visual Question Answering | Demo | Demo |
| Chart Question Answering | ||
| Document Question Answering | ||
| Multi-Label Classification | ||
| Vision Language | ||
| Model Features | ||
| LLMs with Vision Capabilities | ||
| Multimodal Vision | ||
| Foundation Vision | ||
Vision Evalsground-truth scores across 6 vision tasks | ||
| Overall | 86.0% | 77.2% |
| Object Detection | 61.7% | 39.3% |
| Counting | 81.1% | 67.6% |
| Identification | 100.0% | 93.8% |
| OCR | 91.1% | 87.6% |
| Data Extraction | 94.8% | 96.9% |
| Reasoning | 87.0% | 78.3% |
| Avg cost / sample | $0.0082 | $0.0017 |
| Avg speed / sample | 4.8s | 3.9s |
Gemini 3.5 Flash vs Gemini 3 Flash: Overview
Gemini 3.5 Flash is a multimodal language model developed by Google DeepMind and released at Google I/O 2026. It is built on the Gemini 3 Flash reasoning foundation and introduces configurable thinking levels (minimal, low, medium, and high) that allow developers to tune the depth of internal reasoning before a response is generated. The model accepts text, image, video, audio, and PDF inputs and produces text output, with a 1 million token context window and up to 65,000 output tokens per request. It is natively multimodal, processing visual inputs alongside text to support tasks such as image captioning, classification, optical character recognition, object detection, and visual grounding, where the model references specific regions within an image or video frame.
Its vision capabilities extend to interpreting UI screenshots, diagrams, charts, and real-world scenes, as well as understanding video and live frame sequences for activity and scene recognition. The model supports combined tool use, including Google Search, URL context, code execution, and custom functions, within a single request, and it uses reasoning context from previous turns when thought signatures are present in the conversation history, enabling persistent multi-turn reasoning chains. Gemini 3.5 Flash carries a knowledge cutoff of January 2026 and is available via the Gemini API, Google AI Studio, Google Antigravity, and the Gemini Enterprise Agent Platform.
Gemini 3 Flash is a proprietary multimodal large language model developed by Google through Google DeepMind, designed to deliver fast, cost-efficient reasoning across real-time products and developer workflows. Released in December 2025, it is the Flash-tier variant of the Gemini 3 family, balancing low latency with reasoning quality approaching Pro models.
The model supports text, images, audio, and video, with an exceptionally large context window of roughly one million input tokens and outputs up to ~65k tokens. It emphasizes rapid responses for coding, summarization, analysis, and agentic tasks, and exposes configurable “thinking levels” via API to trade speed for deeper reasoning. Today, Gemini 3 Flash positions itself as a high-throughput, production-ready model, serving as the default in the Gemini app and Google Search’s AI Mode, optimized for scalable, interactive AI applications.