Gemini 3.5 Flash vs Gemini 3 Flash
Gemini 3.5 Flash and Gemini 3 Flash score 81.8% vs 65.7% averaged across five Vision Evals tasks (#5 and #29 of 65 models), so Gemini 3.5 Flash leads overall.
- Gemini 3.5 Flash wins all 5 tasks, with its widest lead on object detection (70.6% vs 38.6%).
- Gemini 3 Flash is about a fifth of the cost: $0.0024 vs $0.012 overall average cost per sample.
- Gemini 3 Flash is faster: 5.8s vs 11.5s per sample.
Roboflow Vision Evals. Full breakdown below.
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Gemini 3.5 Flash vs Gemini 3 Flash on Vision Evals
Roboflow Vision Evals. Full breakdown below.
Gemini 3.5 Flash vs Gemini 3 Flash Comparison Table
Evals updated October 26, 2026Pricing updated November 5, 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 | Unknown | Unknown |
| License | Proprietary | Proprietary |
| Commercial use | commercial use per vendor terms | commercial use per vendor terms |
| Pricing per 1M tokens | ||
| Input $/1M | $1.50 | $0.500 |
| Output $/1M | $9.00 | $3.00 |
| Vision Tasks | ||
| Model Features | ||
Both support 3 more features | ||
Vision Evalsground-truth scores across 5 vision tasks, pooled at low effort | ||
| Overall | 81.8% | 65.7% |
| Avg cost / sample | $0.012 | $0.0024 |
| Avg speed / sample | 11.52s | 5.83s |
| By task | ||
| Object Detection (low) | 70.6% ±2.0, Mean of 3 runs, range 68.7 to 72.6 | 38.6% |
| Object Detection (high) | 69.8% ±1.8, Mean of 3 runs, range 67.5 to 71.1 | – |
| Counting (low) | 80.6% ±0.7, Mean of 3 runs, range 79.7 to 81.1 | 67.6% |
| Counting (high) | 82.4% ±0.0, Mean of 3 runs, range 82.4 to 82.4 | – |
| Identification (low) | 99.0% ±1.6, Mean of 3 runs, range 96.9 to 100.0 | 93.8% |
| Identification (high) | 97.9% ±1.6, Mean of 3 runs, range 96.9 to 100.0 | – |
| OCR (low) | 76.7% | 63.9% |
| by category |
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| OCR (high) | 75.5% | 73.1% |
| by category |
|
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| Reasoning (low) | 82.1% ±2.0, Mean of 3 runs, range 80.1 to 84.1 | 64.9% |
| Reasoning (high) | 81.0% ±1.7, Mean of 3 runs, range 79.5 to 82.8 | 74.2% |
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.