Gemini 3.7 Flash vs Gemini 3 Flash
Compare Gemini 3.7 Flash and Gemini 3 Flash side-by-side. See how these vision models stack up in Image Captioning, Open Prompt, Classification, and OCR.
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Models in this comparison
Gemini 3.7 Flash vs Gemini 3 Flash on Vision Evals
Gemini 3.7 Flash scores higher on 4 of the six Vision Evals tasks.
The widest gap is Object Detection, where Gemini 3.7 Flash leads 69.4% to 38.6%.
Overall, Gemini 3.7 Flash averages 84.6% (#2 of 30) against 74.9% (#11 of 30) for Gemini 3 Flash.
Gemini 3.7 Flash is cheaper ($0.0016 vs $0.0021 per sample), while Gemini 3 Flash is faster (4.1s vs 10.0s per sample).
Gemini 3.7 Flash vs Gemini 3 Flash Comparison Table
Evals updated August 14, 2026Pricing updated August 15, 2026
| Property | Gemini 3.7 Flash | Gemini 3 Flash |
|---|---|---|
| Organization | ||
| Category | closed | closed |
| Modality | multimodal | multimodal |
| Release Date | Aug 2026 | Dec 2025 |
| Context Window | 1.0M | 1.0M |
| Parameters | Undisclosed | |
| License | Proprietary | Proprietary |
| Pricing per 1M tokens | ||
| Input $/1M | $0.375 | $0.500 |
| Output $/1M | $1.88 | $3.00 |
| Vision Tasks | ||
| Captioning | Demo | Demo |
| Chart Question Answering | ||
| Classification | Demo | Demo |
| Document Question Answering | ||
| Image Tagging | ||
| Multi-Label Classification | ||
| Object Detection | Demo | |
| OCR | Demo | Demo |
| Vision Language | ||
| Visual Question Answering | Demo | Demo |
| Model Features | ||
| Foundation Vision | ||
| LLMs with Vision Capabilities | ||
| Multimodal Vision | ||
Vision Evalsground-truth scores across 6 vision tasks, pooled at low effort | ||
| Overall | 84.6% | 74.9% |
| Avg cost / sample | $0.0016 | $0.0021 |
| Avg speed / sample | 9.97s | 4.10s |
| By task | ||
| Object Detection | 69.4% $0.0024 | 38.6% $0.0031 |
| Counting | 77.0% $0.0013 | 67.6% $0.0012 |
| Identification | 96.9% $0.0007 | 93.8% $0.0009 |
| OCR | 86.9% $0.0014 | 87.6% $0.0024 |
| Data Extraction | 94.8% $0.0007 | 96.9% $0.0008 |
| Reasoning (low) | 82.8% $0.0011 | 64.9% $0.0020 |
| Reasoning (high) | 82.1% $0.0026 | 74.2% $0.0040 |
Gemini 3.7 Flash vs Gemini 3 Flash: Overview
Gemini 3.7 Flash is a proprietary multimodal model from Google, positioned in the Flash branch of the Gemini 3 series that trades some of the capacity of the larger Pro models for lower latency and lower cost per token. It accepts interleaved text and image input alongside other modalities handled by the Gemini family and returns text, and it continues the series pattern of exposing a configurable thinking budget so that reasoning effort can be scaled up for harder problems or reduced for high throughput extraction, routing and classification work. The model is announced roughly three weeks after Gemini 3.6 Flash, part of an unusually fast iteration cadence within the Flash line.
Google reports gains concentrated in agentic coding and front end generation, citing a WebDev Arena Elo of 1588 for this release compared with 1538 for the preceding Flash model, and describes it as producing more functional layouts and more feature complete applications in fewer prompts. Weights are not published and the architecture, parameter count and training corpus are undisclosed, consistent with prior Gemini releases. Visual capability follows the Flash lineage, covering image and document understanding, chart and diagram interpretation, text recognition in images, and general visual question answering.
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.
Frequently Asked Questions
On Roboflow's Vision Evals, Gemini 3.7 Flash performed better. It scores higher on 4 of the six vision tasks and averages 84.6% (#2 of 30) against 74.9% (#11 of 30) for Gemini 3 Flash. These scores measure vision capabilities only; either model may perform differently on work outside this benchmark's tasks.
Yes. On the Vision Evals Object Detection benchmark, Gemini 3.7 Flash leads with 69.4% against 38.6%. This is the widest gap between the two models across the benchmark's tasks.
Gemini 3.7 Flash is cheaper to run. Across Roboflow's Vision Evals task mix it averaged $0.0016 per sample against $0.0021. Gemini 3.7 Flash is priced at $0.38 per 1M input tokens and $1.88 per 1M output; Gemini 3 Flash is priced at $0.50 per 1M input tokens and $3.00 per 1M output. Actual costs depend on your image sizes, prompts, and output length.
Gemini 3 Flash is faster. Across Roboflow's Vision Evals it averaged 4.1s per inference against 10.0s. Latency varies with image size, prompt length, and provider load, so treat these as relative rather than guaranteed figures.
Yes. The comparison demo on this page runs both models on the same image side by side for image captioning and open prompts in the free Roboflow Playground. You can try it instantly, and a free account unlocks unlimited runs.