Gemini 3 Flash vs Gemma 3 12B
Compare Gemini 3 Flash and Gemma 3 12B side-by-side. See how these vision models stack up in Open Prompt, OCR, and Image Captioning.
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Gemini 3 Flash vs Gemma 3 12B Comparison Table
Evals updated September 5, 2026Pricing updated September 21, 2026
| Property | Gemini 3 Flash | Gemma 3 12B |
|---|---|---|
| Organization | ||
| Category | closed | open |
| Modality | multimodal | multimodal |
| Release Date | Dec 2025 | Mar 2025 |
| Context Window | 1.0M | 128K |
| Parameters | 12B | |
| License | Proprietary | Custom |
| Pricing per 1M tokens | ||
| Input $/1M | $0.500 | $0.050 |
| Output $/1M | $3.00 | $0.150 |
| Vision Tasks | ||
| Captioning | Demo | Demo |
| Chart Question Answering | ||
| Classification | Demo | |
| Document Question Answering | ||
| Image Tagging | ||
| Multi-Label Classification | ||
| OCR | Demo | Demo |
| Vision Language | ||
| Visual Question Answering | Demo | Demo |
| Object Detection | Demo | |
| Model Features | ||
| Foundation Vision | ||
| LLMs with Vision Capabilities | ||
| Multimodal Vision | ||
Vision Evalsground-truth scores across 6 vision tasks, pooled at low effort | ||
| Overall | 74.9% | Not evaluated |
| Avg cost / sample | $0.0021 | – |
| Avg speed / sample | 4.10s | – |
| By task | ||
| Object Detection | 38.6% | – |
| Counting | 67.6% | – |
| Identification | 93.8% | – |
| OCR | 87.6% | – |
| Data Extraction | 96.9% | – |
| Reasoning (low) | 64.9% | – |
| Reasoning (high) | 74.2% | – |
Gemini 3 Flash vs Gemma 3 12B: Overview
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.
Gemma 3 12B, announced by Google DeepMind on March 12, 2025, is part of the open-weight Gemma 3 family, designed to provide a balance between capability and accessibility. With around 12 billion parameters, it supports multimodal input (text + images) and outputs text, making it useful for reasoning, summarization, Q&A, and visual understanding tasks. The model supports an input context of 128,000 tokens and typically generates up to ~8,000 tokens in output.
The 12B variant is instruction-tuned (“Gemma-3-12B-IT”) and optimized for multilingual use across more than 140 languages. It can run on a single GPU or TPU, offering a lighter compute footprint than very large proprietary models, while still achieving strong performance in reasoning benchmarks. Quantized and lower-precision variants are available to improve efficiency. Limitations include smaller output lengths relative to input capacity, scaling hardware needs at larger sizes, and performance below massive proprietary models on the most complex multimodal or reasoning-heavy tasks.