Gemini 3.5 Flash-Lite vs Gemma 4 12B
Compare Gemini 3.5 Flash-Lite and Gemma 4 12B side-by-side.
Compare Gemini 3.5 Flash-Lite vs Gemma 4 12B live
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Gemini 3.5 Flash-Lite vs Gemma 4 12B Comparison Table
Evals updated July 10, 2026Pricing updated July 21, 2026
| Property | Gemini 3.5 Flash-Lite | Gemma 4 12B |
|---|---|---|
| Organization | ||
| Category | closed | open |
| Modality | multimodal | multimodal |
| Release Date | Jul 2026 | Jun 2026 |
| Context Window | 1.0M | — |
| Parameters | 12B | |
| License | Proprietary | Apache 2.0 |
| Vision Tasks | ||
| Captioning | Demo | |
| OCR | Demo | |
| Vision Language | ||
| Visual Question Answering | Demo | |
| Classification | Demo | |
| Document Question Answering | ||
| Multi-Label Classification | ||
| Object Detection | Demo | |
| Video Classification | ||
| Model Features | ||
| Multimodal Vision | ||
| LLMs with Vision Capabilities | ||
| Real-Time Vision | ||
Gemini 3.5 Flash-Lite vs Gemma 4 12B: 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.
On agentic and coding benchmarks, Gemini 3.5 Flash-Lite significantly outperforms its predecessor, Gemini 3.1 Flash-Lite, including on Terminal-Bench 2.1 (54% vs. 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). It also surpasses Gemini 3 Flash on SWE-Bench Pro (54.2% vs. 49.6%) and OSWorld-Verified (74.0% vs. 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.
Gemma 4 12B is an open-weight multimodal model from Google in the Gemma 4 family. It is intended for text and image understanding tasks such as visual question answering, OCR, captioning, and document understanding, with a smaller parameter footprint than the larger Gemma 4 variants.
This entry is connected to Roboflow Playground vision evals for comparison. No runnable Playground workflow is configured yet, so the model page is used for discovery and benchmark context rather than direct hosted inference.