Gemini 2.5 Flash-Lite vs Gemini 3 Pro
Compare Gemini 2.5 Flash-Lite and Gemini 3 Pro side-by-side. See how these vision models stack up in Image Captioning, Object Detection, OCR, Open Prompt, and Classification.
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Gemini 3 Pro is deprecated and can no longer be run. Details and evals are still available on its model page.
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Gemini 2.5 Flash-Lite vs Gemini 3 Pro: Overview
Gemini 2.5 Flash-Lite, released for general availability on July 22, 2025, is the most cost-efficient model in the Gemini 2.5 family, designed for high-volume and latency-sensitive tasks. It is multimodal, supporting text, images, video, audio, and PDFs as inputs, with text as its primary output. The model handles up to 1 million input tokens and generates outputs up to 64K tokens, making it suitable for large-scale document or media processing at low cost. It is built on a Sparse Mixture-of-Experts architecture with native multimodal support, though exact parameter counts are undisclosed.
Flash-Lite offers the lowest usage cost among Gemini 2.5 models. It introduces developer controls for “thinking mode,” allowing fine-tuning of reasoning depth vs. efficiency. It also integrates native tools such as code execution, search grounding, and URL context. While strong on translation, classification, coding, and general multimodal reasoning, it lacks support for image or audio generation in its stable release and is less capable than Gemini 2.5 Flash or Pro on complex reasoning-heavy workflows.
Gemini 3 Pro is Google DeepMind’s flagship multimodal frontier model, built for high-accuracy reasoning and large-scale context understanding across text, images, audio, video, code, and documents. It delivers major gains over Gemini 2.5 Pro, supported by a 1M-token window and strong performance on Google-reported benchmarks such as GPQA Diamond, MMMU-Pro, and Video-MMMU.
The model excels at structured outputs, tool use, and agentic coding, enabling complex multi-step workflows and analysis of entire books, codebases, or long videos in a single prompt. Positioned as Google’s top production model, it balances advanced reasoning with broad multimodal capabilities, making it well suited for research assistants, automation agents, coding systems, and enterprise-scale document and media analysis.
Gemini 2.5 Flash-Lite vs Gemini 3 Pro Comparison Table
| Property | Gemini 2.5 Flash-Lite | Gemini 3 Pro |
|---|---|---|
| Organization | ||
| Category | closed | closed |
| Modality | multimodal | multimodal |
| Release Date | Jul 2025 | Nov 2025 |
| Context Window | 1.0M | 1.0M |
| Parameters | ||
| License | Proprietary | Proprietary |
| Pricing per 1M tokens | ||
| Input $/1M | $0.100 | |
| Output $/1M | $0.400 | |
| Vision Tasks | ||
| Captioning | Demo | |
| Classification | Demo | |
| Object Detection | Demo | |
| OCR | Demo | |
| Vision Language | ||
| Visual Question Answering | Demo | |
| Model Features | ||
| Foundation Vision | ||
| LLMs with Vision Capabilities | ||
| Multimodal Vision | ||
Vision Evalspass/fail results · 67 prompts Score key:≥75%40–74%<40% | ||
| Visual Understanding | ||
| Overall Score | 53.73% | |
| Avg Response Time | 7.19s | |
| Median input tokensincl. image tokens | 294 | |
| Median output tokens | 6 | |
| Est. cost / taskon this benchmark | <$0.0001 | |
| Defect Detection | 66.7%(10/15) | |
| Document Understanding | 66.7%(6/9) | |
| Object Counting | 10%(1/10) | |
| Object Understanding | 71.4%(10/14) | |
| Spatial Understanding | 47.4%(9/19) | |
| OCR | ||
| Overall Score | 77.73% | |
| Avg Response Time | 7.45s | |
| Median input tokensincl. image tokens | 290 | |
| Median output tokens | 12 | |
| Est. cost / taskon this benchmark | <$0.0001 | |
| Focused Scene OCR | 75.8%(75/99) | |
| Handwritten Math | 70%(7/10) | |
| License Plate Recognition | 90%(27/30) | |
| Text Recognition | 80%(24/30) | |
| VQA & Extraction | 75%(45/60) | |
Output tokens (incl. reasoning) and est. cost / task are measured on this benchmark from a single low-temperature run, and shown only for models whose run covered at least 90% of prompts. Methodology