Gemini 2.5 Flash-Lite vs Gemma 4 31B
Gemma 4 31B: 57.7% average across four Vision Evals tasks (#41 of 65 models). We have not run Gemini 2.5 Flash-Lite through Roboflow's Vision Evals, so there is no head-to-head score. Run both on your own image below.
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Gemini 2.5 Flash-Lite vs Gemma 4 31B Comparison Table
Evals updated October 26, 2026Pricing updated November 4, 2026
| Property | Gemini 2.5 Flash-Lite | Gemma 4 31B |
|---|---|---|
| Organization | ||
| Category | closed | open |
| Modality | multimodal | multimodal |
| Release Date | Jul 2025 | Apr 2026 |
| Context Window | 1.0M | 256K |
| Parameters | Unknown | 31B |
| License | Proprietary | Apache 2.0 |
| Commercial use | commercial use per vendor terms | free for commercial use |
| Pricing per 1M tokens | ||
| Input $/1M | $0.100 | $0.200 |
| Output $/1M | $0.400 | $0.400 |
| Vision Tasks | ||
| Model Features | ||
Both support 3 more features | ||
Vision Evalsground-truth scores across 5 vision tasks | ||
| Overall | Not evaluated | 57.7%* |
| Quantizationsself-hosted | ||
| Avg cost / sample | – | $0.0015 |
| Avg speed / sample | – | 34.36s |
| By task | ||
| Object Detection | – | 47.5% ±0.6, Mean of 3 runs, range 46.8 to 48.0 |
| Counting | – | 51.4% ±2.7, Mean of 3 runs, range 48.6 to 54.0 |
| Identification | – | 79.2% ±1.6, Mean of 3 runs, range 78.1 to 81.3 |
| OCR | – | – |
| by category | ||
| Reasoning | – | 52.8% ±1.3, Mean of 3 runs, range 51.7 to 54.3 |
Gemini 2.5 Flash-Lite vs Gemma 4 31B: 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.
Gemma 4 31B is the largest dense model in Google's Gemma 4 family, built from the same research as Gemini 3 and released as open weights under the Apache 2.0 license. It supports a 256K token context window with text and image input, configurable thinking mode for step-by-step reasoning, and multilingual support across 140+ languages. The unquantized model fits on a single 80GB GPU.
For vision tasks, Gemma 4 31B supports image understanding with variable aspect ratios and resolutions, and can output structured bounding boxes for UI element detection, making it useful for document parsing and UI understanding. Compared to Gemma 3, it delivers stronger reasoning and multimodal performance. It is part of a four-size family alongside the 26B A4B MoE variant and two on-device models (E2B, E4B), with the 31B dense variant optimized for output quality and fine-tuning over inference speed.
Frequently Asked Questions
Gemini 2.5 Flash-Lite is released under Proprietary, while Gemma 4 31B uses Apache 2.0. In practice: Gemini 2.5 Flash-Lite: commercial use per vendor terms; Gemma 4 31B: free for commercial use. Licensing often matters more than raw accuracy for commercial deployments, so check the terms against how you plan to ship.
Yes. The comparison demo on this page runs both models on the same image side by side for image captioning and object detection in the free Roboflow Playground. You can try it instantly, and a free account unlocks unlimited runs.