Gemini 2.5 Flash-Lite vs Moondream 2
Compare Gemini 2.5 Flash-Lite and Moondream 2 side-by-side.
Compare Gemini 2.5 Flash-Lite vs Moondream 2 live
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Gemini 2.5 Flash-Lite vs Moondream 2 Comparison Table
Evals updated September 5, 2026Pricing updated September 21, 2026
| Property | Gemini 2.5 Flash-Lite | Moondream 2 |
|---|---|---|
| Organization | Moondream | |
| Category | closed | open |
| Modality | multimodal | multimodal |
| Release Date | Jul 2025 | Jan 2024 |
| Context Window | 1.0M | — |
| Parameters | ~2B | |
| License | Proprietary | Apache 2.0 |
| Pricing per 1M tokens | ||
| Input $/1M | $0.100 | |
| Output $/1M | $0.400 | |
| Vision Tasks | ||
| Captioning | Demo | |
| Object Detection | Demo | |
| Vision Language | ||
| Visual Question Answering | Demo | |
| Chart Question Answering | ||
| Classification | Demo | |
| Document Question Answering | ||
| Image Tagging | ||
| Multi-Label Classification | ||
| OCR | Demo | |
| Model Features | ||
| Multimodal Vision | ||
| Foundation Vision | ||
| LLMs with Vision Capabilities | ||
Gemini 2.5 Flash-Lite vs Moondream 2: 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.
Moondream 2 is a small open-source vision-language model from Moondream, the company founded by Vikhyat Korrapati. It was first released in early 2024 and updated through mid-2025. At approximately 1.9 billion parameters, it is designed to run efficiently on consumer hardware such as laptops and edge devices while supporting a practical range of multimodal tasks. Moondream 2 combines a vision encoder based on SigLIP with a compact language backbone, trained for image understanding tasks rather than as a general chat model.
The model accepts an image paired with a natural language prompt and produces text responses, supporting visual question answering, image captioning, and image-conditioned dialogue. Later Moondream 2 releases added object localization through a point API that returns coordinates for queried objects, along with improvements to OCR, counting, and document understanding. Moondream 2 is distributed under the Apache 2.0 license and is available through Hugging Face and the maintainer's distribution. Because the model is updated frequently, production deployments should pin to a specific revision rather than tracking the latest release. A successor model, Moondream 3 (Preview), was released in September 2025 with a 9B mixture-of-experts architecture and 2B active parameters, offering substantially stronger visual reasoning than Moondream 2 while retaining the efficiency-focused design. A referring expression segmentation extension to Moondream 3 was released in March 2026.