Compare Gemini Embedding 001 and Gemini 3 Flash Preview on key metrics including price, context length, throughput, and other model features.
Gemini-Embedding-001 is Google’s top-ranked multilingual embedding model, supporting over 100 languages and flexible output dimensions (3072, 1536, or 768). It is optimized for semantic search, clustering, and recommendations, and leverages Matryoshka Representation Learning for efficient, high-quality embeddings.
Gemini 3 Flash Preview is a high-speed, cost-effective reasoning model built for agent-driven workflows, multi-turn conversation, and coding support. Offering near-Pro level performance in both reasoning and tool use, it stands out by delivering significantly lower latency than larger Gemini versions—making it ideal for interactive development, long-running agent loops, and collaborative programming. Compared to Gemini 2.5 Flash, it features notable improvements in reasoning ability, multimodal comprehension, and overall reliability. The model supports a 1M token context window and handles multimodal inputs—text, images, audio, video, and PDFs—with text-based output. Features like configurable reasoning levels, structured outputs, tool integration, and automatic context caching make it a strong choice for users seeking powerful agentic capabilities without the high cost or lag of more extensive models.