Gemini 2.0 Flash Exp vs Gemini 3.8 Flash

Gemini 2.0 Flash, released by Google DeepMind on February 5, 2025, is the efficiency-focused successor to Gemini 1.5 Flash. It is a multimodal model that accepts text, code, images, audio, and video as inputs, though its stable GA release outputs text only (image and audio generation remain in preview). The model supports up to 1 million tokens of input context with an output cap of ~8K tokens, making it well-suited for analyzing large documents, transcripts, or media files. Its knowledge is current through August 2024.

Flash 2.0 is optimized for speed, scalability, and agentic workflows, offering fast response times, tool use, structured outputs, and function calling. While more cost-efficient than Pro variants, its trade-offs include shorter output lengths and less depth on reasoning-intensive tasks. Available through the Gemini API, Vertex AI, AI Studio, and Gemini apps, Gemini 2.0 Flash is positioned for real-time applications, enterprise assistants, and production-scale multimodal processing where efficiency and throughput are priorities.

Gemini 3.8 Flash is a natively multimodal reasoning model in Google's Gemini 3 series, positioned as the speed and cost oriented Flash tier while targeting long-horizon software engineering, autonomous agents, and enterprise workflows. It accepts text, images, video, audio, and PDF documents in a single request and returns text, with an input limit of 1,048,576 tokens and an output limit of 65,536 tokens. Thinking is configurable at low, medium, and high levels, and the model supports function calling, code execution, structured outputs, context caching, search and Maps grounding, file search, and computer use in preview. Image generation, audio generation, and the Live API are not supported.

On vision oriented evaluations the model reports 86.2% on CharXiv Reasoning for chart and figure synthesis and 87.8% on LVBench for long video understanding in agentic mode, alongside 90.8% on Terminal-Bench 2.1 and 61.6% on SWE-Bench Pro for coding. Following Gemini API conventions, it can localize objects by emitting bounding boxes as [ymin, xmin, ymax, xmax] integers normalized to a 0 to 1000 range, which supports prompt driven detection and grounding in addition to captioning, document parsing, and visual question answering. The knowledge cutoff is March 2026, though coverage in some domains reflects the January 2025 cutoff shared across the Gemini 3 family.