Gemini 2.0 Flash Exp vs Gemini 3.6 Flash
Compare Gemini 2.0 Flash Exp and Gemini 3.6 Flash side-by-side. See how these vision models stack up in Classification, Image Captioning, OCR, Open Prompt, and Object Detection.
Compare Gemini 2.0 Flash Exp vs Gemini 3.6 Flash live
Run the same image across every model that supports a task and compare their outputs side-by-side.
Detect and compare bounding boxes across models on the same image.
Upload an image
Drag and drop an image here, or click to browse
Gemini 2.0 Flash Exp is deprecated and can no longer be run. Details and evals are still available on its model page.
Models in this comparison
Gemini 2.0 Flash Exp vs Gemini 3.6 Flash Comparison Table
Evals updated August 6, 2026Pricing updated August 10, 2026
| Property | Gemini 2.0 Flash Exp | Gemini 3.6 Flash |
|---|---|---|
| Organization | ||
| Category | closed | closed |
| Modality | multimodal | multimodal |
| Release Date | Feb 2025 | Jul 2026 |
| Context Window | 1.0M | 1.0M |
| Parameters | ||
| License | Proprietary | Proprietary |
| Pricing per 1M tokens | ||
| Input $/1M | $1.50 | |
| Output $/1M | $7.50 | |
| Vision Tasks | ||
| Captioning | Demo | |
| Chart Question Answering | ||
| Classification | Demo | |
| Document Question Answering | ||
| Image Tagging | ||
| Multi-Label Classification | ||
| Object Detection | Demo | |
| OCR | Demo | |
| Vision Language | ||
| Visual Question Answering | Demo | |
| Video Classification | ||
| Model Features | ||
| Foundation Vision | ||
| LLMs with Vision Capabilities | ||
| Multimodal Vision | ||
Vision Evalsground-truth scores across 6 vision tasks, pooled at low effort | ||
| Overall | Deprecated | 83.1% |
| Avg cost / sample | – | $0.0063 |
| Avg speed / sample | – | 4.73s |
| By task | ||
| Object Detection | – | 56.0% $0.0083 |
| Counting | – | 82.4% $0.0065 |
| Identification | – | 96.9% $0.0030 |
| OCR | – | 88.4% $0.0050 |
| Data Extraction | – | 94.8% $0.0030 |
| Reasoning (low) | – | 80.1% $0.0062 |
| Reasoning (high) | – | 80.1% $0.017 |
Gemini 2.0 Flash Exp vs Gemini 3.6 Flash: Overview
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 3.6 Flash is a multimodal language model from Google DeepMind, positioned as the workhorse tier in the Gemini 3.x family. It accepts text, image, video, audio, and PDF inputs with a 1 million token context window and produces up to 64,000 output tokens. The model builds directly on Gemini 3.5 Flash, incorporating developer and customer feedback to improve token efficiency, coding quality, and knowledge work performance. According to the Artificial Analysis Index, it consumes 17% fewer output tokens than its predecessor, and on some benchmarks such as DeepSWE, token reduction reaches up to 65%. It supports function calling, structured output, search as a tool, and code execution, and includes computer use as a built-in capability in the Gemini API and Gemini Enterprise.
On coding benchmarks, Gemini 3.6 Flash scores 49% on DeepSWE versus 37% for 3.5 Flash, and 63.9% on MLE Bench versus 49.7%. Computer use performance on OSWorld-Verified improves from 78.4% to 83%, and knowledge work scores on GDPval-AA v2 rise from 1349 to 1421. The model carries a knowledge cutoff of March 2026 and ships with enhanced Frontier Safety safeguards covering chemical, biological, radiological, nuclear, and cyber offense domains, with training to minimize refusals for beneficial uses. It is a proprietary, closed-weights model available in preview through the Gemini API via Google AI Studio, Android Studio, Google Antigravity, Gemini Enterprise, and the Gemini app.