Gemini 3.5 Flash vs Qwen3.6 Plus
Compare Gemini 3.5 Flash and Qwen3.6 Plus side-by-side. See how these vision models stack up in Open Prompt, Image Captioning, and OCR.
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Gemini 3.5 Flash vs Qwen3.6 Plus: Overview
Gemini 3.5 Flash is a multimodal language model developed by Google DeepMind and released at Google I/O 2026. It is built on the Gemini 3 Flash reasoning foundation and introduces configurable thinking levels (minimal, low, medium, and high) that allow developers to tune the depth of internal reasoning before a response is generated. The model accepts text, image, video, audio, and PDF inputs and produces text output, with a 1 million token context window and up to 65,000 output tokens per request. It is natively multimodal, processing visual inputs alongside text to support tasks such as image captioning, classification, optical character recognition, object detection, and visual grounding, where the model references specific regions within an image or video frame.
Its vision capabilities extend to interpreting UI screenshots, diagrams, charts, and real-world scenes, as well as understanding video and live frame sequences for activity and scene recognition. The model supports combined tool use, including Google Search, URL context, code execution, and custom functions, within a single request, and it uses reasoning context from previous turns when thought signatures are present in the conversation history, enabling persistent multi-turn reasoning chains. Gemini 3.5 Flash carries a knowledge cutoff of January 2026 and is available via the Gemini API, Google AI Studio, Google Antigravity, and the Gemini Enterprise Agent Platform.
Qwen3.6 Plus is a flagship model in Alibaba’s Qwen Plus series, designed for agentic workflows, coding, and multi-step reasoning. It supports a 1 million token context window and up to 65,536 output tokens, with built-in reasoning capabilities. The model is available as a hosted, proprietary API through Alibaba Cloud.
Compared to Qwen3.5, it improves reliability in multi-step execution and frontend code generation, with stronger performance on agentic coding tasks. It also supports document and image understanding, though its vision capabilities are more limited than dedicated Qwen-VL models. Qwen3.6 Plus is part of a broader Qwen ecosystem that includes both closed-source APIs and open-weight models.
Gemini 3.5 Flash vs Qwen3.6 Plus Comparison Table
| Property | Gemini 3.5 Flash | Qwen3.6 Plus |
|---|---|---|
| Organization | Qwen | |
| Category | closed | closed |
| Modality | multimodal | multimodal |
| Release Date | May 2026 | Apr 2026 |
| Context Window | 1.0M | 1.0M |
| Parameters | ||
| License | Proprietary | Proprietary |
| Pricing per 1M tokens | ||
| Input $/1M | $1.50 | $0.325 |
| Output $/1M | $9.00 | $1.95 |
| Vision Tasks | ||
| Captioning | Demo | Demo |
| Object Detection | Demo | |
| OCR | Demo | Demo |
| Visual Question Answering | Demo | Demo |
| Chart Question Answering | ||
| Classification | Demo | |
| Document Question Answering | ||
| Multi-Label Classification | ||
| Vision Language | ||
| Model Features | ||
| LLMs with Vision Capabilities | ||
| Multimodal Vision | ||
Vision Evalspass/fail results · 67 prompts Score key:≥75%40–74%<40% | ||
| Overall Score | 79.1% | 68.66% |
| Avg Response Time | 6.71s | 34.17s |
| Median input tokensincl. image tokens | 1.1K | 1.2K |
| Median output tokens | 294 | 47 |
| Est. cost / taskon this benchmark | $0.0043 | $0.0005 |
| Defect Detection | 80%(12/15) | 86.7%(13/15) |
| Document Understanding | 77.8%(7/9) | 77.8%(7/9) |
| Object Counting | 60%(6/10) | 20%(2/10) |
| Object Understanding | 92.9%(13/14) | 78.6%(11/14) |
| Spatial Understanding | 78.9%(15/19) | 68.4%(13/19) |
Output tokens (incl. reasoning) and est. cost / task are measured on this benchmark from a single low-temperature run, and shown only for models whose run covered at least 90% of prompts. Methodology