Gemini 3 Flash vs Qwen3 VL 235B A22B Instruct
Compare Gemini 3 Flash and Qwen3 VL 235B A22B Instruct side-by-side. See how these vision models stack up in Open Prompt, OCR, and Image Captioning.
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Models in this comparison
Gemini 3 Flash vs Qwen3 VL 235B A22B Instruct on Vision Evals
Gemini 3 Flash scores higher on 4 of the six Vision Evals tasks.
The widest gap is Reasoning, where Gemini 3 Flash leads 78.3% to 43.5%.
Overall, Gemini 3 Flash averages 77.2% (#4 of 16) against 66.4% (#10 of 16) for Qwen3 VL 235B A22B Instruct.
Qwen3 VL 235B A22B Instruct is cheaper ($0.0007 vs $0.0017 per sample), while Gemini 3 Flash is faster (3.9s vs 8.2s per sample).
Gemini 3 Flash vs Qwen3 VL 235B A22B Instruct Comparison Table
Evals updated July 10, 2026Pricing updated July 21, 2026
| Property | Gemini 3 Flash | Qwen3 VL 235B A22B Instruct |
|---|---|---|
| Organization | Qwen | |
| Category | closed | open |
| Modality | multimodal | multimodal |
| Release Date | Dec 2025 | Sep 2025 |
| Context Window | 1.0M | 256K |
| Parameters | 235B | |
| License | Proprietary | Apache 2.0 |
| Pricing per 1M tokens | ||
| Input $/1M | $0.500 | $0.210 |
| Output $/1M | $3.00 | $1.90 |
| Vision Tasks | ||
| Captioning | Demo | Demo |
| Object Detection | Demo | |
| OCR | Demo | Demo |
| Vision Language | ||
| Visual Question Answering | Demo | Demo |
| Classification | Demo | |
| Model Features | ||
| LLMs with Vision Capabilities | ||
| Multimodal Vision | ||
| Foundation Vision | ||
Vision Evalsground-truth scores across 6 vision tasks | ||
| Overall | 77.2% | 66.4% |
| Object Detection | 39.3% | 42.3% |
| Counting | 67.6% | 47.3% |
| Identification | 93.8% | 90.6% |
| OCR | 87.6% | 88.1% |
| Data Extraction | 96.9% | 86.6% |
| Reasoning | 78.3% | 43.5% |
| Avg cost / sample | $0.0017 | $0.0007 |
| Avg speed / sample | 3.9s | 8.2s |
Gemini 3 Flash vs Qwen3 VL 235B A22B Instruct: Overview
Gemini 3 Flash is a proprietary multimodal large language model developed by Google through Google DeepMind, designed to deliver fast, cost-efficient reasoning across real-time products and developer workflows. Released in December 2025, it is the Flash-tier variant of the Gemini 3 family, balancing low latency with reasoning quality approaching Pro models.
The model supports text, images, audio, and video, with an exceptionally large context window of roughly one million input tokens and outputs up to ~65k tokens. It emphasizes rapid responses for coding, summarization, analysis, and agentic tasks, and exposes configurable “thinking levels” via API to trade speed for deeper reasoning. Today, Gemini 3 Flash positions itself as a high-throughput, production-ready model, serving as the default in the Gemini app and Google Search’s AI Mode, optimized for scalable, interactive AI applications.
Qwen3 VL 235B A22B Instruct is a flagship multimodal vision-language model developed by Qwen (Alibaba Cloud), designed for instruction-following tasks that combine advanced text generation with visual understanding. It serves as a high-end open-weight model for developers and researchers building multimodal AI systems that require strong reasoning, perception, and long-context capabilities.
The model supports interleaved text and image inputs, very long context windows (up to roughly 256K tokens), and efficient inference through a mixture-of-experts architecture with about 22B active parameters out of 235B total. In today’s landscape, it competes with top-tier proprietary vision-language models while offering the advantages of open weights and flexible deployment. Typical applications include multimodal assistants, document and image analysis, visual reasoning, and large-context instruction-based workflows.