Gemini 3 Flash vs Qwen3.7 Flash
Compare Gemini 3 Flash and Qwen3.7 Flash side-by-side. See how these vision models stack up in Object Detection, Classification, Open Prompt, OCR, and Image Captioning.
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Models in this comparison
Gemini 3 Flash vs Qwen3.7 Flash on Vision Evals
Gemini 3 Flash scores higher on 5 of the six Vision Evals tasks.
The widest gap is Reasoning, where Gemini 3 Flash leads 64.9% to 34.4%.
Overall, Gemini 3 Flash averages 74.9% (#10 of 25) against 61.7% (#24 of 25) for Qwen3.7 Flash.
Qwen3.7 Flash is cheaper ($0.0001 vs $0.0021 per sample), while Gemini 3 Flash is faster (4.1s vs 6.3s per sample).
Gemini 3 Flash vs Qwen3.7 Flash Comparison Table
Evals updated August 6, 2026Pricing updated August 11, 2026
| Property | Gemini 3 Flash | Qwen3.7 Flash |
|---|---|---|
| Organization | Qwen | |
| Category | closed | closed |
| Modality | multimodal | multimodal |
| Release Date | Dec 2025 | Jul 2026 |
| Context Window | 1.0M | 1.0M |
| Parameters | ||
| License | Proprietary | Proprietary |
| Pricing per 1M tokens | ||
| Input $/1M | $0.500 | $0.030 |
| Output $/1M | $3.00 | $0.130 |
| Vision Tasks | ||
| Captioning | Demo | Demo |
| Chart Question Answering | ||
| Classification | Demo | Demo |
| Document Question Answering | ||
| Image Tagging | ||
| Multi-Label Classification | ||
| Object Detection | Demo | Demo |
| OCR | Demo | Demo |
| Vision Language | ||
| Visual Question Answering | Demo | Demo |
| Model Features | ||
| Foundation Vision | ||
| LLMs with Vision Capabilities | ||
| Multimodal Vision | ||
Vision Evalsground-truth scores across 6 vision tasks, pooled at low effort | ||
| Overall | 74.9% | 61.7% |
| Avg cost / sample | $0.0021 | $0.0001 |
| Avg speed / sample | 4.10s | 6.32s |
| By task | ||
| Object Detection | 38.6% $0.0031 | 42.8% $0.0001 |
| Counting | 67.6% $0.0012 | 46.0% <$0.0001 |
| Identification | 93.8% $0.0009 | 84.4% <$0.0001 |
| OCR | 87.6% $0.0024 | 84.1% $0.0001 |
| Data Extraction | 96.9% $0.0008 | 78.3% <$0.0001 |
| Reasoning (low) | 64.9% $0.0020 | 34.4% <$0.0001 |
| Reasoning (high) | 74.2% $0.0040 | 60.9% $0.0005 |
Gemini 3 Flash vs Qwen3.7 Flash: 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.
Qwen3.7 Flash is the low-latency, cost-oriented tier of Alibaba's Qwen3.7 series, a vision-language reasoning model that accepts interleaved text and image input and returns text. It is built as a hybrid thinking model: like the rest of the Qwen3.7, Qwen3.6, and Qwen3.5 families served through Alibaba Cloud Model Studio, it can either emit an explicit reasoning trace before answering or respond directly, with thinking behavior controlled by an enable_thinking switch that defaults to on for the Qwen3.7 generation. The model exposes a context window of roughly one million tokens and a maximum generation length of 65,536 tokens, which allows long multi-image sequences, long documents, and extended agent trajectories to be held in a single request.
Functionally, Qwen3.7 Flash targets multimodal agent workloads rather than pure chat. Reported strengths include object recognition, spatial understanding, and perception of real-world scenes, alongside visual coding, search, and computer-use style interaction where the model reads screen content and reasons over interface state. Weights are not published; the model is a proprietary endpoint positioned below Qwen3.7 Plus and Qwen3.7 Max in the same series, and it supports function calling and tool use for agentic pipelines.
Frequently Asked Questions
On Roboflow's Vision Evals, Gemini 3 Flash performed better. It scores higher on 5 of the six vision tasks and averages 74.9% (#10 of 25) against 61.7% (#24 of 25) for Qwen3.7 Flash. These scores measure vision capabilities only; either model may perform differently on work outside this benchmark's tasks.
Yes. On the Vision Evals Reasoning benchmark at low effort, Gemini 3 Flash leads with 64.9% against 34.4%. This is the widest gap between the two models across the benchmark's tasks.
Qwen3.7 Flash is cheaper to run. Across Roboflow's Vision Evals task mix it averaged $0.0001 per sample against $0.0021. Gemini 3 Flash is priced at $0.50 per 1M input tokens and $3.00 per 1M output; Qwen3.7 Flash is priced at $0.03 per 1M input tokens and $0.13 per 1M output. Actual costs depend on your image sizes, prompts, and output length.
Gemini 3 Flash is faster. Across Roboflow's Vision Evals it averaged 4.1s per inference against 6.3s. Latency varies with image size, prompt length, and provider load, so treat these as relative rather than guaranteed figures.
Yes. The comparison demo on this page runs both models on the same image side by side for object detection and image classification in the free Roboflow Playground. You can try it instantly, and a free account unlocks unlimited runs.