Gemini 3.5 Flash-Lite vs Qwen3.7 Plus
Compare Gemini 3.5 Flash-Lite and Qwen3.7 Plus side-by-side. See how these vision models stack up in Image Captioning, Open Prompt, Classification, Object Detection, and OCR.
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Models in this comparison
Gemini 3.5 Flash-Lite vs Qwen3.7 Plus on Vision Evals
Gemini 3.5 Flash-Lite scores higher on 4 of the six Vision Evals tasks.
The widest gap is Reasoning, where Gemini 3.5 Flash-Lite leads 48.3% to 39.7%.
Overall, Gemini 3.5 Flash-Lite averages 69.6% (#16 of 31) against 67.4% (#18 of 31) for Qwen3.7 Plus.
Qwen3.7 Plus is cheaper ($0.0008 vs $0.0014 per sample), while Gemini 3.5 Flash-Lite is faster (2.7s vs 7.0s per sample).
Gemini 3.5 Flash-Lite vs Qwen3.7 Plus Comparison Table
Evals updated August 20, 2026Pricing updated August 24, 2026
| Property | Gemini 3.5 Flash-Lite | Qwen3.7 Plus |
|---|---|---|
| Organization | Qwen | |
| Category | closed | closed |
| Modality | multimodal | — |
| Release Date | Jul 2026 | — |
| Context Window | 1.0M | — |
| Parameters | ||
| License | Proprietary | |
| Pricing per 1M tokens | ||
| Input $/1M | $0.300 | $0.320 |
| Output $/1M | $2.50 | $1.28 |
| Vision Tasks | ||
| Captioning | Demo | Demo |
| Classification | Demo | Demo |
| Object Detection | Demo | Demo |
| OCR | Demo | Demo |
| Visual Question Answering | Demo | Demo |
| Chart Question Answering | ||
| Document Question Answering | ||
| Image Tagging | ||
| Multi-Label Classification | ||
| Video Classification | ||
| Vision Language | ||
| Model Features | ||
| Foundation Vision | ||
| LLMs with Vision Capabilities | ||
| Multimodal Vision | ||
Vision Evalsground-truth scores across 6 vision tasks, pooled at low effort | ||
| Overall | 69.6% | 67.4% |
| Avg cost / sample | $0.0014 | $0.0008 |
| Avg speed / sample | 2.70s | 7.01s |
| By task | ||
| Object Detection | 57.5% $0.0023 | 60.1% $0.0013 |
| Counting | 52.7% $0.0007 | 50.0% $0.0004 |
| Identification | 81.3% $0.0004 | 84.4% $0.0003 |
| OCR | 87.4% $0.0011 | 86.5% $0.0009 |
| Data Extraction | 90.7% $0.0004 | 83.5% $0.0004 |
| Reasoning (low) | 48.3% $0.0012 | 39.7% $0.0003 |
| Reasoning (high) | 68.9% $0.0042 | 68.2% $0.0043 |
Gemini 3.5 Flash-Lite vs Qwen3.7 Plus: Overview
Gemini 3.5 Flash-Lite is a natively multimodal reasoning model developed by Google DeepMind, released on July 21, 2026 as part of the Gemini 3.5 model family. It is the fastest model in the 3.5 series, designed for both low-latency tasks and high-throughput production workloads such as agentic search, document processing, receipt translation, and large-scale data extraction. The model accepts text, images, audio, and video as inputs, with a context window of up to 1 million tokens, and produces text output. It supports configurable thinking levels, allowing developers to tune the balance between response quality, cost, and latency depending on workload requirements.
On agentic and coding benchmarks, Gemini 3.5 Flash-Lite significantly outperforms its predecessor, Gemini 3.1 Flash-Lite, including on Terminal-Bench 2.1 (54% vs. 31%), GDM-MRCR v2 long-context (72.2% vs. 60.1%), and real-world task execution as measured by GDPval-AA v2 (1140 vs. 642). It also surpasses Gemini 3 Flash on SWE-Bench Pro (54.2% vs. 49.6%) and OSWorld-Verified (74.0% vs. 65.1%). According to the Artificial Analysis Index, the model generates output at approximately 350 tokens per second. It is built on the Gemini 3.5 Flash foundation and is evaluated across reasoning, coding, multimodal understanding, multilingual performance, and long-context tasks. The model is developed under Google's Frontier Safety Framework.
Frequently Asked Questions
On Roboflow's Vision Evals, Gemini 3.5 Flash-Lite performed better. It scores higher on 4 of the six vision tasks and averages 69.6% (#16 of 31) against 67.4% (#18 of 31) for Qwen3.7 Plus. 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 3.5 Flash-Lite leads with 48.3% against 39.7%. This is the widest gap between the two models across the benchmark's tasks.
Qwen3.7 Plus is cheaper to run. Across Roboflow's Vision Evals task mix it averaged $0.0008 per sample against $0.0014. Gemini 3.5 Flash-Lite is priced at $0.30 per 1M input tokens and $2.50 per 1M output; Qwen3.7 Plus is priced at $0.32 per 1M input tokens and $1.28 per 1M output. Actual costs depend on your image sizes, prompts, and output length.
Gemini 3.5 Flash-Lite is faster. Across Roboflow's Vision Evals it averaged 2.7s per inference against 7.0s. 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 image captioning and open prompts in the free Roboflow Playground. You can try it instantly, and a free account unlocks unlimited runs.