Gemini 3.8 Flash vs Qwen3.7 Plus
Compare Gemini 3.8 Flash and Qwen3.7 Plus side-by-side. See how these vision models stack up in Object Detection, Image Captioning, OCR, Classification, and Open Prompt.
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Models in this comparison
Gemini 3.8 Flash vs Qwen3.7 Plus on Vision Evals
Gemini 3.8 Flash scores higher on all five Vision Evals tasks.
The widest gap is Reasoning, where Gemini 3.8 Flash leads 81.2% to 39.7%.
Overall, Gemini 3.8 Flash averages 79.8% (#7 of 63) against 58.9% (#37 of 63) for Qwen3.7 Plus.
Qwen3.7 Plus is both cheaper ($0.0008 vs $0.0045 per sample) and faster (7.8s vs 12.8s per sample).
Gemini 3.8 Flash vs Qwen3.7 Plus Comparison Table
Evals updated October 13, 2026Pricing updated October 17, 2026
| Property | Gemini 3.8 Flash | Qwen3.7 Plus |
|---|---|---|
| Organization | Qwen | |
| Category | closed | closed |
| Modality | multimodal | — |
| Release Date | Sep 2026 | Jun 2026 |
| Context Window | 1.0M | — |
| Parameters | Unknown | Unknown |
| License | Proprietary | Unknown |
| Commercial use | commercial use per vendor terms | See license terms |
| Pricing per 1M tokens | ||
| Input $/1M | $0.825 | $0.320 |
| Output $/1M | $4.13 | $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 | Supported | Not listed |
| Document Question Answering | Supported | Not listed |
| Image Tagging | Supported | Not listed |
| Multi-Label Classification | Supported | Not listed |
| Vision Language | Supported | Not listed |
| Model Features | ||
| Foundation Vision | Supported | Not listed |
| LLMs with Vision Capabilities | Supported | Not listed |
| Multimodal Vision | Supported | Not listed |
Vision Evalsground-truth scores across 5 vision tasks, pooled at low effort | ||
| Overall | 79.8% | 58.9% |
| Avg cost / sample | $0.0045 | $0.0008 |
| Avg speed / sample | 12.76s | 7.77s |
| By task | ||
| Object Detection (low) | 68.1% ±0.8, Mean of 3 runs, range 67.3 to 69.0 | 60.1% |
| Object Detection (high) | 74.8% ±1.1, Mean of 3 runs, range 73.4 to 75.6 | – |
| Counting (low) | 78.8% ±2.7, Mean of 3 runs, range 75.7 to 81.1 | 50.0% |
| Counting (high) | 79.3% ±1.4, Mean of 3 runs, range 78.4 to 81.1 | – |
| Identification (low) | 97.9% ±1.6, Mean of 3 runs, range 96.9 to 100.0 | 84.4% |
| Identification (high) | 96.9% ±0.0, Mean of 3 runs, range 96.9 to 96.9 | – |
| OCR (low) | 72.8% | 60.3% |
| by category |
|
|
| OCR (high) | 78.7% | 65.5% |
| by category |
|
|
| Reasoning (low) | 81.2% ±0.3, Mean of 3 runs, range 80.8 to 81.5 | 39.7% |
| Reasoning (high) | 84.5% ±1.0, Mean of 3 runs, range 83.4 to 85.4 | 68.2% |
Gemini 3.8 Flash vs Qwen3.7 Plus: Overview
Gemini 3.8 Flash is a natively multimodal reasoning model in Google's Gemini 3 series, positioned as the speed and cost oriented Flash tier while targeting long-horizon software engineering, autonomous agents, and enterprise workflows. It accepts text, images, video, audio, and PDF documents in a single request and returns text, with an input limit of 1,048,576 tokens and an output limit of 65,536 tokens. Thinking is configurable at low, medium, and high levels, and the model supports function calling, code execution, structured outputs, context caching, search and Maps grounding, file search, and computer use in preview. Image generation, audio generation, and the Live API are not supported.
On vision oriented evaluations the model reports 86.2% on CharXiv Reasoning for chart and figure synthesis and 87.8% on LVBench for long video understanding in agentic mode, alongside 90.8% on Terminal-Bench 2.1 and 61.6% on SWE-Bench Pro for coding. Following Gemini API conventions, it can localize objects by emitting bounding boxes as [ymin, xmin, ymax, xmax] integers normalized to a 0 to 1000 range, which supports prompt driven detection and grounding in addition to captioning, document parsing, and visual question answering. The knowledge cutoff is March 2026, though coverage in some domains reflects the January 2025 cutoff shared across the Gemini 3 family.
Frequently Asked Questions
On Roboflow's Vision Evals, Gemini 3.8 Flash performed better. It scores higher on all five vision tasks and averages 79.8% (#7 of 63) against 58.9% (#37 of 63) 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 3.8 Flash leads with 81.2% 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 $0.0045. Gemini 3.8 Flash is priced at $0.83 per 1M input tokens and $4.13 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.
Qwen3.7 Plus is faster. Across Roboflow's Vision Evals it averaged 7.8s per inference against 12.8s. 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 captioning in the free Roboflow Playground. You can try it instantly, and a free account unlocks unlimited runs.