Gemma 4 31B vs Qwen3.7 Plus
Compare Gemma 4 31B and Qwen3.7 Plus side-by-side. See how these vision models stack up in Image Captioning, OCR, Open Prompt, Object Detection, and Classification.
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Gemma 4 31B vs Qwen3.7 Plus Comparison Table
Evals updated August 20, 2026Pricing updated August 24, 2026
| Property | Gemma 4 31B | Qwen3.7 Plus |
|---|---|---|
| Organization | Qwen | |
| Category | open | closed |
| Modality | multimodal | — |
| Release Date | Apr 2026 | — |
| Context Window | 256K | — |
| Parameters | 31B | |
| License | Apache 2.0 | |
| Pricing per 1M tokens | ||
| Input $/1M | $0.100 | $0.320 |
| Output $/1M | $0.340 | $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 | ||
| 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 | Not evaluated | 67.4% |
| Avg cost / sample | – | $0.0008 |
| Avg speed / sample | – | 7.01s |
| By task | ||
| Object Detection | – | 60.1% $0.0013 |
| Counting | – | 50.0% $0.0004 |
| Identification | – | 84.4% $0.0003 |
| OCR | – | 86.5% $0.0009 |
| Data Extraction | – | 83.5% $0.0004 |
| Reasoning (low) | – | 39.7% $0.0003 |
| Reasoning (high) | – | 68.2% $0.0043 |
Gemma 4 31B vs Qwen3.7 Plus: Overview
Gemma 4 31B is the largest dense model in Google's Gemma 4 family, built from the same research as Gemini 3 and released as open weights under the Apache 2.0 license. It supports a 256K token context window with text and image input, configurable thinking mode for step-by-step reasoning, and multilingual support across 140+ languages. The unquantized model fits on a single 80GB GPU.
For vision tasks, Gemma 4 31B supports image understanding with variable aspect ratios and resolutions, and can output structured bounding boxes for UI element detection, making it useful for document parsing and UI understanding. Compared to Gemma 3, it delivers stronger reasoning and multimodal performance. It is part of a four-size family alongside the 26B A4B MoE variant and two on-device models (E2B, E4B), with the 31B dense variant optimized for output quality and fine-tuning over inference speed.
Frequently Asked Questions
Gemma 4 31B has not yet been evaluated on Roboflow's current Vision Evals, so this comparison shows specs, licensing, and pricing rather than benchmark scores.
Yes. The comparison demo on this page runs both models on the same image side by side for image captioning and OCR in the free Roboflow Playground. You can try it instantly, and a free account unlocks unlimited runs.