Gemini 3.1 Pro vs Qwen3 VL 235B A22B Instruct
Gemini 3.1 Pro and Qwen3 VL 235B A22B Instruct score 76.8% vs 55.2% averaged across five Vision Evals tasks (#14 and #50 of 65 models), so Gemini 3.1 Pro leads overall.
- Gemini 3.1 Pro wins all 5 tasks, with its widest lead on reasoning (72.2% vs 29.8%).
- Qwen3 VL 235B A22B Instruct is about 1/9 of the cost: $0.0011 vs $0.010 overall average cost per sample.
- Gemini 3.1 Pro is faster: 8.4s vs 15.9s per sample.
Roboflow Vision Evals. Full breakdown below.
Compare Gemini 3.1 Pro vs Qwen3 VL 235B A22B Instruct live
Run the same image across every model that supports a task and compare their outputs side-by-side.
Detect and compare bounding boxes across models on the same image.
Upload an image
Drag and drop an image here, or click to browse
Gemini 3.1 Pro vs Qwen3 VL 235B A22B Instruct on Vision Evals
Roboflow Vision Evals. Full breakdown below.
Gemini 3.1 Pro vs Qwen3 VL 235B A22B Instruct Comparison Table
Evals updated October 26, 2026Pricing updated November 8, 2026
| Property | Gemini 3.1 Pro | Qwen3 VL 235B A22B Instruct |
|---|---|---|
| Organization | Qwen | |
| Category | closed | open |
| Modality | multimodal | multimodal |
| Release Date | Feb 2026 | Sep 2025 |
| Context Window | 1.0M | 256K |
| Parameters | Unknown | 235B |
| License | Proprietary | Apache 2.0 |
| Commercial use | commercial use per vendor terms | free for commercial use |
| Pricing per 1M tokens | ||
| Input $/1M | $2.00 | $0.210 |
| Output $/1M | $12.00 | $1.90 |
| Vision Tasks | ||
| Model Features | ||
Both support 3 more features | ||
Vision Evalsground-truth scores across 5 vision tasks, pooled at low effort | ||
| Overall | 76.8% | 55.2% |
| Avg cost / sample | $0.010 | $0.0011 |
| Avg speed / sample | 8.44s | 15.87s |
| By task | ||
| Object Detection | 67.4% | 52.1% |
| Counting | 71.6% | 47.3% |
| Identification | 100.0% | 90.6% |
| OCR (low) | 72.6% | 56.4% |
| by category |
|
|
| OCR (high) | 73.1% | 55.5% |
| by category |
|
|
| Reasoning (low) | 72.2% | 29.8% |
| Reasoning (high) | 74.8% | 33.8% |
Gemini 3.1 Pro vs Qwen3 VL 235B A22B Instruct: Overview
Gemini 3.1 Pro is a proprietary multimodal model from Google’s Gemini 3 series, released in early 2026 and designed for advanced reasoning across large multimodal datasets. It accepts text, images, audio, video, and documents, supporting up to a 1-million-token input context with up to 64k output tokens. Compared with Gemini 3 Pro, it improves long-context synthesis and multi-step reasoning, enabling more reliable analysis of large documents, datasets, and software codebases.
The model also advances visual understanding and grounding, allowing it to interpret UI screenshots, diagrams, and real-world scenes while referencing specific regions within images or video. These capabilities make Gemini 3.1 Pro well suited for multimodal workflows involving document processing, interface analysis, robotics research, and complex visual reasoning.
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.