Gemini 3.1 Pro vs GLM 5V Turbo
Compare Gemini 3.1 Pro and GLM 5V Turbo side-by-side. See how these vision models stack up in Image Captioning, Open Prompt, Classification, OCR, and Object Detection.
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Models in this comparison
Gemini 3.1 Pro vs GLM 5V Turbo on Vision Evals
Gemini 3.1 Pro scores higher on all six Vision Evals tasks.
The widest gap is Reasoning, where Gemini 3.1 Pro leads 72.2% to 31.8%.
Overall, Gemini 3.1 Pro averages 83.1% (#5 of 33) against 65.3% (#25 of 33) for GLM 5V Turbo.
GLM 5V Turbo is both cheaper ($0.0031 vs $0.0093 per sample) and faster (6.3s vs 7.8s per sample).
Gemini 3.1 Pro vs GLM 5V Turbo Comparison Table
Evals updated August 26, 2026Pricing updated August 26, 2026
| Property | Gemini 3.1 Pro | GLM 5V Turbo |
|---|---|---|
| Organization | Z.ai | |
| Category | closed | closed |
| Modality | multimodal | multimodal |
| Release Date | Feb 2026 | Apr 2026 |
| Context Window | 1.0M | 200K |
| Parameters | ||
| License | Proprietary | Proprietary |
| Pricing per 1M tokens | ||
| Input $/1M | $2.00 | $1.20 |
| Output $/1M | $12.00 | $4.00 |
| 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 | 83.1% | 65.3% |
| Avg cost / sample | $0.0093 | $0.0031 |
| Avg speed / sample | 7.81s | 6.35s |
| By task | ||
| Object Detection | 67.6% $0.010 | 56.5% $0.0052 |
| Counting | 71.6% $0.0071 | 48.6% $0.0017 |
| Identification | 100.0% $0.0070 | 84.4% $0.0015 |
| OCR | 92.6% $0.0066 | 89.3% $0.0030 |
| Data Extraction | 94.8% $0.0063 | 81.4% $0.0018 |
| Reasoning (low) | 72.2% $0.012 | 31.8% $0.0017 |
| Reasoning (high) | 74.8% $0.021 | 49.7% $0.0069 |
Gemini 3.1 Pro vs GLM 5V Turbo: 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.
GLM-5V-Turbo is a native multimodal model from Z.ai that extends the GLM family with joint image, video, and text input aimed at vision-centered coding and agent workflows. The model reads screenshots, design drafts, document layouts, and interface captures and generates runnable code from them, covering tasks such as turning a visual design into a working front end, diagnosing rendering and layout defects from screen captures, and operating graphical user interfaces during long-horizon agent runs. It accepts roughly 200,000 input tokens and can emit up to 131,072 output tokens in a single response, which supports sessions that hold specifications, source files, logs, and visual references at the same time.
Training includes a joint reinforcement learning stage spanning more than 30 tasks simultaneously, an approach Z.ai describes as a way to counter the trade-off in which improving visual recognition degrades programming ability and the reverse. Reported evaluations cover pure-text coding on the backend, frontend, and repository exploration tracks of CC-Bench-V2, together with agent execution suites such as PinchBench, ClawEval, and ZClawBench, indicating that text coding behavior is retained after visual input is added.
Frequently Asked Questions
On Roboflow's Vision Evals, Gemini 3.1 Pro performed better. It scores higher on all six vision tasks and averages 83.1% (#5 of 33) against 65.3% (#25 of 33) for GLM 5V Turbo. 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 3.1 Pro leads with 72.2% against 31.8%. This is the widest gap between the two models across the benchmark's tasks.
GLM 5V Turbo is cheaper to run. Across Roboflow's Vision Evals task mix it averaged $0.0031 per sample against $0.0093. Gemini 3.1 Pro is priced at $2.00 per 1M input tokens and $12.00 per 1M output; GLM 5V Turbo is priced at $1.20 per 1M input tokens and $4.00 per 1M output. Actual costs depend on your image sizes, prompts, and output length.
GLM 5V Turbo is faster. Across Roboflow's Vision Evals it averaged 6.3s per inference against 7.8s. 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 image captioning and open prompts in the free Roboflow Playground. You can try it instantly, and a free account unlocks unlimited runs.