GLM 5V Turbo vs Qwen3.7 Plus
Compare GLM 5V Turbo and Qwen3.7 Plus side-by-side. See how these vision models stack up in Image Captioning, OCR, Classification, Object Detection, and Open Prompt.
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Models in this comparison
GLM 5V Turbo vs Qwen3.7 Plus on Vision Evals
Qwen3.7 Plus scores higher on 4 of the five Vision Evals tasks.
The widest gap is OCR, where Qwen3.7 Plus leads 60.3% to 51.5%.
Overall, GLM 5V Turbo averages 54.6% (#47 of 61) against 58.9% (#35 of 61) for Qwen3.7 Plus.
Qwen3.7 Plus is cheaper ($0.0008 vs $0.0037 per sample), while GLM 5V Turbo is faster (5.9s vs 7.8s per sample).
GLM 5V Turbo vs Qwen3.7 Plus Comparison Table
Evals updated October 8, 2026Pricing updated October 10, 2026
| Property | GLM 5V Turbo | Qwen3.7 Plus |
|---|---|---|
| Organization | Z.ai | Qwen |
| Category | closed | closed |
| Modality | multimodal | — |
| Release Date | Apr 2026 | Jun 2026 |
| Context Window | 200K | — |
| Parameters | Unknown | Unknown |
| License | Proprietary | Unknown |
| Pricing per 1M tokens | ||
| Input $/1M | $1.20 | $0.320 |
| Output $/1M | $4.00 | $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 | 54.6% | 58.9% |
| Avg cost / sample | $0.0037 | $0.0008 |
| Avg speed / sample | 5.89s | 7.77s |
| By task | ||
| Object Detection | 56.5% | 60.1% |
| Counting | 48.6% | 50.0% |
| Identification | 84.4% | 84.4% |
| OCR (low) | 51.5% | 60.3% |
| by category |
|
|
| OCR (high) | 56.0% | 65.5% |
| by category |
|
|
| Reasoning (low) | 31.8% | 39.7% |
| Reasoning (high) | 49.7% | 68.2% |
GLM 5V Turbo vs Qwen3.7 Plus: Overview
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, Qwen3.7 Plus performed better. It scores higher on 4 of the five vision tasks and averages 58.9% (#35 of 61) against 54.6% (#47 of 61) for GLM 5V Turbo. These scores measure vision capabilities only; either model may perform differently on work outside this benchmark's tasks.
No. On the Vision Evals OCR benchmark at low effort, Qwen3.7 Plus leads with 60.3% against 51.5%. 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 $0.0037. GLM 5V Turbo is priced at $1.20 per 1M input tokens and $4.00 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.
GLM 5V Turbo is faster. Across Roboflow's Vision Evals it averaged 5.9s 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 OCR in the free Roboflow Playground. You can try it instantly, and a free account unlocks unlimited runs.