Grok 4.7 vs Qwen3.7 Plus
Compare Grok 4.7 and Qwen3.7 Plus 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
Grok 4.7 vs Qwen3.7 Plus on Vision Evals
Grok 4.7 scores higher on 4 of the five Vision Evals tasks.
The widest gap is Reasoning, where Grok 4.7 leads 64.2% to 39.7%.
Overall, Grok 4.7 averages 63.5% (#31 of 63) against 58.9% (#37 of 63) for Qwen3.7 Plus.
Qwen3.7 Plus is both cheaper ($0.0008 vs $0.020 per sample) and faster (7.8s vs 33.3s per sample).
Grok 4.7 vs Qwen3.7 Plus Comparison Table
Evals updated October 13, 2026Pricing updated October 13, 2026
| Property | Grok 4.7 | Qwen3.7 Plus |
|---|---|---|
| Organization | SpaceXAI | Qwen |
| Category | closed | closed |
| Modality | — | — |
| Release Date | Sep 2026 | Jun 2026 |
| Context Window | 500K | — |
| Parameters | Unknown | Unknown |
| License | Proprietary | Unknown |
| Commercial use | commercial use per vendor terms | See license terms |
| Pricing per 1M tokens | ||
| Input $/1M | $2.00 | $0.320 |
| Output $/1M | $6.00 | $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 |
Vision Evalsground-truth scores across 5 vision tasks, pooled at low effort | ||
| Overall | 63.5% | 58.9% |
| Avg cost / sample | $0.020 | $0.0008 |
| Avg speed / sample | 33.31s | 7.77s |
| By task | ||
| Object Detection (low) | 40.4% ±0.6, Mean of 3 runs, range 39.8 to 41.0 | 60.1% |
| Object Detection (high) | 41.2% ±1.6, Mean of 3 runs, range 39.6 to 42.8 | – |
| Counting (low) | 61.7% ±1.3, Mean of 3 runs, range 60.8 to 63.5 | 50.0% |
| Counting (high) | 60.8% ±1.3, Mean of 3 runs, range 59.5 to 62.2 | – |
| Identification (low) | 87.5% ±3.1, Mean of 3 runs, range 84.4 to 90.6 | 84.4% |
| Identification (high) | 80.2% ±1.6, Mean of 3 runs, range 78.1 to 81.3 | – |
| OCR (low) | 63.6% | 60.3% |
| by category |
|
|
| OCR (high) | – | 65.5% |
| by category |
| |
| Reasoning (low) | 64.2% ±2.3, Mean of 3 runs, range 62.3 to 66.9 | 39.7% |
| Reasoning (high) | 66.9% ±1.3, Mean of 3 runs, range 65.6 to 68.2 | 68.2% |
Grok 4.7 vs Qwen3.7 Plus: Overview
Grok 4.7 is a proprietary multimodal reasoning model from SpaceXAI that accepts images alongside text and returns text-only output. On visual inputs it supports image captioning, visual question answering, OCR, document and chart question answering, and image classification and tagging, with all results expressed as generated text rather than bounding boxes or masks. Its 500,000 token context window leaves room for several images, long documents, or extended conversations about visual content in a single request.
The model exposes a configurable reasoning effort setting with low, medium, high, and xhigh levels (high by default), letting callers trade latency for the amount of deliberation spent on a prompt, including multi-step questions about an image. Built on a larger base model than Grok 4.6 with extended reinforcement learning on harder tasks, it works longer on difficult problems and checks its own work more carefully at the same serving speed. SpaceXAI's launch materials focus on coding and agentic knowledge work and report no image benchmark results.
Frequently Asked Questions
On Roboflow's Vision Evals, Grok 4.7 performed better. It scores higher on 4 of the five vision tasks and averages 63.5% (#31 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, Grok 4.7 leads with 64.2% 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 $0.020. Grok 4.7 is priced at $2.00 per 1M input tokens and $6.00 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.
Qwen3.7 Plus is faster. Across Roboflow's Vision Evals it averaged 7.8s per inference against 33.3s. 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.