Gemini 2.5 Pro vs Grok 4.7
Compare Gemini 2.5 Pro and Grok 4.7 side-by-side.
Compare Gemini 2.5 Pro vs Grok 4.7 live
Run the same image across every model that supports a task and compare their outputs side-by-side.
These models don't share enough common tasks for a side-by-side demo. See the comparison table below for their capabilities.
Models in this comparison
Gemini 2.5 Pro vs Grok 4.7 on Vision Evals
Grok 4.7 scores higher on 5 of the six Vision Evals tasks.
The widest gap is Reasoning, where Grok 4.7 leads 64.2% to 42.4%.
Overall, Gemini 2.5 Pro averages 66.0% (#35 of 54) against 71.9% (#22 of 54) for Grok 4.7.
Gemini 2.5 Pro is both cheaper ($0.0050 vs $0.012 per sample) and faster (6.1s vs 23.6s per sample).
Gemini 2.5 Pro vs Grok 4.7 Comparison Table
Evals updated September 22, 2026Pricing updated September 22, 2026
| Property | Gemini 2.5 Pro | Grok 4.7 |
|---|---|---|
| Organization | SpaceXAI | |
| Category | closed | closed |
| Modality | multimodal | — |
| Release Date | Jun 2025 | Sep 2026 |
| Context Window | 1.0M | 500K |
| Parameters | ||
| License | Proprietary | Proprietary |
| Pricing per 1M tokens | ||
| Input $/1M | $1.25 | $1.60 |
| Output $/1M | $10.00 | $4.80 |
| Vision Tasks | ||
| Captioning | Demo | |
| Chart Question Answering | ||
| Classification | Demo | |
| Document Question Answering | ||
| Image Tagging | ||
| Multi-Label Classification | ||
| Object Detection | Demo | |
| OCR | Demo | |
| Vision Language | ||
| Visual Question Answering | Demo | |
| Model Features | ||
| Foundation Vision | ||
| LLMs with Vision Capabilities | ||
| Multimodal Vision | ||
Vision Evalsground-truth scores across 6 vision tasks, pooled at low effort | ||
| Overall | 66.0% | 71.9% |
| Avg cost / sample | $0.0050 | $0.012 |
| Avg speed / sample | 6.11s | 23.55s |
| By task | ||
| Object Detection (low) | 33.7% | 40.4% ±0.6, Mean of 3 runs, range 39.8 to 41.0 |
| Object Detection (high) | – | 41.2% ±1.6, Mean of 3 runs, range 39.6 to 42.8 |
| Counting (low) | 52.7% | 61.7% ±1.3, Mean of 3 runs, range 60.8 to 63.5 |
| Counting (high) | – | 60.8% ±1.3, Mean of 3 runs, range 59.5 to 62.2 |
| Identification (low) | 93.8% | 87.5% ±3.1, Mean of 3 runs, range 84.4 to 90.6 |
| Identification (high) | – | 80.2% ±1.6, Mean of 3 runs, range 78.1 to 81.3 |
| OCR (low) | 88.8% | 92.6% ±0.7, Mean of 3 runs, range 92.1 to 93.4 |
| OCR (high) | – | 93.5% ±0.3, Mean of 3 runs, range 93.1 to 93.8 |
| Data Extraction (low) | 84.5% | 84.9% ±2.6, Mean of 3 runs, range 82.5 to 87.6 |
| Data Extraction (high) | – | 87.6% ±1.5, Mean of 3 runs, range 86.6 to 89.7 |
| Reasoning (low) | 42.4% | 64.2% ±2.3, Mean of 3 runs, range 62.3 to 66.9 |
| Reasoning (high) | 62.3% | 66.9% ±1.3, Mean of 3 runs, range 65.6 to 68.2 |
Gemini 2.5 Pro vs Grok 4.7: Overview
Gemini 2.5 Pro, released on June 17, 2025, is Google DeepMind’s most capable model in the Gemini 2.5 family, optimized for deep reasoning, coding, and complex multimodal tasks. It accepts text, images, audio, video, and PDFs as input and outputs text. The model supports 1 million input tokens with an output capacity of up to 65K tokens, enabling large-scale comprehension of datasets, codebases, and technical documents. Its training knowledge extends to January 2025.
Pro outperforms earlier Gemini 2.0 models across benchmarks, including agentic coding tasks where it achieved ~63.8% on SWE-Bench Verified. It supports structured outputs, function calling, code execution, search grounding, and URL context, making it well-suited for enterprise, STEM, and developer workflows. However, it does not currently support image or audio generation in its stable release, and its higher computational cost and latency make it less efficient than Flash or Flash-Lite. It is available via the Gemini API, Google AI Studio, and Vertex AI.
Grok 4.7 is a proprietary model from SpaceXAI, released on September 21, 2026. It accepts text and images as input and returns text. It extends Grok 4.6 and is listed at the same API price.
Its Vision Evals scores are on the leaderboard. Running it in the Playground is not available yet, because the inference workflow is not ready.
Frequently Asked Questions
On Roboflow's Vision Evals, Grok 4.7 performed better. It scores higher on 5 of the six vision tasks and averages 71.9% (#22 of 54) against 66.0% (#35 of 54) for Gemini 2.5 Pro. These scores measure vision capabilities only; either model may perform differently on work outside this benchmark's tasks.
No. On the Vision Evals Reasoning benchmark at low effort, Grok 4.7 leads with 64.2% against 42.4%. This is the widest gap between the two models across the benchmark's tasks.
Gemini 2.5 Pro is cheaper to run. Across Roboflow's Vision Evals task mix it averaged $0.0050 per sample against $0.012. Gemini 2.5 Pro is priced at $1.25 per 1M input tokens and $10.00 per 1M output; Grok 4.7 is priced at $1.60 per 1M input tokens and $4.80 per 1M output. Actual costs depend on your image sizes, prompts, and output length.
Gemini 2.5 Pro is faster. Across Roboflow's Vision Evals it averaged 6.1s per inference against 23.6s. Latency varies with image size, prompt length, and provider load, so treat these as relative rather than guaranteed figures.