Claude Opus 5 vs Grok 4.7
Compare Claude Opus 5 and Grok 4.7 side-by-side.
Compare Claude Opus 5 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
Claude Opus 5 vs Grok 4.7 on Vision Evals
Claude Opus 5 scores higher on all six Vision Evals tasks.
The widest gap is Object Detection, where Claude Opus 5 leads 54.4% to 40.4%.
Overall, Claude Opus 5 averages 78.3% (#14 of 54) against 71.9% (#22 of 54) for Grok 4.7.
Grok 4.7 is cheaper ($0.012 vs $0.017 per sample), while Claude Opus 5 is faster (7.4s vs 23.6s per sample).
Claude Opus 5 vs Grok 4.7 Comparison Table
Evals updated September 22, 2026Pricing updated September 22, 2026
| Property | Claude Opus 5 | Grok 4.7 |
|---|---|---|
| Organization | Anthropic | SpaceXAI |
| Category | closed | closed |
| Modality | multimodal | — |
| Release Date | Jul 2026 | Sep 2026 |
| Context Window | 1.0M | 500K |
| Parameters | ||
| License | Proprietary | Proprietary |
| Pricing per 1M tokens | ||
| Input $/1M | $5.00 | $1.60 |
| Output $/1M | $25.00 | $4.80 |
| Vision Tasks | ||
| Captioning | Demo | |
| Chart Question Answering | ||
| Classification | Demo | |
| Document Question Answering | ||
| Multi-Label Classification | ||
| Object Detection | Demo | |
| OCR | Demo | |
| Vision Language | ||
| Visual Question Answering | Demo | |
| Image Tagging | ||
| Model Features | ||
| Foundation Vision | ||
| LLMs with Vision Capabilities | ||
| Multimodal Vision | ||
Vision Evalsground-truth scores across 6 vision tasks, pooled at low effort | ||
| Overall | 78.3% | 71.9% |
| Avg cost / sample | $0.017 | $0.012 |
| Avg speed / sample | 7.38s | 23.55s |
| By task | ||
| Object Detection (low) | 54.4% | 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) | 70.3% | 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) | 90.6% | 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) | 93.2% | 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) | 89.7% | 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) | 71.5% | 64.2% ±2.3, Mean of 3 runs, range 62.3 to 66.9 |
| Reasoning (high) | 74.2% | 66.9% ±1.3, Mean of 3 runs, range 65.6 to 68.2 |
Claude Opus 5 vs Grok 4.7: Overview
Claude Opus 5 is a large language model with multimodal vision capabilities developed by Anthropic, released on July 24, 2026 as the fourth model in the Claude 5 family. It sits in the Opus tier of Anthropic's lineup, positioned below the Mythos-class Fable 5 and Mythos 5 models, and is framed by Anthropic as the go-to model for most knowledge work and automation tasks. The model approaches Fable 5's capabilities at roughly half the cost, priced at $5 per million input tokens and $25 per million output tokens. It becomes the default model on Claude Max and the strongest model available on Claude Pro. The model ships with a 1 million token context window and an adjustable "effort" parameter that allows users to trade reasoning depth for speed and token savings. Early enterprise customers reported that Opus 5 achieved comparable performance to Opus 4.8's maximum-reasoning mode while generating significantly fewer tokens on average, and demonstrated higher accuracy on financial modeling tasks with fewer tool calls and less time.
Claude Opus 5 supports multimodal inputs including images and text, and is designed for agentic workflows, coding, scientific research, and complex enterprise tasks. Anthropic reports the model scores 10.2 percentage points higher than Opus 4.8 on an internal chemistry benchmark, making it the most capable generally available model for scientific research in the Claude lineup. Cyber classifiers on Opus 5 are designed to intervene approximately 85 percent less often than those on Fable 5, with fallback to Opus 4.8 when a classifier triggers. The model does not retain user data for 30 days, unlike Fable 5. It is available across Anthropic's platforms including Claude Code and Claude Cowork, as well as cloud partners.
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, Claude Opus 5 performed better. It scores higher on all six vision tasks and averages 78.3% (#14 of 54) against 71.9% (#22 of 54) for Grok 4.7. These scores measure vision capabilities only; either model may perform differently on work outside this benchmark's tasks.
Yes. On the Vision Evals Object Detection benchmark at low effort, Claude Opus 5 leads with 54.4% against 40.4%. This is the widest gap between the two models across the benchmark's tasks.
Grok 4.7 is cheaper to run. Across Roboflow's Vision Evals task mix it averaged $0.012 per sample against $0.017. Claude Opus 5 is priced at $5.00 per 1M input tokens and $25.00 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.
Claude Opus 5 is faster. Across Roboflow's Vision Evals it averaged 7.4s per inference against 23.6s. Latency varies with image size, prompt length, and provider load, so treat these as relative rather than guaranteed figures.