Roboflow

Claude Opus 4 vs Grok 4.7

Grok 4.7: 63.5% average across five Vision Evals tasks (#33 of 65 models). Claude Opus 4 is deprecated and was not run through Roboflow's Vision Evals, so there is no head-to-head score.

Anthropic

Compare Claude Opus 4 vs Grok 4.7 live

Run the same image across every model that supports a task and compare their outputs side-by-side.

Detect and compare bounding boxes across models on the same image.

Open Object Detection in the full playground
AnthropicClaude Opus 4

Claude Opus 4 is deprecated and can no longer be run. Details and evals are still available on its model page.

GrokGrok 4.7
Run to compare this model.

Claude Opus 4 vs Grok 4.7 Comparison Table

Evals updated October 26, 2026Pricing updated November 5, 2026

PropertyClaude Opus 4Grok 4.7
OrganizationAnthropicSpaceXAI
Categoryclosedclosed
Modalitymultimodal—
Release DateMay 2025Sep 2026
Context Window200K500K
ParametersUnknownUnknown
LicenseProprietaryProprietary
Commercial usecommercial use per vendor termscommercial use per vendor terms
Pricing per 1M tokens
Input $/1MNo published price$2.00
Output $/1MNo published price$6.00
Vision Tasks
CaptioningSupportedDemo
ClassificationSupportedDemo
Object DetectionSupportedDemo
OCRSupportedDemo
Visual Question AnsweringSupportedDemo
Both support 5 more tasks
Model Features
Foundation VisionSupportedNot listed
LLMs with Vision CapabilitiesSupportedNot listed
Multimodal VisionSupportedNot listed
Vision Evalsground-truth scores across 5 vision tasks, pooled at low effort
OverallDeprecated
63.5%
Avg cost / sample–$0.020
Avg speed / sample–33.31s
By task
Object Detection (low)–
40.4%
±0.6, Mean of 3 runs, range 39.8 to 41.0
$0.021
Object Detection (high)–
41.2%
±1.6, Mean of 3 runs, range 39.6 to 42.8
$0.028
Counting (low)–
61.7%
±1.3, Mean of 3 runs, range 60.8 to 63.5
$0.011
Counting (high)–
60.8%
±1.3, Mean of 3 runs, range 59.5 to 62.2
$0.017
Identification (low)–
87.5%
±3.1, Mean of 3 runs, range 84.4 to 90.6
$0.0063
Identification (high)–
80.2%
±1.6, Mean of 3 runs, range 78.1 to 81.3
$0.0093
OCR–
63.6%
$0.023
by category
Single value
54.4%
Transcription
89.5%
Structured JSON
86.4%
Text localization
14.8%
Reasoning (low)–
64.2%
±2.3, Mean of 3 runs, range 62.3 to 66.9
$0.015
Reasoning (high)–
66.9%
±1.3, Mean of 3 runs, range 65.6 to 68.2
$0.024

Claude Opus 4 vs Grok 4.7: Overview

Claude Opus 4

Claude 4 Opus, released by Anthropic in May 2025, is the flagship model of the Claude 4 family, built for complex, long-horizon reasoning and advanced coding workflows. It is multimodal, supporting text (including voice), images, and tool use, and operates as a hybrid reasoning model—able to deliver quick answers in fast mode or switch to extended thinking for deeper, multi-step problem solving. With a ~200,000-token context window and a training cutoff around March 2025, it is optimized for handling large documents, long conversations, and sophisticated agentic tasks.

It is best suited for research, enterprise automation, and software development at scale. The model is classified at Anthropic’s ASL-3 safety level, denoting advanced oversight and safety features.

Grok 4.7

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.