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Claude Sonnet 5 vs Grok 4.6

Compare Claude Sonnet 5 and Grok 4.6 side-by-side. See how these vision models stack up in Open Prompt, OCR, Classification, and Image Captioning.

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AnthropicClaude Sonnet 5
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GrokGrok 4.6
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Models in this comparison

Claude Sonnet 5 vs Grok 4.6 on Vision Evals

Claude Sonnet 5 scores higher on 3 of the six Vision Evals tasks.

The widest gap is Reasoning, where Grok 4.6 leads 61.6% to 43.0%.

Overall, Claude Sonnet 5 averages 66.4% (#21 of 30) against 67.8% (#17 of 30) for Grok 4.6.

Claude Sonnet 5 is both cheaper ($0.0064 vs $0.0069 per sample) and faster (4.8s vs 7.4s per sample).

Claude Sonnet 5Grok 4.6

Claude Sonnet 5 vs Grok 4.6 Comparison Table

Evals updated August 14, 2026Pricing updated August 15, 2026

PropertyClaude Sonnet 5Grok 4.6
OrganizationAnthropicSpaceXAI
Categoryclosedclosed
Modalitymultimodalmultimodal
Release DateJun 2026Aug 2026
Context Window1.0M500K
Parameters
LicenseProprietaryProprietary
Pricing per 1M tokens
Input $/1M$2.00$2.00
Output $/1M$10.00$6.00
Vision Tasks
CaptioningDemoDemo
Chart Question Answering
ClassificationDemoDemo
Document Question Answering
Image Tagging
Multi-Label Classification
OCRDemoDemo
Vision Language
Visual Question AnsweringDemoDemo
Object DetectionDemo
Model Features
Foundation Vision
LLMs with Vision Capabilities
Multimodal Vision
Vision Evalsground-truth scores across 6 vision tasks, pooled at low effort
Overall
66.4%
67.8%
Avg cost / sample$0.0064$0.0069
Avg speed / sample4.84s7.39s
By task
Object Detection
36.1%
$0.011
20.2%
$0.0068
Counting
56.8%
$0.0030
70.3%
$0.0074
Identification
81.3%
$0.0027
78.1%
$0.0048
OCR
91.7%
$0.0078
92.0%
$0.0086
Data Extraction
89.7%
$0.0030
84.5%
$0.0042
Reasoning (low)
43.0%
$0.0032
61.6%
$0.0087
Reasoning (high)
43.0%
$0.0043
61.6%
$0.027

Claude Sonnet 5 vs Grok 4.6: Overview

Claude Sonnet 5

Claude Sonnet 5 is a mid-tier large language model from Anthropic, released on June 30, 2026, as the latest model in the Sonnet series and a direct successor to Claude Sonnet 4.6. It is a hybrid reasoning model designed primarily for agentic workflows, software coding, and professional tasks. The model features a 1 million token context window, a 128k maximum output token limit, and runs adaptive thinking by default, giving API users fine-grained control over reasoning effort across five levels (low, medium, high, max, and extra-high). It uses an updated tokenizer shared with Opus 4.7 and later models, which produces approximately 30% more tokens for equivalent text compared to earlier Claude models. On benchmarks, Sonnet 5 scores 63.2% on agentic coding and 81.2% on OSWorld, narrowing the gap with Opus 4.8 while remaining at Sonnet-tier pricing.

The model supports text and image input with text output, and accepts tools including browsers and terminals for autonomous multi-step task execution. Anthropic's safety evaluations report that Sonnet 5 shows a lower rate of undesirable behaviors than Sonnet 4.6 and is generally safer in agentic contexts, with improved resistance to prompt injection and reduced sycophancy. Cybersecurity safeguards equivalent to those on Opus 4.7 and 4.8 are active, though Anthropic notes the model was not deliberately trained on cybersecurity tasks. The model is proprietary and API-only, with no open weights.

Grok 4.6

Grok 4.6 is a proprietary reasoning model from xAI aimed at long-running agentic workflows, coding, and knowledge work. It accepts text and image input and returns text, with a 500,000 token context window and a knowledge cutoff of February 1, 2026. The model exposes an adjustable reasoning budget with low, medium, high, and xhigh settings, where high is the default, and it supports function calling, structured outputs, web and X search, and code execution as documented tool behaviors. Its visual capability covers interpreting images supplied alongside text prompts, which places it in the visual question answering and document understanding family rather than producing pixel level outputs such as boxes or masks.

xAI characterizes Grok 4.6 as the result of an extended post-training run over the Grok 4.5 lineage rather than a new pretrained base. The described recipe combines curated model-generated reasoning and technical data, engineering data, a revised optimizer, regenerated supervised fine-tuning trajectories, and reinforcement learning across agent environments spanning knowledge work, coding, kernel optimization, web development, and computer-aided design. Parameter count and architecture specifics are not disclosed. Independent measurement from Artificial Analysis places the model at 61 on its Intelligence Index, five points above Grok 4.5.

Frequently Asked Questions

On Roboflow's Vision Evals, Grok 4.6 performed slightly better overall. The two split the six vision tasks 3 to 3, but Grok 4.6 averages 67.8% (#17 of 30) against 66.4% (#21 of 30) for Claude Sonnet 5. 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 4.6 leads with 61.6% against 43.0%. This is the widest gap between the two models across the benchmark's tasks.

Claude Sonnet 5 is cheaper to run. Across Roboflow's Vision Evals task mix it averaged $0.0064 per sample against $0.0069. Claude Sonnet 5 is priced at $2.00 per 1M input tokens and $10.00 per 1M output; Grok 4.6 is priced at $2.00 per 1M input tokens and $6.00 per 1M output. Actual costs depend on your image sizes, prompts, and output length.

Claude Sonnet 5 is faster. Across Roboflow's Vision Evals it averaged 4.8s per inference against 7.4s. 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 open prompts and OCR in the free Roboflow Playground. You can try it instantly, and a free account unlocks unlimited runs.