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Claude Sonnet 5 vs Grok 4.6

Grok 4.6 and Claude Sonnet 5 score 59.1% vs 55.3% averaged across five Vision Evals tasks (#42 and #53 of 69 models), so Grok 4.6 leads overall.

  • Grok 4.6 wins 4 of the 5 tasks, with its widest lead on reasoning (61.1% vs 43.0%).
  • Claude Sonnet 5 is cheaper: $0.0074 vs $0.011 overall average cost per sample.
  • Claude Sonnet 5 is faster: 5.9s vs 19.3s per sample.

Compare Claude Sonnet 5 vs Grok 4.6 live

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AnthropicClaude Sonnet 5
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GrokGrok 4.6
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Claude Sonnet 5 vs Grok 4.6 on Vision Evals

Score by taskClaude Sonnet 5Grok 4.6
Reasoning
43.0
61.1
Object Detection
36.1
23.8
Counting
56.8
65.8
Identification
81.3
84.4
OCR
59.4
60.6

Roboflow Vision Evals. Full breakdown below.

Claude Sonnet 5 vs Grok 4.6 Comparison Table

Evals updated November 12, 2026Pricing updated November 13, 2026

PropertyClaude Sonnet 5Grok 4.6
OrganizationAnthropicSpaceXAI
Categoryclosedclosed
Modalitymultimodalmultimodal
Release DateJun 2026Aug 2026
Context Window1.0M500K
ParametersUnknownUnknown
LicenseProprietaryProprietary
Commercial usecommercial use per vendor termscommercial use per vendor terms
Pricing per 1M tokens
Input $/1M$2.00$2.00
Output $/1M$10.00$6.00
Vision Tasks
Both support 10 more tasks
Model Features
Both support 3 more features
Vision Evalsground-truth scores across 5 vision tasks, pooled at low effort
Overall
55.3%
59.1%
Avg cost / sample$0.0074$0.011
Avg speed / sample5.86s19.32s
By task
Object Detection (low)
36.1%
$0.011
23.8%
±2.8, Mean of 3 runs, range 20.2 to 25.9
$0.013
Object Detection (high)–
24.0%
±1.0, Mean of 3 runs, range 23.1 to 25.1
$0.041
Counting (low)
56.8%
$0.0030
65.8%
±4.1, Mean of 3 runs, range 62.2 to 70.3
$0.0079
Counting (high)–
56.8%
±1.4, Mean of 3 runs, range 55.4 to 58.1
$0.027
Identification (low)
81.3%
$0.0027
84.4%
±3.1, Mean of 3 runs, range 81.3 to 87.5
$0.0055
Identification (high)–
85.4%
±1.6, Mean of 3 runs, range 84.4 to 87.5
$0.015
OCR (low)
59.4%
$0.0078
60.6%
$0.011
by category
Single value
52.2%
Transcription
88.6%
Structured JSON
78.3%
Text localization
13.1%
Single value
50.0%
Transcription
89.0%
Structured JSON
84.4%
Text localization
11.0%
OCR (high)
59.5%
$0.015
61.2%
$0.030
by category
Single value
54.8%
Transcription
88.3%
Structured JSON
76.6%
Text localization
11.6%
Single value
50.9%
Transcription
88.7%
Structured JSON
85.7%
Text localization
9.4%
Reasoning (low)
43.0%
$0.0032
61.1%
±1.3, Mean of 3 runs, range 59.6 to 62.3
$0.0093
Reasoning (high)
43.0%
$0.0043
63.8%
±2.0, Mean of 3 runs, range 62.3 to 66.2
$0.032

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.

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, and it can also return object detection boxes as text coordinates when prompted.

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.

Frequently Asked Questions

On Roboflow's Vision Evals, Grok 4.6 performed better. It scores higher on 4 of the five vision tasks and averages 59.1% (#42 of 69) against 55.3% (#53 of 69) 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 61.1% 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 $0.0074 per sample against $0.011. 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 5.9s per inference against 19.3s. 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 object detection and open prompts in the free Roboflow Playground. You can try it instantly, and a free account unlocks unlimited runs.