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Claude Sonnet 5 vs Qwen3 VL 235B A22B Instruct

Compare Claude Sonnet 5 and Qwen3 VL 235B A22B Instruct side-by-side. See how these vision models stack up in Object Detection, Open Prompt, OCR, Classification, and Image Captioning.

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AnthropicClaude Sonnet 5
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QwenQwen3 VL 235B A22B Instruct
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Models in this comparison

Claude Sonnet 5 vs Qwen3 VL 235B A22B Instruct on Vision Evals

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

The widest gap is Object Detection, where Qwen3 VL 235B A22B Instruct leads 52.1% to 36.1%.

Overall, Claude Sonnet 5 averages 55.3% (#47 of 63) against 55.2% (#48 of 63) for Qwen3 VL 235B A22B Instruct.

Qwen3 VL 235B A22B Instruct is cheaper ($0.0011 vs $0.0074 per sample), while Claude Sonnet 5 is faster (5.9s vs 15.9s per sample).

Claude Sonnet 5Qwen3 VL 235B A22B Instruct

Claude Sonnet 5 vs Qwen3 VL 235B A22B Instruct Comparison Table

Evals updated October 13, 2026Pricing updated October 19, 2026

PropertyClaude Sonnet 5Qwen3 VL 235B A22B Instruct
OrganizationAnthropicQwen
Categoryclosedopen
Modalitymultimodalmultimodal
Release DateJun 2026Sep 2025
Context Window1.0M256K
ParametersUnknown235B
LicenseProprietaryApache 2.0
Commercial usecommercial use per vendor termsfree for commercial use
Pricing per 1M tokens
Input $/1M$2.00$0.210
Output $/1M$10.00$1.90
Vision Tasks
CaptioningDemoDemo
Chart Question AnsweringSupportedSupported
ClassificationDemoDemo
Document Question AnsweringSupportedSupported
Image TaggingSupportedSupported
Multi-Label ClassificationSupportedSupported
Object DetectionDemoDemo
OCRDemoDemo
Vision LanguageSupportedSupported
Visual Question AnsweringDemoDemo
Model Features
Foundation VisionSupportedSupported
LLMs with Vision CapabilitiesSupportedSupported
Multimodal VisionSupportedSupported
Vision Evalsground-truth scores across 5 vision tasks, pooled at low effort
Overall
55.3%
55.2%
Avg cost / sample$0.0074$0.0011
Avg speed / sample5.86s15.87s
By task
Object Detection
36.1%
$0.011
52.1%
$0.0014
Counting
56.8%
$0.0030
47.3%
$0.0002
Identification
81.3%
$0.0027
90.6%
$0.0002
OCR (low)
59.4%
$0.0078
56.4%
$0.0013
by category
Single value
52.2%
Transcription
88.6%
Structured JSON
78.3%
Text localization
13.1%
Single value
48.3%
Transcription
84.3%
Structured JSON
71.0%
Text localization
24.0%
OCR (high)
59.5%
$0.015
55.5%
$0.0013
by category
Single value
54.8%
Transcription
88.3%
Structured JSON
76.6%
Text localization
11.6%
Single value
46.5%
Transcription
84.1%
Structured JSON
71.4%
Text localization
21.6%
Reasoning (low)
43.0%
$0.0032
29.8%
$0.0002
Reasoning (high)
43.0%
$0.0043
33.8%
$0.0002

Claude Sonnet 5 vs Qwen3 VL 235B A22B Instruct: 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.

Qwen3 VL 235B A22B Instruct

Qwen3 VL 235B A22B Instruct is a flagship multimodal vision-language model developed by Qwen (Alibaba Cloud), designed for instruction-following tasks that combine advanced text generation with visual understanding. It serves as a high-end open-weight model for developers and researchers building multimodal AI systems that require strong reasoning, perception, and long-context capabilities.

The model supports interleaved text and image inputs, very long context windows (up to roughly 256K tokens), and efficient inference through a mixture-of-experts architecture with about 22B active parameters out of 235B total. In today’s landscape, it competes with top-tier proprietary vision-language models while offering the advantages of open weights and flexible deployment. Typical applications include multimodal assistants, document and image analysis, visual reasoning, and large-context instruction-based workflows.