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GPT-4.1 vs Qwen3 VL 235B A22B Instruct

Compare GPT-4.1 and Qwen3 VL 235B A22B Instruct side-by-side. See how these vision models stack up in Open Prompt, Image Captioning, and OCR.

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OpenAIGPT-4.1

GPT-4.1 is deprecated and can no longer be run. Details and evals are still available on its model page.

QwenQwen3 VL 235B A22B Instruct
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GPT-4.1 vs Qwen3 VL 235B A22B Instruct Comparison Table

Evals updated August 6, 2026Pricing updated August 7, 2026

PropertyGPT-4.1Qwen3 VL 235B A22B Instruct
OrganizationOpenAIQwen
Categoryclosedopen
Modalitymultimodalmultimodal
Release DateApr 2025Sep 2025
Context Window1.0M256K
Parameters235B
LicenseProprietaryApache 2.0
Pricing per 1M tokens
Input $/1M$2.00$0.210
Output $/1M$8.00$1.90
Vision Tasks
CaptioningDemo
Chart Question Answering
Classification
Document Question Answering
Image Tagging
Multi-Label Classification
Object Detection
OCRDemo
Vision Language
Visual Question AnsweringDemo
Model Features
Foundation Vision
LLMs with Vision Capabilities
Multimodal Vision
Vision Evalsground-truth scores across 6 vision tasks, pooled at low effort
OverallDeprecated
65.8%
Avg cost / sample$0.0007
Avg speed / sample9.17s
By task
Object Detection
52.2%
$0.0014
Counting
47.3%
$0.0002
Identification
90.6%
$0.0002
OCR
88.1%
$0.0010
Data Extraction
86.6%
$0.0002
Reasoning (low)
29.8%
$0.0002
Reasoning (high)
33.8%
$0.0002

GPT-4.1 vs Qwen3 VL 235B A22B Instruct: Overview

GPT-4.1

GPT-4.1, released by OpenAI in April 2025, is a multimodal large language model that advances the GPT-4 series with major improvements in coding, reasoning, and instruction following. It accepts both text and images, supports tool calling and structured outputs, and features an expanded context window of up to ~1 million tokens—enabling it to process very large documents, multi-file codebases, or long conversations in a single prompt. Its knowledge is current through June 2024.

The GPT-4.1 family includes standard, mini, and nano variants, offering trade-offs between performance, cost, and latency. While parameter counts remain undisclosed, the series improves efficiency and responsiveness compared to GPT-4, making it suitable for both enterprise-scale tasks and cost-sensitive applications. Common use cases include software development, technical research, knowledge management, multimodal analysis, and high-context enterprise assistants.

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.