GPT-4.1 vs Qwen3 VL 235B A22B Instruct
Qwen3 VL 235B A22B Instruct: 55.2% average across five Vision Evals tasks (#50 of 65 models). GPT-4.1 is deprecated and was not run through Roboflow's Vision Evals, so there is no head-to-head score.
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GPT-4.1 is deprecated and can no longer be run. Details and evals are still available on its model page.
GPT-4.1 vs Qwen3 VL 235B A22B Instruct Comparison Table
Evals updated October 26, 2026Pricing updated October 31, 2026
| Property | GPT-4.1 | Qwen3 VL 235B A22B Instruct |
|---|---|---|
| Organization | OpenAI | Qwen |
| Category | closed | open |
| Modality | multimodal | multimodal |
| Release Date | Apr 2025 | Sep 2025 |
| Context Window | 1.0M | 256K |
| Parameters | Unknown | 235B |
| License | Proprietary | Apache 2.0 |
| Commercial use | commercial use per vendor terms | free for commercial use |
| Pricing per 1M tokens | ||
| Input $/1M | $2.00 | $0.210 |
| Output $/1M | $8.00 | $1.90 |
| Vision Tasks | ||
| Captioning | Supported | Demo |
| Classification | Supported | Demo |
| Object Detection | Supported | Demo |
| OCR | Supported | Demo |
| Visual Question Answering | Supported | Demo |
| Model Features | ||
Both support 3 more features | ||
Vision Evalsground-truth scores across 5 vision tasks, pooled at low effort | ||
| Overall | Deprecated | 55.2% |
| Avg cost / sample | – | $0.0011 |
| Avg speed / sample | – | 15.87s |
| By task | ||
| Object Detection | – | 52.1% |
| Counting | – | 47.3% |
| Identification | – | 90.6% |
| OCR (low) | – | 56.4% |
| by category |
| |
| OCR (high) | – | 55.5% |
| by category |
| |
| Reasoning (low) | – | 29.8% |
| Reasoning (high) | – | 33.8% |
GPT-4.1 vs Qwen3 VL 235B A22B Instruct: Overview
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 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.