Qwen VL Max vs Qwen3 VL 235B A22B Instruct
Qwen3 VL 235B A22B Instruct: 55.2% average across five Vision Evals tasks (#50 of 65 models). We have not run Qwen VL Max through Roboflow's Vision Evals, so there is no head-to-head score.
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Qwen VL Max vs Qwen3 VL 235B A22B Instruct Comparison Table
Evals updated October 26, 2026Pricing updated November 7, 2026
| Property | Qwen VL Max | Qwen3 VL 235B A22B Instruct |
|---|---|---|
| Organization | Qwen | Qwen |
| Category | closed | open |
| Modality | multimodal | multimodal |
| Release Date | Feb 2025 | Sep 2025 |
| Context Window | 131K | 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 | No published price | $0.210 |
| Output $/1M | No published price | $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 | Not evaluated | 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% |
Qwen VL Max vs Qwen3 VL 235B A22B Instruct: Overview
Qwen-VL-Max is a proprietary vision-language model developed by Alibaba’s QwenLM team. Released on February 1, 2025, it is the flagship offering in the Qwen-VL family and sits above the VL-Plus tier in capability.
The model supports text and image inputs and provides a context window of up to 131,072 tokens (with a maximum input size of 129,024 tokens), according to Alibaba Cloud Model Studio. While the parameter count for VL-Max has not been publicly disclosed, the broader Qwen2.5-VL series includes open-weight models scaling up to 72B parameters.
Qwen-VL-Max is optimized for advanced multimodal applications such as document parsing, visual reasoning, multilingual analysis, and structured data extraction. Unlike the open Qwen2.5-VL variants, VL-Max is not available as open weights.
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.