GPT-4.1 vs Qwen3.5-27B
Qwen3.5-27B: 64.1% average across four Vision Evals tasks (#32 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 Qwen3.5-27B Comparison Table
Evals updated October 26, 2026Pricing updated November 3, 2026
| Property | GPT-4.1 | Qwen3.5-27B |
|---|---|---|
| Organization | OpenAI | Qwen |
| Category | closed | open |
| Modality | multimodal | multimodal |
| Release Date | Apr 2025 | Feb 2026 |
| Context Window | 1.0M | 262K |
| Parameters | Unknown | 27B |
| License | Proprietary | Apache 2.0 |
| Commercial use | commercial use per vendor terms | free for commercial use |
| Pricing per 1M tokens | ||
| Input $/1M | $2.00 | $0.260 |
| Output $/1M | $8.00 | $2.60 |
| 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 | ||
| Overall | Deprecated | 64.1%* |
| Quantizationsself-hosted | ||
| Avg cost / sample | – | $0.0043 |
| Avg speed / sample | – | 80.37s |
| By task | ||
| Object Detection | – | 50.5% ±3.5, Mean of 3 runs, range 46.1 to 53.0 |
| Counting | – | 67.6% ±1.4, Mean of 3 runs, range 66.2 to 68.9 |
| Identification | – | 80.2% ±4.7, Mean of 3 runs, range 75.0 to 84.4 |
| OCR | – | – |
| by category | ||
| Reasoning | – | 58.1% ±2.3, Mean of 3 runs, range 55.6 to 60.3 |
GPT-4.1 vs Qwen3.5-27B: 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.
Qwen3.5-27B is a multimodal dense hybrid model developed by Alibaba Cloud’s Qwen team and released in February 2026 as a high-precision entry in the Qwen3.5 "Medium" series. Unlike its Mixture-of-Experts (MoE) siblings, the 27B model utilizes a dense architecture combining Gated Delta Networks with a feed-forward structure, activating its full parameter suite for every inference to maximize reliability. The model features a native 262K-token context window, extensible to 1M tokens via YaRN (RoPE scaling), and is released under the Apache-2.0 license.
Optimized for agentic workflows, Qwen3.5-27B employs an early-fusion architecture that treats visual and textual data as a unified stream for deep cross-modal reasoning. While the larger MoE variants in the family lead in raw knowledge benchmarks, the 27B model offers a stable and high-density alternative for structured data extraction and spatial perception, contributing to the Qwen3.5 family’s generational leap in OCR accuracy over the previous Qwen3-VL series.