GPT-4.1 nano vs Qwen3.5 397B A17B
We don't benchmark GPT-4.1 nano or Qwen3.5 397B A17B on Vision Evals. GPT-4.1 nano is proprietary under Proprietary: commercial use per vendor terms. Qwen3.5 397B A17B is open-weight under Apache 2.0: free for commercial use. GPT-4.1 nano is cheaper per token ($0.10/M vs $0.50/M input).
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GPT-4.1 nano is deprecated and can no longer be run. Details and evals are still available on its model page.
GPT-4.1 nano vs Qwen3.5 397B A17B Comparison Table
Pricing updated November 2, 2026
| Property | GPT-4.1 nano | Qwen3.5 397B A17B |
|---|---|---|
| Organization | OpenAI | Qwen |
| Category | closed | open |
| Modality | multimodal | multimodal |
| Release Date | Apr 2025 | Feb 2026 |
| Context Window | 1.0M | 262K |
| Parameters | Unknown | 397B |
| License | Proprietary | Apache 2.0 |
| Commercial use | commercial use per vendor terms | free for commercial use |
| Pricing per 1M tokens | ||
| Input $/1M | $0.100 | $0.500 |
| Output $/1M | $0.400 | $3.60 |
| Vision Tasks | ||
| Captioning | Supported | Demo |
| OCR | Supported | Demo |
| Visual Question Answering | Supported | Demo |
| Model Features | ||
Both support 3 more features | ||
GPT-4.1 nano vs Qwen3.5 397B A17B: Overview
GPT-4.1 nano, released by OpenAI in April 2025, is the smallest and most cost-efficient member of the GPT-4.1 family. It is multimodal, supporting both text and image inputs, and retains the family’s extended 1 million-token context window—allowing it to handle large documents or codebases despite its lightweight design. Its training knowledge extends to June 2024.
GPT-4.1 nano prioritizes speed and affordability over raw reasoning power. While less capable than GPT-4.1 and GPT-4.1 mini, it is well-suited for high-volume or latency-sensitive workloads such as classification, autocomplete, content moderation, and lightweight assistants. This makes it an attractive option for developers seeking scalable deployment where efficiency is more critical than deep reasoning.
Qwen3.5-397B-A17B is a 397B-parameter (17B active) open-weight multimodal model developed by Alibaba’s Qwen team, released on 2026-02-16 under Apache-2.0. It supports text and image inputs with text outputs, combining a sparse Mixture-of-Experts architecture with Gated Delta Networks for efficient scaling. The model provides native vision-language reasoning and a large ~262K token context window, extendable to ~1M tokens.
As the first open-weight release in the Qwen3.5 family, it positions itself as a high-capacity, long-context alternative in the large vision-language space, balancing scale and efficiency via sparse activation. It is designed for advanced reasoning, coding, agent workflows, and multimodal understanding tasks.