GPT-5.1 vs Qwen3.5 397B A17B

Compare GPT-5.1 and Qwen3.5 397B A17B side-by-side. See how these vision models stack up in Image Captioning, Open Prompt, and OCR.

Compare GPT-5.1 vs Qwen3.5 397B A17B live

Run the same image across every model that supports a task and compare their outputs side-by-side.

Extract and compare text from images across multiple models.

Open OCR in the full playground
OpenAIGPT-5.1
Run to compare this model.
QwenQwen3.5 397B A17B
Run to compare this model.

Models in this comparison

OpenAI

GPT-5.1 vs Qwen3.5 397B A17B: Overview

GPT-5.1

GPT-5.1 is an OpenAI frontier-grade model in the GPT-5 series, offering stronger general-purpose reasoning, clearer long-form responses, and improved instruction following. It introduces two variants—Instant and Thinking—that dynamically adjust computational depth. Instant focuses on fast, conversational replies, while Thinking provides deeper, more thorough reasoning for complex tasks. In ChatGPT, GPT-5.1 also powers an Auto mode that switches between these variants automatically based on task difficulty.

The model supports significantly expanded context windows: up to 16K/32K/128K tokens for Instant (depending on tier) and up to 196K tokens for Thinking on paid tiers. GPT-5.1 is also compatible with ChatGPT tools such as web search, file and image analysis, and multi-step workflows.

GPT-5.1 includes enhanced tone and style controls, allowing responses to be tailored using presets like Friendly, Professional, or Efficient, along with fine-grained adjustments for warmth, brevity, and emoji usage. Designed for broad applications in research assistance, coding, analysis, and conversational agents, GPT-5.1 serves as OpenAI’s primary full-capability successor to GPT-5 across ChatGPT and API integrations.

Qwen3.5 397B A17B

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.

GPT-5.1 vs Qwen3.5 397B A17B Comparison Table

PropertyGPT-5.1Qwen3.5 397B A17B
OrganizationOpenAIQwen
Categoryclosedopen
Modalitymultimodalmultimodal
Release DateNov 2025Feb 2026
Context Window196K262K
Parameters397B
LicenseProprietaryApache 2.0
Pricing per 1M tokens
Input $/1M$1.25$0.385
Output $/1M$10.00$2.45
Vision Tasks
CaptioningDemoDemo
Object DetectionDemo
OCRDemoDemo
Vision Language
Visual Question AnsweringDemoDemo
ClassificationDemo
Model Features
LLMs with Vision Capabilities
Multimodal Vision
Foundation Vision
Vision Evalspass/fail results · 67 prompts
Score key:≥75%40–74%<40%
Overall Score
58.21%
Avg Response Time56.61s
Median input tokensincl. image tokens1.1K
Median output tokens54
Est. cost / taskon this benchmark$0.0006
Defect Detection
66.7%(10/15)
Document Understanding
77.8%(7/9)
Object Counting
20%(2/10)
Object Understanding
64.3%(9/14)
Spatial Understanding
57.9%(11/19)

Output tokens (incl. reasoning) and est. cost / task are measured on this benchmark from a single low-temperature run, and shown only for models whose run covered at least 90% of prompts. Methodology