Qwen3.6 27B vs Qwen3.6 Plus

Compare Qwen3.6 27B and Qwen3.6 Plus side-by-side. See how these vision models stack up in Image Captioning, OCR, and Open Prompt.

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QwenQwen3.6 27B
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Qwen3.6 27B vs Qwen3.6 Plus: Overview

Qwen3.6 27B

Qwen3.6-27B is a dense 27-billion-parameter multimodal language model developed by Alibaba's Qwen team and released on April 22, 2026. It combines a causal language model with an integrated vision encoder, supporting text, image, and video inputs natively. The architecture employs a hybrid attention design that interleaves Gated DeltaNet linear attention blocks with standard Gated Attention layers across 64 transformer layers with a hidden dimension of 5,120. Unlike Mixture-of-Experts variants in the Qwen3.6 family, all 27 billion parameters are active on every inference pass, simplifying deployment and quantization. The model supports a native context window of 262,144 tokens, extensible to approximately 1,010,000 tokens via YaRN scaling. It is released under the Apache 2.0 license with open weights available on Hugging Face and ModelScope.

The model introduces two notable capabilities relative to prior Qwen releases: enhanced agentic coding support covering frontend workflows and repository-level reasoning, and a Thinking Preservation mechanism that retains chain-of-thought reasoning context across multi-turn conversation history to reduce redundant token generation in iterative agent sessions. It supports both a thinking mode for multi-step reasoning and a non-thinking mode for faster responses within a single model. On coding benchmarks, Qwen reports scores of 77.2 on SWE-bench Verified, 59.3 on Terminal-Bench 2.0, and 48.2 on SkillsBench. Vision capabilities include chart understanding (CharXiv RQ: 78.4), OCR (CC-OCR: 81.2), and video understanding (VideoMME with subtitles: 87.7).

Qwen3.6 Plus

Qwen3.6 Plus is a flagship model in Alibaba’s Qwen Plus series, designed for agentic workflows, coding, and multi-step reasoning. It supports a 1 million token context window and up to 65,536 output tokens, with built-in reasoning capabilities. The model is available as a hosted, proprietary API through Alibaba Cloud.

Compared to Qwen3.5, it improves reliability in multi-step execution and frontend code generation, with stronger performance on agentic coding tasks. It also supports document and image understanding, though its vision capabilities are more limited than dedicated Qwen-VL models. Qwen3.6 Plus is part of a broader Qwen ecosystem that includes both closed-source APIs and open-weight models.

Qwen3.6 27B vs Qwen3.6 Plus Comparison Table

PropertyQwen3.6 27BQwen3.6 Plus
OrganizationQwenQwen
Categoryopenclosed
Modalitymultimodalmultimodal
Release DateApr 2026Apr 2026
Context Window262K1.0M
Parameters27B
LicenseApache 2.0Proprietary
Pricing per 1M tokens
Input $/1M$0.289$0.325
Output $/1M$3.17$1.95
Vision Tasks
CaptioningDemoDemo
OCRDemoDemo
Vision Language
Visual Question AnsweringDemoDemo
Chart Question Answering
Document Question Answering
Object Detection
Video Classification
Model Features
LLMs with Vision Capabilities
Multimodal Vision
Foundation Vision
Vision Evalspass/fail results · 67 prompts
Score key:≥75%40–74%<40%
Overall Score
68.66%
Avg Response Time34.17s
Median input tokensincl. image tokens1.2K
Median output tokens47
Est. cost / taskon this benchmark$0.0005
Defect Detection
86.7%(13/15)
Document Understanding
77.8%(7/9)
Object Counting
20%(2/10)
Object Understanding
78.6%(11/14)
Spatial Understanding
68.4%(13/19)

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