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Muse Spark 1.1 vs Qwen3.6 Plus

Compare Muse Spark 1.1 and Qwen3.6 Plus side-by-side. See how these vision models stack up in OCR, Image Captioning, and Open Prompt.

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MetaMuse Spark 1.1
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QwenQwen3.6 Plus
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Models in this comparison

Muse Spark 1.1 vs Qwen3.6 Plus Comparison Table

Evals updated August 6, 2026Pricing updated August 11, 2026

PropertyMuse Spark 1.1Qwen3.6 Plus
OrganizationMetaQwen
Categoryclosedclosed
Modalitymultimodalmultimodal
Release DateJul 2026Apr 2026
Context Window1.0M1.0M
Parameters
LicenseProprietaryProprietary
Pricing per 1M tokens
Input $/1M$1.25$0.325
Output $/1M$4.25$1.95
Vision Tasks
CaptioningDemoDemo
Chart Question Answering
ClassificationDemo
Document Question Answering
Image Tagging
Multi-Label Classification
Object DetectionDemo
OCRDemoDemo
Vision Language
Visual Question AnsweringDemoDemo
Model Features
Foundation Vision
LLMs with Vision Capabilities
Multimodal Vision
Vision Evalsground-truth scores across 6 vision tasks, pooled at low effort
Overall
79.2%
Not evaluated
Avg cost / sample$0.0069
Avg speed / sample11.40s
By task
Object Detection
58.2%
$0.010
Counting
75.7%
$0.0043
Identification
87.5%
$0.0032
OCR
92.5%
$0.0063
Data Extraction
86.6%
$0.0031
Reasoning (low)
74.8%
$0.0065
Reasoning (high)
76.2%
$0.013

Muse Spark 1.1 vs Qwen3.6 Plus: Overview

Muse Spark 1.1

Muse Spark 1.1 is a natively multimodal reasoning model from Meta Superintelligence Labs, released on July 9, 2026, as a significant upgrade to the original Muse Spark. The model accepts text, image, video, PDF, and audio as input and produces text output. It operates with a 1-million-token context window (1,048,576 tokens per the Meta Model API documentation) and is designed specifically for agentic tasks that require planning, tool use, computer use, and multi-agent orchestration. The model runs in a "Thinking" mode, where adjustable reasoning effort is applied before generating a response. It can function both as a main agent gathering context, forming plans, and delegating to parallel subagents and as a subagent that adheres to assigned tasks and escalates when needed. It is trained to decide autonomously when to write automation scripts versus interact directly with a user interface.

Muse Spark 1.1 supports a range of multimodal capabilities including visual perception, image and video captioning, visual-to-code generation, and document analysis. The model was evaluated under Meta's Advanced AI Scaling Framework across frontier risk categories including chemical and biological threats, cybersecurity, and loss-of-control scenarios. Parameter count, architecture details, and training data composition are not publicly disclosed. The model is proprietary and closed-weight, accessible to consumers through the Meta AI app and to developers via the Meta Model API, which launched in public preview alongside this release.

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.

Frequently Asked Questions

Qwen3.6 Plus has not yet been evaluated on Roboflow's current Vision Evals, so this comparison shows specs, licensing, and pricing rather than benchmark scores.

Yes. The comparison demo on this page runs both models on the same image side by side for OCR and image captioning in the free Roboflow Playground. You can try it instantly, and a free account unlocks unlimited runs.