Roboflow

Muse Glimmer 30B vs Qwen3.6 Plus

Compare Muse Glimmer 30B and Qwen3.6 Plus side-by-side. See how these vision models stack up in Image Captioning, Open Prompt, and OCR.

Compare Muse Glimmer 30B vs Qwen3.6 Plus 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
MetaMuse Glimmer 30B
Run to compare this model.
QwenQwen3.6 Plus
Run to compare this model.

Models in this comparison

Muse Glimmer 30B vs Qwen3.6 Plus Comparison Table

Evals updated October 13, 2026Pricing updated October 17, 2026

PropertyMuse Glimmer 30BQwen3.6 Plus
OrganizationMetaQwen
Categoryopenclosed
Modalitymultimodalmultimodal
Release DateAug 2026Apr 2026
Context Window131K1.0M
Parameters29.6BUnknown
LicenseApache 2.0Proprietary
Commercial usefree for commercial usecommercial use per vendor terms
Pricing per 1M tokens
Input $/1M$0.300$0.325
Output $/1M$1.20$1.95
Vision Tasks
CaptioningDemoDemo
Chart Question AnsweringSupportedSupported
ClassificationDemoSupported
Document Question AnsweringSupportedSupported
Image TaggingSupportedSupported
Multi-Label ClassificationSupportedSupported
Object DetectionDemoSupported
OCRDemoDemo
Vision LanguageSupportedSupported
Visual Question AnsweringDemoDemo
Model Features
Foundation VisionSupportedSupported
LLMs with Vision CapabilitiesSupportedSupported
Multimodal VisionSupportedSupported
Vision Evalsground-truth scores across 5 vision tasks, pooled at low effort
Overall
61.4%
Not evaluated
Avg cost / sample$0.0013–
Avg speed / sample10.60s–
By task
Object Detection
41.0%
$0.0017
–
Counting
66.2%
$0.0007
–
Identification
81.3%
$0.0005
–
OCR (low)
60.7%
$0.0013
–
by category
Single value
54.4%
Transcription
82.9%
Structured JSON
80.2%
Text localization
14.8%
OCR (high)
60.1%
$0.0033
–
by category
Single value
54.4%
Transcription
78.4%
Structured JSON
80.0%
Text localization
13.7%
Reasoning (low)
57.6%
$0.0009
–
Reasoning (high)
62.9%
$0.0026
–

Muse Glimmer 30B vs Qwen3.6 Plus: Overview

Muse Glimmer 30B

Muse Glimmer 30B is a dense vision language model from Meta built for long-horizon agentic work on local hardware. The architecture pairs a 52-layer causal text decoder with a roughly 1.8B parameter ViT-G/14 perception encoder for about 29.6 billion parameters in total, and it accepts interleaved text and image input so an agent can interpret screenshots, charts, and documents alongside conversation. The decoder uses grouped-query attention with 32 query heads and 2 key-value heads, a repeating pattern of three sliding-window local attention layers followed by one global layer, SwiGLU feed-forward blocks, and rotary position embeddings applied on the local layers, supporting a trained context of 131,072 tokens.

Meta describes the model as distilled from the larger Muse Spark and trained and evaluated around agentic behavior: end-to-end task completion, schema-accurate tool calling, multi-step reasoning across extended workflows, and recovery when a tool call returns an unexpected result. Reasoning effort is selectable across low, medium, high, and xhigh settings, and the model emits channel-scoped reasoning traces together with XML style tool calls rather than JSON, which requires parsers specific to this family. A companion block-diffusion drafter head predicts blocks of 16 tokens per forward pass for speculative decoding, with the main model verifying the proposals in parallel.

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.