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Gemma 3 12B vs Muse Spark 1.3

Compare Gemma 3 12B and Muse Spark 1.3 side-by-side. See how these vision models stack up in Image Captioning, OCR, and Open Prompt.

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GoogleGemma 3 12B
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MetaMuse Spark 1.3
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Models in this comparison

Gemma 3 12B vs Muse Spark 1.3 Comparison Table

Evals updated September 3, 2026Pricing updated September 3, 2026

PropertyGemma 3 12BMuse Spark 1.3
OrganizationGoogleMeta
Categoryopenclosed
Modalitymultimodalmultimodal
Release DateMar 2025Sep 2026
Context Window128K1.0M
Parameters12B
LicenseCustomProprietary
Pricing per 1M tokens
Input $/1M$0.050$1.25
Output $/1M$0.150$4.25
Vision Tasks
CaptioningDemoDemo
Chart Question Answering
ClassificationDemo
Document Question Answering
Image Tagging
Multi-Label Classification
OCRDemoDemo
Vision Language
Visual Question AnsweringDemoDemo
Object DetectionDemo
Model Features
Foundation Vision
LLMs with Vision Capabilities
Multimodal Vision
Vision Evalsground-truth scores across 6 vision tasks, pooled at low effort
OverallNot evaluated
79.8%
Avg cost / sample$0.0075
Avg speed / sample23.14s
By task
Object Detection (low)
58.6%
±0.7, Mean of 3 runs, range 58.0 to 59.4
$0.011
Object Detection (high)
56.6%
±2.4, Mean of 3 runs, range 54.5 to 59.3
$0.017
Counting (low)
74.3%
±2.0, Mean of 3 runs, range 73.0 to 77.0
$0.0049
Counting (high)
75.7%
±3.4, Mean of 3 runs, range 73.0 to 79.7
$0.0094
Identification (low)
92.7%
±1.6, Mean of 3 runs, range 90.6 to 93.8
$0.0036
Identification (high)
86.5%
±1.6, Mean of 3 runs, range 84.4 to 87.5
$0.0063
OCR (low)
91.3%
±0.5, Mean of 3 runs, range 90.7 to 91.6
$0.0083
OCR (high)
86.9%
±4.1, Mean of 3 runs, range 82.2 to 90.4
$0.015
Data Extraction (low)
88.7%
±1.5, Mean of 3 runs, range 86.6 to 89.7
$0.0031
Data Extraction (high)
87.6%
±0.0, Mean of 3 runs, range 87.6 to 87.6
$0.0044
Reasoning (low)
73.3%
±1.0, Mean of 3 runs, range 72.2 to 74.2
$0.0064
Reasoning (high)
73.1%
±1.0, Mean of 3 runs, range 72.2 to 74.2
$0.012

Gemma 3 12B vs Muse Spark 1.3: Overview

Gemma 3 12B

Gemma 3 12B, announced by Google DeepMind on March 12, 2025, is part of the open-weight Gemma 3 family, designed to provide a balance between capability and accessibility. With around 12 billion parameters, it supports multimodal input (text + images) and outputs text, making it useful for reasoning, summarization, Q&A, and visual understanding tasks. The model supports an input context of 128,000 tokens and typically generates up to ~8,000 tokens in output.

The 12B variant is instruction-tuned (“Gemma-3-12B-IT”) and optimized for multilingual use across more than 140 languages. It can run on a single GPU or TPU, offering a lighter compute footprint than very large proprietary models, while still achieving strong performance in reasoning benchmarks. Quantized and lower-precision variants are available to improve efficiency. Limitations include smaller output lengths relative to input capacity, scaling hardware needs at larger sizes, and performance below massive proprietary models on the most complex multimodal or reasoning-heavy tasks.

Muse Spark 1.3

Muse Spark 1.3 is a proprietary multimodal reasoning model from Meta Superintelligence Labs and the fourth Muse Spark release in five months, arriving on September 2, 2026. It takes text, images, video, and document files as input and returns text, and it operates over a context window of 1,048,576 tokens. Meta trains the model for long-horizon agentic work, so it carries accumulated context and prior tool results forward across many turns, reconciles messy or conflicting inputs, and asks for clarification when a task is underspecified. Visual inputs such as screenshots and video clips feed a reasoning loop that runs against a real execution environment rather than a scripted sequence of steps.

The model exposes graded reasoning effort settings. An xhigh configuration is generally available at launch, while a max reasoning configuration aimed at harder reasoning and agentic problems arrives after further safety testing. Artificial Analysis measures Muse Spark 1.3 (max) at 62 on its Intelligence Index and the xhigh configuration at 61, with agentic tool-use evaluations driving most of the gain over Muse Spark 1.2; max reaches 52% on Tau3-Bench Banking by spending more turns and reasoning tokens than xhigh. Prior Muse Spark versions emit bounding box coordinates, transcriptions, and structured field extractions from images on Roboflow Vision Evals.

Frequently Asked Questions

Gemma 3 12B has not yet been evaluated on Roboflow's current Vision Evals, so this comparison shows specs, licensing, and pricing rather than benchmark scores.

Gemma 3 12B is released under Custom, while Muse Spark 1.3 uses Proprietary. Licensing often matters more than raw accuracy for commercial deployments, so check the terms against how you plan to ship.

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