Gemini 3.1 Pro vs Muse Spark 1.3
Compare Gemini 3.1 Pro and Muse Spark 1.3 side-by-side. See how these vision models stack up in Image Captioning, Open Prompt, Classification, OCR, and Object Detection.
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Models in this comparison
Gemini 3.1 Pro vs Muse Spark 1.3 on Vision Evals
Gemini 3.1 Pro scores higher on 4 of the six Vision Evals tasks.
The widest gap is Object Detection, where Gemini 3.1 Pro leads 67.4% to 58.6%.
Overall, Gemini 3.1 Pro averages 83.3% (#5 of 52) against 79.8% (#10 of 52) for Muse Spark 1.3.
Muse Spark 1.3 is cheaper ($0.0075 vs $0.0093 per sample), while Gemini 3.1 Pro is faster (7.8s vs 23.1s per sample).
Gemini 3.1 Pro vs Muse Spark 1.3 Comparison Table
Evals updated September 3, 2026Pricing updated September 3, 2026
| Property | Gemini 3.1 Pro | Muse Spark 1.3 |
|---|---|---|
| Organization | Meta | |
| Category | closed | closed |
| Modality | multimodal | multimodal |
| Release Date | Feb 2026 | Sep 2026 |
| Context Window | 1.0M | 1.0M |
| Parameters | ||
| License | Proprietary | Proprietary |
| Pricing per 1M tokens | ||
| Input $/1M | $2.00 | $1.25 |
| Output $/1M | $12.00 | $4.25 |
| Vision Tasks | ||
| Captioning | Demo | Demo |
| Chart Question Answering | ||
| Classification | Demo | Demo |
| Document Question Answering | ||
| Image Tagging | ||
| Multi-Label Classification | ||
| Object Detection | Demo | Demo |
| OCR | Demo | Demo |
| Vision Language | ||
| Visual Question Answering | Demo | Demo |
| Model Features | ||
| Foundation Vision | ||
| LLMs with Vision Capabilities | ||
| Multimodal Vision | ||
Vision Evalsground-truth scores across 6 vision tasks, pooled at low effort | ||
| Overall | 83.3% | 79.8% |
| Avg cost / sample | $0.0093 | $0.0075 |
| Avg speed / sample | 7.81s | 23.14s |
| By task | ||
| Object Detection (low) | 67.4% | 58.6% ±0.7, Mean of 3 runs, range 58.0 to 59.4 |
| Object Detection (high) | – | 56.6% ±2.4, Mean of 3 runs, range 54.5 to 59.3 |
| Counting (low) | 71.6% | 74.3% ±2.0, Mean of 3 runs, range 73.0 to 77.0 |
| Counting (high) | – | 75.7% ±3.4, Mean of 3 runs, range 73.0 to 79.7 |
| Identification (low) | 100.0% | 92.7% ±1.6, Mean of 3 runs, range 90.6 to 93.8 |
| Identification (high) | – | 86.5% ±1.6, Mean of 3 runs, range 84.4 to 87.5 |
| OCR (low) | 92.6% | 91.3% ±0.5, Mean of 3 runs, range 90.7 to 91.6 |
| OCR (high) | – | 86.9% ±4.1, Mean of 3 runs, range 82.2 to 90.4 |
| Data Extraction (low) | 95.9% | 88.7% ±1.5, Mean of 3 runs, range 86.6 to 89.7 |
| Data Extraction (high) | – | 87.6% ±0.0, Mean of 3 runs, range 87.6 to 87.6 |
| Reasoning (low) | 72.2% | 73.3% ±1.0, Mean of 3 runs, range 72.2 to 74.2 |
| Reasoning (high) | 74.8% | 73.1% ±1.0, Mean of 3 runs, range 72.2 to 74.2 |
Gemini 3.1 Pro vs Muse Spark 1.3: Overview
Gemini 3.1 Pro is a proprietary multimodal model from Google’s Gemini 3 series, released in early 2026 and designed for advanced reasoning across large multimodal datasets. It accepts text, images, audio, video, and documents, supporting up to a 1-million-token input context with up to 64k output tokens. Compared with Gemini 3 Pro, it improves long-context synthesis and multi-step reasoning, enabling more reliable analysis of large documents, datasets, and software codebases.
The model also advances visual understanding and grounding, allowing it to interpret UI screenshots, diagrams, and real-world scenes while referencing specific regions within images or video. These capabilities make Gemini 3.1 Pro well suited for multimodal workflows involving document processing, interface analysis, robotics research, and complex visual reasoning.
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
On Roboflow's Vision Evals, Gemini 3.1 Pro performed better. It scores higher on 4 of the six vision tasks and averages 83.3% (#5 of 52) against 79.8% (#10 of 52) for Muse Spark 1.3. These scores measure vision capabilities only; either model may perform differently on work outside this benchmark's tasks.
Yes. On the Vision Evals Object Detection benchmark at low effort, Gemini 3.1 Pro leads with 67.4% against 58.6%. This is the widest gap between the two models across the benchmark's tasks.
Muse Spark 1.3 is cheaper to run. Across Roboflow's Vision Evals task mix it averaged $0.0075 per sample against $0.0093. Gemini 3.1 Pro is priced at $2.00 per 1M input tokens and $12.00 per 1M output; Muse Spark 1.3 is priced at $1.25 per 1M input tokens and $4.25 per 1M output. Actual costs depend on your image sizes, prompts, and output length.
Gemini 3.1 Pro is faster. Across Roboflow's Vision Evals it averaged 7.8s per inference against 23.1s. Latency varies with image size, prompt length, and provider load, so treat these as relative rather than guaranteed figures.
Yes. The comparison demo on this page runs both models on the same image side by side for image captioning and open prompts in the free Roboflow Playground. You can try it instantly, and a free account unlocks unlimited runs.