Gemini 2.5 Pro vs Muse Spark Open
Muse Spark Open and Gemini 2.5 Pro score 69.4% vs 57.6% averaged across five Vision Evals tasks (#25 and #42 of 65 models), so Muse Spark Open leads overall.
- Muse Spark Open wins 4 of the 5 tasks, with its widest lead on object detection (57.8% vs 33.7%).
- Gemini 2.5 Pro is cheaper: $0.0051 vs $0.0059 overall average cost per sample.
- Gemini 2.5 Pro is faster: 6.8s vs 7.4s per sample.
Roboflow Vision Evals. Full breakdown below.
Compare Gemini 2.5 Pro vs Muse Spark Open live
Run the same image across every model that supports a task and compare their outputs side-by-side.
These models don't share enough common tasks for a side-by-side demo. See the comparison table below for their capabilities.
Gemini 2.5 Pro vs Muse Spark Open on Vision Evals
Roboflow Vision Evals. Full breakdown below.
Gemini 2.5 Pro vs Muse Spark Open Comparison Table
Evals updated October 26, 2026Pricing updated October 27, 2026
| Property | Gemini 2.5 Pro | Muse Spark Open |
|---|---|---|
| Organization | Meta | |
| Category | closed | open |
| Modality | multimodal | multimodal |
| Release Date | Jun 2025 | Oct 2026 |
| Context Window | 1.0M | 1.0M |
| Parameters | Unknown | 816B total / 42B active |
| License | Proprietary | Custom |
| Commercial use | commercial use per vendor terms | See license terms |
| Pricing per 1M tokens | ||
| Input $/1M | $1.25 | $1.25 |
| Output $/1M | $10.00 | $4.25 |
| Vision Tasks | ||
| Captioning | Demo | Supported |
| Classification | Demo | Supported |
| Object Detection | Demo | Supported |
| OCR | Demo | Supported |
| Visual Question Answering | Demo | Supported |
| Model Features | ||
Both support 3 more features | ||
Vision Evalsground-truth scores across 5 vision tasks, pooled at low effort | ||
| Overall | 57.6% | 69.4% |
| Avg cost / sample | $0.0051 | $0.0059 |
| Avg speed / sample | 6.83s | 7.37s |
| By task | ||
| Object Detection (low) | 33.7% | 57.8% ±0.6, Mean of 3 runs, range 57.0 to 58.2 |
| Object Detection (high) | – | 60.9% ±0.8, Mean of 3 runs, range 60.3 to 61.9 |
| Counting (low) | 52.7% | 75.7% ±2.7, Mean of 3 runs, range 73.0 to 78.4 |
| Counting (high) | – | 75.2% ±4.1, Mean of 3 runs, range 71.6 to 79.7 |
| Identification (low) | 93.8% | 82.3% ±1.6, Mean of 3 runs, range 81.3 to 84.4 |
| Identification (high) | – | 80.2% ±3.1, Mean of 3 runs, range 78.1 to 84.4 |
| OCR (low) | 65.2% | 67.6% |
| by category |
|
|
| OCR (high) | 64.6% | 68.6% |
| by category |
|
|
| Reasoning (low) | 42.4% | 63.8% ±1.0, Mean of 3 runs, range 62.9 to 64.9 |
| Reasoning (high) | 62.3% | 65.1% ±3.0, Mean of 3 runs, range 62.3 to 68.2 |
Gemini 2.5 Pro vs Muse Spark Open: Overview
Gemini 2.5 Pro, released on June 17, 2025, is Google DeepMind’s most capable model in the Gemini 2.5 family, optimized for deep reasoning, coding, and complex multimodal tasks. It accepts text, images, audio, video, and PDFs as input and outputs text. The model supports 1 million input tokens with an output capacity of up to 65K tokens, enabling large-scale comprehension of datasets, codebases, and technical documents. Its training knowledge extends to January 2025.
It supports structured outputs, function calling, code execution, search grounding, and URL context, making it well-suited for enterprise, STEM, and developer workflows. However, it does not currently support image or audio generation in its stable release, and its higher computational cost and latency make it less efficient than Flash or Flash-Lite. It is available via the Gemini API, Google AI Studio, and Vertex AI.
Muse Spark Open is an open-weight multimodal model released by Meta on October 15, 2026. Its sparse mixture-of-experts architecture has 816 billion total parameters and activates 42 billion per token. It accepts text, images, audio and video, produces text, and supports a context window of 1,048,576 tokens. Meta provides BF16 and NVFP4 checkpoints for self-hosting, alongside access through hosted inference partners.
The model is designed for coding, tool use and multi-step reasoning over long tasks. Its visual inputs support workflows involving screenshots, documents and other image content. Vision Evals measures its text understanding, counting, identification, reasoning and object detection at Low and High effort. The published weights use the custom Muse Model License, with commercial use subject to its terms and the accompanying usage policy.
Frequently Asked Questions
On Roboflow's Vision Evals, Muse Spark Open performed better. It scores higher on 4 of the five vision tasks and averages 69.4% (#25 of 65) against 57.6% (#42 of 65) for Gemini 2.5 Pro. These scores measure vision capabilities only; either model may perform differently on work outside this benchmark's tasks.
No. On the Vision Evals Object Detection benchmark at low effort, Muse Spark Open leads with 57.8% against 33.7%. This is the widest gap between the two models across the benchmark's tasks.
Gemini 2.5 Pro is cheaper to run. Across Roboflow's Vision Evals task mix it averaged $0.0051 per sample against $0.0059. Gemini 2.5 Pro is priced at $1.25 per 1M input tokens and $10.00 per 1M output; Muse Spark Open 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 2.5 Pro is faster. Across Roboflow's Vision Evals it averaged 6.8s per inference against 7.4s. Latency varies with image size, prompt length, and provider load, so treat these as relative rather than guaranteed figures.