Gemini 3 Flash vs Muse Spark Open
Muse Spark Open and Gemini 3 Flash score 69.4% vs 65.7% averaged across five Vision Evals tasks (#25 and #29 of 65 models), so Muse Spark Open leads overall.
- Muse Spark Open wins 3 of the 5 tasks, with its widest lead on object detection (57.8% vs 38.6%).
- Gemini 3 Flash is about half the cost: $0.0024 vs $0.0059 overall average cost per sample.
- Gemini 3 Flash is faster: 5.8s vs 7.4s per sample.
Roboflow Vision Evals. Full breakdown below.
Compare Gemini 3 Flash 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 3 Flash vs Muse Spark Open on Vision Evals
Roboflow Vision Evals. Full breakdown below.
Gemini 3 Flash vs Muse Spark Open Comparison Table
Evals updated October 26, 2026Pricing updated October 27, 2026
| Property | Gemini 3 Flash | Muse Spark Open |
|---|---|---|
| Organization | Meta | |
| Category | closed | open |
| Modality | multimodal | multimodal |
| Release Date | Dec 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 | $0.500 | $1.25 |
| Output $/1M | $3.00 | $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 | 65.7% | 69.4% |
| Avg cost / sample | $0.0024 | $0.0059 |
| Avg speed / sample | 5.83s | 7.37s |
| By task | ||
| Object Detection (low) | 38.6% | 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) | 67.6% | 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) | 63.9% | 67.6% |
| by category |
|
|
| OCR (high) | 73.1% | 68.6% |
| by category |
|
|
| Reasoning (low) | 64.9% | 63.8% ±1.0, Mean of 3 runs, range 62.9 to 64.9 |
| Reasoning (high) | 74.2% | 65.1% ±3.0, Mean of 3 runs, range 62.3 to 68.2 |
Gemini 3 Flash vs Muse Spark Open: Overview
Gemini 3 Flash is a proprietary multimodal large language model developed by Google through Google DeepMind, designed to deliver fast, cost-efficient reasoning across real-time products and developer workflows. Released in December 2025, it is the Flash-tier variant of the Gemini 3 family, balancing low latency with reasoning quality approaching Pro models.
The model supports text, images, audio, and video, with an exceptionally large context window of roughly one million input tokens and outputs up to ~65k tokens. It emphasizes rapid responses for coding, summarization, analysis, and agentic tasks, and exposes configurable “thinking levels” via API to trade speed for deeper reasoning. Today, Gemini 3 Flash positions itself as a high-throughput, production-ready model, serving as the default in the Gemini app and Google Search’s AI Mode, optimized for scalable, interactive AI applications.
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 3 of the five vision tasks and averages 69.4% (#25 of 65) against 65.7% (#29 of 65) for Gemini 3 Flash. 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 38.6%. This is the widest gap between the two models across the benchmark's tasks.
Gemini 3 Flash is cheaper to run. Across Roboflow's Vision Evals task mix it averaged $0.0024 per sample against $0.0059. Gemini 3 Flash is priced at $0.50 per 1M input tokens and $3.00 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 3 Flash is faster. Across Roboflow's Vision Evals it averaged 5.8s per inference against 7.4s. Latency varies with image size, prompt length, and provider load, so treat these as relative rather than guaranteed figures.