Gemini 3 Flash vs Muse Spark 1.1
Compare Gemini 3 Flash and Muse Spark 1.1 side-by-side. See how these vision models stack up in Object Detection, Classification, Open Prompt, OCR, and Image Captioning.
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Models in this comparison
Gemini 3 Flash vs Muse Spark 1.1 on Vision Evals
Muse Spark 1.1 scores higher on 4 of the six Vision Evals tasks.
The widest gap is Object Detection, where Muse Spark 1.1 leads 58.2% to 38.6%.
Overall, Gemini 3 Flash averages 74.9% (#10 of 25) against 79.2% (#6 of 25) for Muse Spark 1.1.
Gemini 3 Flash is both cheaper ($0.0021 vs $0.0069 per sample) and faster (4.1s vs 11.4s per sample).
Gemini 3 Flash vs Muse Spark 1.1 Comparison Table
Evals updated August 6, 2026Pricing updated August 11, 2026
| Property | Gemini 3 Flash | Muse Spark 1.1 |
|---|---|---|
| Organization | Meta | |
| Category | closed | closed |
| Modality | multimodal | multimodal |
| Release Date | Dec 2025 | Jul 2026 |
| Context Window | 1.0M | 1.0M |
| Parameters | ||
| License | Proprietary | Proprietary |
| Pricing per 1M tokens | ||
| Input $/1M | $0.500 | $1.25 |
| Output $/1M | $3.00 | $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 | 74.9% | 79.2% |
| Avg cost / sample | $0.0021 | $0.0069 |
| Avg speed / sample | 4.10s | 11.40s |
| By task | ||
| Object Detection | 38.6% $0.0031 | 58.2% $0.010 |
| Counting | 67.6% $0.0012 | 75.7% $0.0043 |
| Identification | 93.8% $0.0009 | 87.5% $0.0032 |
| OCR | 87.6% $0.0024 | 92.5% $0.0063 |
| Data Extraction | 96.9% $0.0008 | 86.6% $0.0031 |
| Reasoning (low) | 64.9% $0.0020 | 74.8% $0.0065 |
| Reasoning (high) | 74.2% $0.0040 | 76.2% $0.013 |
Gemini 3 Flash vs Muse Spark 1.1: 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 1.1 is a natively multimodal reasoning model from Meta Superintelligence Labs, released on July 9, 2026, as a significant upgrade to the original Muse Spark. The model accepts text, image, video, PDF, and audio as input and produces text output. It operates with a 1-million-token context window (1,048,576 tokens per the Meta Model API documentation) and is designed specifically for agentic tasks that require planning, tool use, computer use, and multi-agent orchestration. The model runs in a "Thinking" mode, where adjustable reasoning effort is applied before generating a response. It can function both as a main agent gathering context, forming plans, and delegating to parallel subagents and as a subagent that adheres to assigned tasks and escalates when needed. It is trained to decide autonomously when to write automation scripts versus interact directly with a user interface.
Muse Spark 1.1 supports a range of multimodal capabilities including visual perception, image and video captioning, visual-to-code generation, and document analysis. The model was evaluated under Meta's Advanced AI Scaling Framework across frontier risk categories including chemical and biological threats, cybersecurity, and loss-of-control scenarios. Parameter count, architecture details, and training data composition are not publicly disclosed. The model is proprietary and closed-weight, accessible to consumers through the Meta AI app and to developers via the Meta Model API, which launched in public preview alongside this release.
Frequently Asked Questions
On Roboflow's Vision Evals, Muse Spark 1.1 performed better. It scores higher on 4 of the six vision tasks and averages 79.2% (#6 of 25) against 74.9% (#10 of 25) 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, Muse Spark 1.1 leads with 58.2% 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 $0.0021 per sample against $0.0069. Gemini 3 Flash is priced at $0.50 per 1M input tokens and $3.00 per 1M output; Muse Spark 1.1 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 4.1s per inference against 11.4s. 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 object detection and image classification in the free Roboflow Playground. You can try it instantly, and a free account unlocks unlimited runs.