Muse Spark 1.1 vs Qwen3.7 Plus
Compare Muse Spark 1.1 and Qwen3.7 Plus side-by-side. See how these vision models stack up in OCR, Classification, Image Captioning, Object Detection, and Open Prompt.
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Models in this comparison
Muse Spark 1.1 vs Qwen3.7 Plus on Vision Evals
Muse Spark 1.1 scores higher on 5 of the six Vision Evals tasks.
The widest gap is Reasoning, where Muse Spark 1.1 leads 74.8% to 39.7%.
Overall, Muse Spark 1.1 averages 79.3% (#7 of 31) against 67.4% (#18 of 31) for Qwen3.7 Plus.
Qwen3.7 Plus is both cheaper ($0.0008 vs $0.0069 per sample) and faster (7.0s vs 11.4s per sample).
Muse Spark 1.1 vs Qwen3.7 Plus Comparison Table
Evals updated August 20, 2026Pricing updated August 24, 2026
| Property | Muse Spark 1.1 | Qwen3.7 Plus |
|---|---|---|
| Organization | Meta | Qwen |
| Category | closed | closed |
| Modality | multimodal | — |
| Release Date | Jul 2026 | — |
| Context Window | 1.0M | — |
| Parameters | ||
| License | Proprietary | |
| Pricing per 1M tokens | ||
| Input $/1M | $1.25 | $0.320 |
| Output $/1M | $4.25 | $1.28 |
| Vision Tasks | ||
| Captioning | Demo | Demo |
| Classification | Demo | Demo |
| Object Detection | Demo | Demo |
| OCR | Demo | Demo |
| Visual Question Answering | Demo | Demo |
| Chart Question Answering | ||
| Document Question Answering | ||
| Image Tagging | ||
| Multi-Label Classification | ||
| Vision Language | ||
| Model Features | ||
| Foundation Vision | ||
| LLMs with Vision Capabilities | ||
| Multimodal Vision | ||
Vision Evalsground-truth scores across 6 vision tasks, pooled at low effort | ||
| Overall | 79.3% | 67.4% |
| Avg cost / sample | $0.0069 | $0.0008 |
| Avg speed / sample | 11.40s | 7.01s |
| By task | ||
| Object Detection | 58.4% $0.010 | 60.1% $0.0013 |
| Counting | 75.7% $0.0043 | 50.0% $0.0004 |
| Identification | 87.5% $0.0032 | 84.4% $0.0003 |
| OCR | 92.5% $0.0063 | 86.5% $0.0009 |
| Data Extraction | 86.6% $0.0031 | 83.5% $0.0004 |
| Reasoning (low) | 74.8% $0.0065 | 39.7% $0.0003 |
| Reasoning (high) | 76.2% $0.013 | 68.2% $0.0043 |
Muse Spark 1.1 vs Qwen3.7 Plus: Overview
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 5 of the six vision tasks and averages 79.3% (#7 of 31) against 67.4% (#18 of 31) for Qwen3.7 Plus. These scores measure vision capabilities only; either model may perform differently on work outside this benchmark's tasks.
Yes. On the Vision Evals Reasoning benchmark at low effort, Muse Spark 1.1 leads with 74.8% against 39.7%. This is the widest gap between the two models across the benchmark's tasks.
Qwen3.7 Plus is cheaper to run. Across Roboflow's Vision Evals task mix it averaged $0.0008 per sample against $0.0069. Muse Spark 1.1 is priced at $1.25 per 1M input tokens and $4.25 per 1M output; Qwen3.7 Plus is priced at $0.32 per 1M input tokens and $1.28 per 1M output. Actual costs depend on your image sizes, prompts, and output length.
Qwen3.7 Plus is faster. Across Roboflow's Vision Evals it averaged 7.0s 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 OCR and image classification in the free Roboflow Playground. You can try it instantly, and a free account unlocks unlimited runs.