MetaReleased Nov 2026Proprietary
Muse Ember scores 76.6% overall on Roboflow's Vision Evals (November 10, 2026 snapshot), #16 of 67 models (Gemini 4 Argon leads at 87.5%).
Its best task is counting (79.7%, #9 of 67) and its weakest is OCR (69.5%, #17 of 51). It is a proprietary model from Meta, so commercial use follows Meta's terms.
Muse EmberField median
Ranks out of 67 models (51 for OCR)
Not available to run yet
Muse Ember is on the Vision Evals leaderboard. Running it in the Playground is not available yet. View evals
Vision Evals is Roboflow's ground-truth benchmark: every model runs the same real-world samples across five vision tasks, and answers are scored against ground truth.
Evals updated November 10, 2026Pricing updated November 10, 2026
Best showing
Weak spot
Above the field median, but its lowest rank.
Muse EmberField median
Ranks out of 67 models (51 for OCR)
| Task | Score | Field (0 to 100) | Rank | Cost / sample | Speed |
|---|---|---|---|---|---|
| Object Detection (low) | 63.8% ±0.5, Mean of 3 runs, range 63.3 to 64.3 | #19 of 67 | $0.0011 | 6.15s | |
| Object Detection (high) | 64.0% ±0.5, Mean of 3 runs, range 63.5 to 64.5 | #21 of 35 | $0.0017 | 8.11s | |
| Counting (low) | 79.7% ±1.4, Mean of 3 runs, range 78.4 to 81.1 | #9 of 67 | $0.0006 | 4.70s | |
| Counting (high) | 79.3% ±0.7, Mean of 3 runs, range 78.4 to 79.7 | #11 of 35 | $0.0011 | 6.58s | |
| Identification (low) | 91.7% ±1.6, Mean of 3 runs, range 90.6 to 93.8 | #17 of 67 | $0.0004 | 3.67s | |
| Identification (high) | 90.6% ±3.1, Mean of 3 runs, range 87.5 to 93.8 | #13 of 35 | $0.0007 | 4.93s | |
| OCR (low) | 69.5% | #17 of 51 | $0.0010 | 6.66s | |
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| OCR (high) | 70.5% | #18 of 51 | $0.0017 | 9.69s | |
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| Reasoning (low) | 78.2% ±1.3, Mean of 3 runs, range 76.8 to 79.5 | #11 of 67 | $0.0006 | 4.89s | |
| Reasoning (high) | 81.9% ±1.7, Mean of 3 runs, range 80.1 to 83.4 | #10 of 54 | $0.0013 | 7.38s | |
Overall benchmark score against estimated cost per sample, on a log scale. Upper-left is the sweet spot: high quality at low cost.
66 of 67 models plotted (the rest have no measured figure for this axis) · scores and efficiency pooled across all five tasks at low effort · Muse Ember highlighted
Muse Ember scores are the mean of 3 runs per task at both low and high effort; OCR is a single preliminary run · Methodology
View all Vision Evals →Muse Ember is a proprietary multimodal reasoning model from Meta, released on November 9, 2026. It accepts text, images, video, audio, and PDF documents and returns text. The Meta Model API serves it as muse-ember-1.0, with a 1,048,576-token context window and up to 524,288 output tokens. Reasoning effort is adjustable from minimal to max.
Muse Ember costs $0.100 per 1M input tokens and $0.500 per 1M output tokens.
Pricing updated Nov 10, 2026
Muse Ember is proprietary: the weights are not distributed, and the Muse Ember license is the vendor's commercial terms of service that you accept when you call the API.
Vendor terms govern data retention, whether your inputs can be trained on, rate limits, and regional availability, and they can change with notice. Review them if you handle regulated or customer data.
Proprietary terms are set by the vendor rather than negotiated per project, and no open-source obligation attaches to your code. If you would rather deploy an open model instead of Muse Ember, Roboflow's licensing page lists the models whose commercial license is included when you deploy on Roboflow.
Do not hesitate to reach out with questions for your commercial project. Our team will help you start solving business problems on the first call. See Roboflow commercial licensing for the models included in each plan.
Talk to salesLicense information is provided as a guide and is not legal advice.
Yes. Muse Ember accepts image input and handles OCR, object counting, identification, visual reasoning, and object detection. On Roboflow's Vision Evals its strongest task is Counting at 79.7% (#9 of 67 at low effort).
Yes, and it is one of the model's strongest vision skills: it scores 69.5% (#17 of 51 at low effort) on Vision Evals OCR, which covers single readings, full transcriptions, structured JSON, and locating text with boxes. Within that, full transcriptions score 95.5%, and returning the fields of a label or form as JSON scores 85.1%.
Yes. On Vision Evals, Muse Ember scores 63.8% mAP@50 on object detection (#19 of 67 at low effort) and 79.7% judge-graded accuracy on object counting.
On our benchmark's task mix, Muse Ember averages $0.0009 per sample at $0.10 per 1M input and $0.50 per 1M output tokens (#15 of 67 on cost), with an average speed of 6.1s per sample across the benchmark. Actual cost depends on your images and prompts.
On the overall Vision Evals ranking, Muse Ember sits #16 of 67 at 76.6%, just behind Gemini 3.1 Pro (76.8%) and just ahead of Claude Fable 5.1 (74.7%). See the full side-by-side: Muse Ember vs Gemini 3.1 Pro.