Claude Fable 5.2 vs Muse Ember
Claude Fable 5.2 and Muse Ember score 86.5% vs 76.6% averaged across five Vision Evals tasks (#2 and #16 of 67 models), so Claude Fable 5.2 leads overall.
- Claude Fable 5.2 wins all 5 tasks, with its widest lead on object detection (81.6% vs 63.8%).
- Muse Ember is under a tenth of the cost: $0.0009 vs $0.031 overall average cost per sample.
- Muse Ember is faster: 6.1s vs 9.3s per sample.
Roboflow Vision Evals. Full breakdown below.
Compare Claude Fable 5.2 vs Muse Ember 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.
Claude Fable 5.2 vs Muse Ember on Vision Evals
Roboflow Vision Evals. Full breakdown below.
Claude Fable 5.2 vs Muse Ember Comparison Table
Evals updated November 10, 2026Pricing updated November 10, 2026
| Property | Claude Fable 5.2 | Muse Ember |
|---|---|---|
| Organization | Anthropic | Meta |
| Category | closed | closed |
| Modality | multimodal | multimodal |
| Release Date | Nov 2026 | Nov 2026 |
| Context Window | 1.0M | 1.0M |
| Parameters | Unknown | Unknown |
| License | Proprietary | Proprietary |
| Commercial use | commercial use per vendor terms | commercial use per vendor terms |
| Pricing per 1M tokens | ||
| Input $/1M | $8.00 | $0.100 |
| Output $/1M | $40.00 | $0.500 |
| Vision Tasks | ||
| Model Features | ||
Both support 3 more features | ||
Vision Evalsground-truth scores across 5 vision tasks, pooled at low effort | ||
| Overall | 86.5% | 76.6% |
| Avg cost / sample | $0.031 | $0.0009 |
| Avg speed / sample | 9.33s | 6.08s |
| By task | ||
| Object Detection (low) | 81.6% ±0.3, Mean of 3 runs, range 81.2 to 81.9 | 63.8% ±0.5, Mean of 3 runs, range 63.3 to 64.3 |
| Object Detection (high) | 83.3% ±0.5, Mean of 3 runs, range 82.8 to 83.7 | 64.0% ±0.5, Mean of 3 runs, range 63.5 to 64.5 |
| Counting (low) | 86.5% ±0.0, Mean of 3 runs, range 86.5 to 86.5 | 79.7% ±1.4, Mean of 3 runs, range 78.4 to 81.1 |
| Counting (high) | 92.8% ±1.4, Mean of 3 runs, range 91.9 to 94.6 | 79.3% ±0.7, Mean of 3 runs, range 78.4 to 79.7 |
| Identification (low) | 96.9% ±0.0, Mean of 3 runs, range 96.9 to 96.9 | 91.7% ±1.6, Mean of 3 runs, range 90.6 to 93.8 |
| Identification (high) | 94.8% ±1.6, Mean of 3 runs, range 93.8 to 96.9 | 90.6% ±3.1, Mean of 3 runs, range 87.5 to 93.8 |
| OCR (low) | 79.5% | 69.5% |
| by category |
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| OCR (high) | 84.8% | 70.5% |
| by category |
|
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| Reasoning (low) | 88.1% ±1.3, Mean of 3 runs, range 86.8 to 89.4 | 78.2% ±1.3, Mean of 3 runs, range 76.8 to 79.5 |
| Reasoning (high) | 92.0% ±1.0, Mean of 3 runs, range 91.4 to 93.4 | 81.9% ±1.7, Mean of 3 runs, range 80.1 to 83.4 |
Claude Fable 5.2 vs Muse Ember: Overview
Claude Fable 5.2 is a proprietary multimodal model from Anthropic, released on November 9, 2026. It accepts text and images and produces text, with a one million token context window and up to 128,000 output tokens. Adaptive thinking is always enabled, with an effort setting that controls reasoning. Anthropic positions Fable for demanding reasoning and long-running technical work, including coding and analysis of visual inputs.
Fable 5.2 succeeds Fable 5.1. Anthropic reports improvements in coding, reasoning, and vision, with output generation up to 30% faster than its predecessor. Fable and Mythos 5.2 share an underlying model, with additional cybersecurity and biology safeguards applied to Fable. Model weights are not publicly released.
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.
Meta positions Ember for repeated tasks within larger agent workflows: tool calls, routing, coding subtasks, and processing collections of images and documents. It can caption or sort photos and extract fields from records while a larger Muse model handles planning. Meta recommends Spark or Wonder for harder single-shot coding and knowledge-heavy problems. Ember is available as a hosted model; its weights are not publicly released.
Frequently Asked Questions
On Roboflow's Vision Evals, Claude Fable 5.2 performed better. It scores higher on all five vision tasks and averages 86.5% (#2 of 67) against 76.6% (#16 of 67) for Muse Ember. These scores measure vision capabilities only; either model may perform differently on work outside this benchmark's tasks.
Yes. On the Vision Evals Object Detection benchmark at low effort, Claude Fable 5.2 leads with 81.6% against 63.8%. This is the widest gap between the two models across the benchmark's tasks.
Muse Ember is cheaper to run. Across Roboflow's Vision Evals task mix it averaged $0.0009 per sample against $0.031. Claude Fable 5.2 is priced at $8.00 per 1M input tokens and $40.00 per 1M output; Muse Ember is priced at $0.10 per 1M input tokens and $0.50 per 1M output. Actual costs depend on your image sizes, prompts, and output length.
Muse Ember is faster. Across Roboflow's Vision Evals it averaged 6.1s per inference against 9.3s. Latency varies with image size, prompt length, and provider load, so treat these as relative rather than guaranteed figures.