Claude Opus 4.6 vs Muse Ember
Muse Ember: 76.6% average across five Vision Evals tasks (#16 of 67 models). We have not run Claude Opus 4.6 through Roboflow's Vision Evals, so there is no head-to-head score.
Compare Claude Opus 4.6 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 Opus 4.6 vs Muse Ember Comparison Table
Evals updated November 10, 2026Pricing updated November 10, 2026
| Property | Claude Opus 4.6 | Muse Ember |
|---|---|---|
| Organization | Anthropic | Meta |
| Category | closed | closed |
| Modality | multimodal | multimodal |
| Release Date | Feb 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 | $5.00 | $0.100 |
| Output $/1M | $25.00 | $0.500 |
| 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 | Not evaluated | 76.6% |
| Avg cost / sample | – | $0.0009 |
| Avg speed / sample | – | 6.08s |
| By task | ||
| Object Detection (low) | – | 63.8% ±0.5, Mean of 3 runs, range 63.3 to 64.3 |
| Object Detection (high) | – | 64.0% ±0.5, Mean of 3 runs, range 63.5 to 64.5 |
| Counting (low) | – | 79.7% ±1.4, Mean of 3 runs, range 78.4 to 81.1 |
| Counting (high) | – | 79.3% ±0.7, Mean of 3 runs, range 78.4 to 79.7 |
| Identification (low) | – | 91.7% ±1.6, Mean of 3 runs, range 90.6 to 93.8 |
| Identification (high) | – | 90.6% ±3.1, Mean of 3 runs, range 87.5 to 93.8 |
| OCR (low) | – | 69.5% |
| by category |
| |
| OCR (high) | – | 70.5% |
| by category |
| |
| Reasoning (low) | – | 78.2% ±1.3, Mean of 3 runs, range 76.8 to 79.5 |
| Reasoning (high) | – | 81.9% ±1.7, Mean of 3 runs, range 80.1 to 83.4 |
Claude Opus 4.6 vs Muse Ember: Overview
Claude Opus 4.6 is the flagship large language model from Anthropic, released on 2026-02-05 for advanced reasoning, complex coding, and enterprise agent workflows. It supports text and image inputs via API, offers a 200K-token standard context window with a 1M-token beta option, and enables outputs up to 128K tokens, with adaptive reasoning and context compaction for sustained tasks.
As of 2026-02-17, Anthropic also released Claude Sonnet 4.6, extending the 1M-token context window to a broader tier. Opus remains positioned for maximum depth and benchmark performance, while Sonnet 4.6 brings long-context capability to more cost- and latency-sensitive production use cases.
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.