Claude Opus 5.5 vs Muse Wonder: 2026 comparison

Claude Opus 5.5 and Muse Wonder in brief

Claude Opus 5.5 and Muse Wonder both address work involving long inputs, reasoning and tool calls. Their published token prices match, but their supported inputs and output limits create distinct use cases. Claude accepts text, images and files. Muse also accepts audio and video, and lists a substantially higher maximum output. Claude has the higher Epoch capability index and provides individual benchmark results. Muse's record contains no benchmark breakdown, leaving less evidence for comparing performance on specific tests before you evaluate either model yourself.

Claude Opus 5.5 : Claude Opus 5.5 (Anthropic): $4 / $20 per million tokens, 1M context, benchmarks, verdict and alternatives. Checked October 25, 2026.

Muse Wonder : Muse Wonder (Meta): $4 / $20 per million tokens, 1M context, benchmarks, verdict and alternatives. Checked October 25, 2026.

Both meet the same need, which makes the comparison useful. We compare them on 11 verifiable criteria, using the same data as their profiles, collected from official sites, OpenRouter and Epoch AI.

Comparison table

Criterion by criterion

For each criterion: why it matters, each one's value and who has the edge. A criterion without data on both sides is not decided.

Capabilities (Epoch AI index)

Epoch AI's capabilities index rolls many benchmarks into one number: the higher, the better the model does on hard tasks. Claude Opus 5.5 : 168.8. Muse Wonder : 161.9. Edge: Claude Opus 5.5.

Shared benchmarks

On the benchmarks both models took, we count each one's wins. Claude Opus 5.5 : not disclosed. Muse Wonder : not disclosed. Cannot be decided: data missing on one side.

Input price

The price of tokens sent to the model weighs heavily as soon as you send long documents or chat history. Claude Opus 5.5 : $4 / M tokens. Muse Wonder : $4 / M tokens. A tie on this point.

Output price

Generated tokens usually cost several times more; they dominate the bill for writing and code. Claude Opus 5.5 : $20 / M tokens. Muse Wonder : $20 / M tokens. A tie on this point.

Cost of a typical task

For a request of 2,000 input and 500 output tokens, repeated 30,000 times a month (1,000 a day). Claude Opus 5.5 : $540 per month. Muse Wonder : $540 per month. A tie on this point.

Context window

The context window sets how much text the model reads at once: useful for long documents and agents. Claude Opus 5.5 : 1M tokens. Muse Wonder : 1M tokens. Edge: Muse Wonder.

Max output

The maximum answer length matters to generate long code files or reports. Claude Opus 5.5 : 128K tokens. Muse Wonder : 943.7K tokens. Edge: Muse Wonder.

Accepted inputs

Text, images, files, audio: the more formats accepted, the more cases covered without extra tools. Claude Opus 5.5 : 3. Muse Wonder : 5. Edge: Muse Wonder.

Tool calling

Essential for an agent: the model can call functions, APIs or MCP servers. Claude Opus 5.5 : yes. Muse Wonder : yes. A tie on this point.

Open weights

Downloadable weights let you run the model yourself, without sending data to a provider. Claude Opus 5.5 : no. Muse Wonder : no. A tie on this point.

Release date

A newer model often has fresher data and better training techniques. Claude Opus 5.5 : September 22, 2026. Muse Wonder : October 12, 2026. Edge: Muse Wonder.

In charts

Our analysis

The clearest distinction concerns the material you can submit and the evaluation evidence available. Anthropic released Claude Opus 5.5 on September 22, 2026, with text, image and file inputs. Meta released Muse Wonder on October 12, 2026, adding audio and video to those input types. This makes Muse relevant when your source material spans more media formats, without establishing that it performs better overall. Both models support reasoning and tool calling. Neither record describes reliability in a particular profession or workflow, so their stated capabilities should help define your shortlist rather than settle how well they will handle your actual assignments.

Claude records an Epoch capability index of 168.83, compared with 161.85 for Muse. Its published results are 90.6% on GPQA, 91.2% on FrontierMath, 100% on AIME, 72.2% on SimpleQA, 98.5% on ARC1 and 93.3% on ARC2. Muse has no individual benchmark results in the supplied record, preventing a test by test comparison. Context limits are 1,000,000 tokens for Claude and 1,048,576 for Muse. Maximum outputs are 128,000 and 943,718 tokens respectively. Each charges USD 4 per million input tokens and USD 20 per million output tokens. Matching unit prices do not make different lengths of generated output cost the same.

Both publishers are based in the United States, and neither model has open weights. No license is specified in either record. The supplied information therefore offers no basis for inspecting model parameters or establishing the detailed rights attached to their use. Data retention, reuse policies and processing locations are also unspecified. A publisher's country alone does not establish where your material will be processed or what happens to it afterward. If you plan to submit confidential files, those missing terms need clarification independently of the capability index. Neither the larger context window nor the benchmark results resolve questions about how your data is handled.

For everyday use, start with your source formats and the length of the responses you need. Both models list support for text, images and files, making either relevant to those inputs. Only Muse lists direct audio and video input. Its higher output ceiling may matter when a task calls for an unusually long response, but the limit does not establish coherence across that response. Claude supplies more benchmark evidence to guide an initial evaluation. Tool calling is available on both, although the records do not identify supported integrations. No latency measurements are supplied, so you cannot infer which will respond faster in your workflow.

Depending on your situation

The right choice depends on use. For a few common situations, here are the criteria that matter and who wins (Claude Opus 5.5 value / Muse Wonder value).

High request volume

Neither stands out on the criteria for this situation (cost of a typical task ($540 per month / $540 per month), input price ($4 / M tokens / $4 / M tokens), and output price ($20 / M tokens / $20 / M tokens)): decide with a trial.

Hard tasks (reasoning, code)

Neither stands out on the criteria for this situation (capabilities (epoch ai index) (168.8 / 161.9), shared benchmarks (not disclosed / not disclosed), and max output (128K tokens / 943.7K tokens)): decide with a trial.

Agents and long documents

Here, Muse Wonder has the edge: it wins 2 of the 3 criteria that matter in this situation, namely tool calling (yes / yes), context window (1M tokens / 1M tokens), and accepted inputs (3 / 5).

Maximum privacy

Neither stands out on the criteria for this situation (open weights (no / no)): decide with a trial.

Which one to choose?

Choose Claude Opus 5.5 if…

• you value capabilities (epoch ai index) (168.8)

Choose Claude Opus 5.5 when your work mainly involves text, images and files, and you want individual benchmark results to inform your evaluation. Its Epoch index is higher in the supplied data. Check that the 128,000 token output ceiling meets your needs, however. Its published input and output rates provide no unit price advantage over Muse.

Choose Muse Wonder if…

• you value context window (1M tokens)
• you value max output (943.7K tokens)
• you value accepted inputs (5)
• you value release date (October 12, 2026)

Muse Wonder is the more direct fit when your inputs include audio or video, or your task requires an output ceiling above Claude's. It also provides a slightly larger context window at the same published token rates. The tradeoff is less detailed evaluation evidence: its record supplies no individual benchmark scores, so you will need your own task results to assess suitability.

Strengths and limits of each

Claude Opus 5.5

• + Among the top 20% of models according to Epoch AI (ECI 168.8).
• + Very large context (1M tokens): long documents or a whole codebase fit in one request.
• + Agent-ready: tool calling and structured JSON output.
• − Expensive: costlier than 93 % of paid models.

Muse Wonder

• + Among the top 20% of models according to Epoch AI (ECI 161.9).
• + Very large context (1M tokens): long documents or a whole codebase fit in one request.
• + Agent-ready: tool calling and structured JSON output.
• − Expensive: costlier than 93 % of paid models.

The best test is still yours: take three real tasks from your day and give them to both for a week. The price calculator works out the gap on your own volume.

What about the others?

If neither suits you, look at GPT-6 Astra, GPT-6.1 Sol, Claude Fable 5.1, Gemini 4 Argon, Claude Sonnet 5.5, and Claude Opus 5.

Related comparisons:

• Claude Opus 5.5 vs GPT-6.1 Sol
• Claude Opus 5.5 vs Gemini 4 Argon
• Claude Opus 5.5 vs GPT-6 Astra

Conclusion

With matching token rates, the practical decision rests on input formats, output length and available evaluation evidence. Claude offers a higher Epoch index and a detailed benchmark record. Muse supports more input types and a much higher output limit. Match those differences to your actual work and test the resulting shortlist on representative material. The supplied information does not establish an advantage for either model in privacy or response speed.