# Muse Wonder 1.0

[Canonical model page](https://headlessthrones.com/models/muse-wonder-1-0) · [Model library](https://headlessthrones.com/models)

Public catalog reference from Headless Thrones. Exact catalog ID: `muse-wonder-1-0`. Catalog source-check date: 2026-10-23.

This brief contains the public catalog answers and any catalog guide, not private drafts, historical editorial revisions or independently measured rankings. The canonical HTML page may also display separately published editorial.

Current catalog answers

## What to know about Muse Wonder 1.0

AI-compiled from linked model documentation. This is a catalog reference, not an independent performance review. Catalog checked October 23, 2026.

[Exact model](https://headlessthrones.com/models/muse-wonder-1-0#model-answer-identity) · [Access](https://headlessthrones.com/models/muse-wonder-1-0#model-answer-access) · [Pricing](https://headlessthrones.com/models/muse-wonder-1-0#model-answer-pricing) · [Token limits](https://headlessthrones.com/models/muse-wonder-1-0#model-answer-context) · [Inputs & outputs](https://headlessthrones.com/models/muse-wonder-1-0#model-answer-modalities) · [Model details](https://headlessthrones.com/models/muse-wonder-1-0#model-answer-research)

### Which Muse Wonder 1.0 does this page describe?

Muse Wonder 1.0 is a model record from **Meta** in the Muse Wonder family. [Source](https://dev.meta.ai/docs/models)

The recorded model identifier or checkpoint is `muse-wonder-1.0`. Use that exact identifier when checking documentation or a provider listing. [Source](https://dev.meta.ai/docs/models)

### How can you access Muse Wonder 1.0?

The catalog documents **API** access  for Muse Wonder 1.0. [Source](https://dev.meta.ai/docs/models)

As of the catalog check, this version was listed as a preview. [Source](https://dev.meta.ai/docs/models)

For API use, confirm the exact model identifier, your account and region, and the endpoint's current limits in the linked documentation. An API listing does not establish access through a consumer subscription.

### How much does Muse Wonder 1.0 cost?

The recorded token rates for Muse Wonder 1.0 are:

- **Input:** US$4 per 1 million input tokens. [Source](https://dev.meta.ai/docs/pricing-rate-limits)

- **Output:** US$20 per 1 million output tokens. [Source](https://dev.meta.ai/docs/pricing-rate-limits)

**Rate conditions:** Standard mode direct Meta API prices in USD per million uncached input/output tokens. Cached input is $0.20 per million. No long-context premium; web search is an additional $2.50 per 1,000 queries. Muse Code subscriptions are a separate product. [Source](https://dev.meta.ai/docs/pricing-rate-limits)

**Illustrative arithmetic:** 10,000 input tokens plus 2,000 output tokens would cost US$0.08 at those recorded rates. This assumes every token is billed at the displayed rate and excludes any cache, batch, tool, storage or tier adjustments; it is not a quote or measured usage.

Check the source's pricing conditions before budgeting. A token rate does not state the price of an app subscription or the full cost of running downloaded weights.

### What are Muse Wonder 1.0's context and output limits?

The documented **context window is 1,048,576 tokens**. [Source](https://dev.meta.ai/docs/models)

A separate maximum-output value is not established in this record. The context or input figure should not be used as an output allowance.

Context, input and output limits describe different constraints. Do not add the figures together to infer a larger window. Check the endpoint's accounting for conversation history, system instructions, tools, media and generated tokens; a documented maximum is not a guarantee of answer quality or a measured usable capacity.

### What can Muse Wonder 1.0 receive and generate?

Documented inputs: **text, image, video, audio, and pdf**. [Source](https://dev.meta.ai/docs/models)

Documented outputs: **text**. [Source](https://dev.meta.ai/docs/models)

Input support and output generation are separate capabilities. Reading an image does not establish image generation; a text output listing does not establish speech output. File sizes, formats and media limits depend on the documented implementation.

### What distinguishes Muse Wonder 1.0?

These details come from the linked publisher material for this model. Reported capabilities and training descriptions are publisher statements, not independent test results.

**Standard data policy**: Standard Mode content is not used to train Meta models. This is a mode-specific policy; it does not describe Contributor Mode. [Source](https://dev.meta.ai/docs/models)

**Preview and access**: Muse Wonder 1.0 is a preview available through the Model API in Standard Mode. The separate Muse Wonder Full offering is accessed through Muse Code, not by adding a Model API max-effort flag. [Source](https://dev.meta.ai/docs/models)

**Regional restriction**: The model guide says Muse Wonder is unavailable in South Korea. [Source](https://dev.meta.ai/docs/models)

**Team rate-limit scope**: The listed limit for muse-wonder-1.0 is 3,000 requests and 4,000,000 tokens per minute. Limits apply across all API keys in one team, separately for each model; adding another key does not create another allowance. [Source](https://dev.meta.ai/docs/pricing-rate-limits)

**Evidence still missing here:** knowledge and training-data cutoffs. Missing documentation is not evidence that a feature is unavailable.

Headless Thrones has not independently benchmarked this model for this reference. Evaluate it on representative work before choosing it; these facts do not rank its accuracy, reliability, speed or suitability against another model.