meta/muse-wonder
Release date: 2026-10-12
1,048,576 context · $4.00/M input tokens · $20.00/M output tokens
Muse Wonder is a frontier reasoning model from Meta, designed for complex personal and professional agentic tasks. It accepts text, images, video, audio, and PDF documents and returns text, with...
Pricing
Pay-per-use
No upfront costs, pay only for what you use
Try the model
API Usage
Use the following code examples to integrate with our API:
import OpenAI from 'openai';
if (!process.env.WAVESPEED_API_KEY) throw new Error('Set WAVESPEED_API_KEY');
const client = new OpenAI({
apiKey: process.env.WAVESPEED_API_KEY,
baseURL: 'https://llm.wavespeed.ai/v1',
timeout: 120_000,
maxRetries: 0,
});
try {
const response = await client.chat.completions.create({
model: 'meta/muse-wonder',
messages: [{ role: 'user', content: 'Hello!' }],
});
const body = response as typeof response & { error?: { message?: string } };
if (body.error) throw new Error(body.error.message || 'LLM generation failed');
console.log(response.choices[0]?.message?.content ?? '');
} catch (error) {
console.error('LLM request failed:', error);
process.exitCode = 1;
}import OpenAI from 'openai';
if (!process.env.WAVESPEED_API_KEY) throw new Error('Set WAVESPEED_API_KEY');
const client = new OpenAI({
apiKey: process.env.WAVESPEED_API_KEY,
baseURL: 'https://llm.wavespeed.ai/v1',
timeout: 120_000,
maxRetries: 0,
});
try {
const response = await client.chat.completions.create({
model: 'meta/muse-wonder',
messages: [{ role: 'user', content: 'Hello!' }],
});
const body = response as typeof response & { error?: { message?: string } };
if (body.error) throw new Error(body.error.message || 'LLM generation failed');
console.log(response.choices[0]?.message?.content ?? '');
} catch (error) {
console.error('LLM request failed:', error);
process.exitCode = 1;
}Model Introduction
Meta: Muse Wonder
Muse Wonder is a frontier reasoning model from Meta, designed for complex personal and professional agentic tasks. It accepts text, images, video, audio, and PDF documents and returns text, with...
This model is available through the WaveSpeed AI OpenAI-compatible API for chat completions and compatible application workflows.
Why It Looks Great
- text+image+file+audio+video->text architecture for Text, Image, Video, file, Audio to Text workloads
- 1048576 context window for long prompts, document analysis, and multi-turn workflows
- Vision input support for image understanding and multimodal tasks
- Function calling and tool-use support for agentic application workflows
- Structured output support for JSON responses and schema-constrained generation
- Reasoning controls available through supported parameters
Key Features
- Context Window: 1048576 tokens
- Max Input: 1048576 tokens
- Max Output: 943718 tokens
- Vision: Supported
- Function Calling: Supported
- Structured Outputs: Supported
- Image Generation: Not listed
- Audio Input: Supported
- Supported Parameters: include_reasoning, max_tokens, reasoning, reasoning_effort, repetition_penalty, response_format, seed, structured_outputs, temperature, tool_choice, tools, top_k, top_p
Specifications
| Specification | Value |
|---|---|
| Provider | meta |
| Model Type | Chat Completions model |
| Architecture | text+image+file+audio+video->text |
| Context Window | 1048576 tokens |
| Max Input | 1048576 tokens |
| Max Output | 943718 tokens |
| Input | Text, Image, Video, file, Audio |
| Output | Text |
| Vision | Supported |
| Function Calling | Supported |
| Structured Outputs | Supported |
| Release Date | October 12, 2026 |
How to Use
- Write your prompt - describe the task, provide context, and specify the desired output format.
- Submit - the model processes your request and returns the response.
API Integration
Base URL: https://llm.wavespeed.ai/v1 API Endpoint: chat/completions Model ID: meta/muse-wonder
API Usage
Python SDK
from openai import OpenAI
client = OpenAI(
api_key="YOUR_API_KEY",
base_url="https://llm.wavespeed.ai/v1"
)
response = client.chat.completions.create(
model="meta/muse-wonder",
messages=[{"role": "user", "content": "Hello!"}]
)
print(response.choices[0].message.content)cURL
curl https://llm.wavespeed.ai/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR_API_KEY" \
-d '{
"model": "meta/muse-wonder",
"messages": [{"role": "user", "content": "Hello!"}]
}'Notes
- Model: meta/muse-wonder
- Provider: meta
Info
Supported Functionality
API Access Guide
Muse Wonder API
meta/muse-wonder
Muse Wonder is a frontier reasoning model from Meta, designed for complex personal and professional agentic tasks. It accepts text, images, video, audio, and PDF documents and returns text, with...
Input
$4 /M
Output
$20 /M
Context
1049K
Max Output
944K
Vision
Supported
Tool Use
Supported
Try Muse Wonder on WaveSpeedAI
Access Muse Wonder through our unified API — OpenAI-compatible, no cold starts, transparent pricing.
Frequently Asked Questions about Muse Wonder
How much does Muse Wonder cost via the API?+
Pricing on WaveSpeedAI: $4.00 per million input tokens and $20.00 per million output tokens. Prompt caching and batch processing are billed separately and reduce effective cost on long, repetitive workloads.
What is the context window of Muse Wonder?+
Muse Wonder supports up to 1049K tokens of context with up to 944K tokens of output per request.
Is Muse Wonder OpenAI-compatible?+
WaveSpeedAI exposes Muse Wonder at https://llm.wavespeed.ai/v1 through the OpenAI-compatible Chat Completions interface. Most OpenAI SDK clients work by changing the base URL and API key; optional fields depend on the selected model.
How do I get started with Muse Wonder?+
Sign in to WaveSpeedAI, create an API key in Access Keys, then send a request to https://llm.wavespeed.ai/v1/chat/completions with the model id shown above. Check the current model catalog for availability, capabilities, and pricing.