Muse Wonder is Meta’s model for complex coding, long-running agents, and computer use. With a 1M-token context window, it plans multi-step tasks, delegates to sub-agents, and combines Active Memory with Active Focus to retain relevant context and sustain progress on challenging tasks.
Pricing
- Input Tokens: $4.4 /M tokens
- Output Tokens: $22 /M tokens
- Cache Read: $0.22 /M tokens
Input Modalities
- Text
- Vision
- Audio
- Video
Output Modalities
- Text
Context length
- 1.05M tokens
Capabilities
- Thinking
- Streaming
- Tool calling
- Web search
- URL context
- Code interpreter
- Computer use
- File search
- Memory tool
- Structured outputs
- Structured decision
- Citations
- Prompt caching
- Background mode
- Server-side sessions
Providers
Meta meta-muse-wonder
Pricing$4.4$22
Cache$0.22
PrecisionⓘNot Disclosed
Latency4.5S
Throughput101.6TPS
Uptime
99.31% uptime 2 days ago
100.00% uptime yesterday
100.00% uptime today
Performance for muse-wonder
Uptime is the percentage of requests that succeeded over the past 72 hours. AIHubMix continuously monitors every provider and automatically retries with the next-best provider when one returns an error or responds too slowly; Latency is total round-trip time (lower is better); Throughput is how fast the model writes (tokens per second, higher is better).
Uptime
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Latency
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Throughput
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Try this model
Python