Muse Spark 1.3
muse-spark-1.3Muse Spark 1.3 is a multimodal reasoning model from Meta for long-running agentic, multi-agent, and coding workflows. It is designed to keep track of information across extended tasks, work through... Built by Meta.
Prices updated
Input price
$1.25
per 1M tokens · Standard
Output price
$4.25
per 1M tokens · Standard
Input limit
1M
tokens
Output limit
944K
tokens
Input formats
Output formats
Muse Spark 1.3 price history
2 price records since 9/25/2026
Muse Spark 1.3 cost calculator
$46/month
Standard pricing
Overview
What is Muse Spark 1.3?
Muse Spark 1.3 is a text & reasoning and vision model from Meta. Muse Spark 1.3 is a multimodal reasoning model from Meta for long-running agentic, multi-agent, and coding workflows. It is designed to keep track of information across extended tasks, work through... Its 1M context window and $1.25 input price make it a candidate for quality-focused production applications.
Benchmarks
Muse Spark 1.3 benchmarks & speed
How Muse Spark 1.3 scores on standardized evaluations, and where it lands among every model we track.
48.1
Intelligence Index
146tok/s
Output speed
1358
DesignArena Elo
Reasoning
GPQA Diamond
93.5%
Graduate-level scientific reasoning · top 7%
HLE
48.7%
Humanity's Last Exam · top 5%
Coding
SciCode
58.8%
Python for scientific computing · top 10%
Latency & design
- Time to first token
- 47.86s
- DesignArena win rate
- 57.3%
- Design battles judged
- 41,855
Independent scores from Artificial Analysis and DesignArena · updated 10/8/2026. Higher is better; ranks compare against every model we track with that score.
Rates
Muse Spark 1.3 pricing
Pricing is based on token usage. Provider-specific caching, batch, regional, and tool charges may affect the final cost.
Input · Standard
$1.25
Per 1M tokens
Cached input · Standard
$0.15
Per 1M tokens
Capabilities
Muse Spark 1.3 Tools
Tools available when using Muse Spark 1.3 through supported provider APIs.
Function calling
Supported
Structured outputs
Supported
JSON mode
Supported
Reasoning
Supported
Built-in web search
Not supported
Log probabilities
Not supported
Deterministic seed
Not supported
Parallel tool calls
Not supported
Prompt caching
Supported
Strengths and limitations
Strengths
- Measured results (AA Intelligence 48.1 · DesignArena Elo 1358) position it for demanding production work.
- 1M context supports large documents, repositories and extended conversations.
- Supports text & reasoning and vision workloads in one model.
Limitations
- Generated tokens cost 3× more than input tokens, which matters for verbose responses.
- Large context capacity does not guarantee consistent retrieval across the entire prompt.
- Arena Elo and MMLU-Pro are directional; test accuracy, latency and reliability on your own workload before committing.
Arena Elo, MMLU-Pro and pricing figures are illustrative; validate current vendor terms before purchase.
Same provider