Ask

Muse Spark 1.1 vs Muse Spark 1.2

Detailed pricing comparison and cost analysis.

Updated September 2026

Cost Simulator

Muse Spark 1.1 Cost
$2.10
Muse Spark 1.2 Cost
$2.10
Same cost at this usage
FeatureMuse Spark 1.1Muse Spark 1.2
ProviderMetaMeta
Input Price (1M)$1.25$1.25
Output Price (1M)$4.25$4.25
Context Window1,048,5761,048,576

Verdict

Muse Spark 1.1 costs $1.25 per 1M input tokens and $4.25 per 1M output tokens. Muse Spark 1.2 costs $1.25 per 1M input tokens and $4.25 per 1M output tokens. Muse Spark 1.1 and Muse Spark 1.2 have identical input token pricing. For output tokens, Muse Spark 1.1 is the more affordable option at $4.25/1M vs $4.25.

On context window, Muse Spark 1.1 supports 1,048,576 tokens — meaning it can fit more conversation history, documents, or code in a single request. This matters for RAG pipelines, long document analysis, and agentic workflows where context builds up over many turns.

When to choose Muse Spark 1.1

  • ✓ You are already integrated with Meta

When to choose Muse Spark 1.2

  • ✓ You are already integrated with Meta

Use the calculator above to simulate your specific workload and find the exact break-even point. For most applications, the cheapest model is the one that minimises your total monthly bill given your input-to-output token ratio.

Frequently Asked Questions

Is Muse Spark 1.1 cheaper than Muse Spark 1.2?

Muse Spark 1.1 and Muse Spark 1.2 have identical input token pricing at $1.25/1M tokens.

What is the context window of Muse Spark 1.1 vs Muse Spark 1.2?

Muse Spark 1.1 has a 1,048,576-token context window. Muse Spark 1.2 has a 1,048,576-token context window. Muse Spark 1.1 supports the larger context, suitable for longer documents and agentic workflows.

Which model is better: Muse Spark 1.1 or Muse Spark 1.2?

The best choice depends on your use case. For cost efficiency on input tokens, Muse Spark 1.1 is the cheaper option. For maximum context length, Muse Spark 1.1 supports 1,048,576 tokens. Use the comparison table above to find the right fit for your workload.