API cost decision in 10 seconds

NewMuse Spark Open vs NewSummarize

Pick Summarize for lower cost; pick Muse Spark Open only if the larger context window matters more.

Page updated:  Data confirmed:  Prices normalized to USD per 1M tokens Sample workload: 1M input + 500K output

Budget verdict

Pick Summarize for lower cost; pick Muse Spark Open only if the larger context window matters more.

On the standard 1M input plus 500K output workload, Summarize is estimated at $0.04 vs $3.38 for Muse Spark Open, saving $3.33 (98.8% lower).

Cost-first pickSummarize
Context-first pickMuse Spark Open
Sample savings$3.3398.8%
10x traffic gap$33.35

Muse Spark Open has more context, but Summarize saves $3.33 on the standard workload. At 10x that traffic, the same price gap is about $33.35. Use the calculator below to replace the sample workload with your own token volume.

Cost sensitivity

Workload Sensitivity

Same prices, different token mixes.

Summarize stays cheaper across input-heavy, balanced, and output-heavy sample workloads.

Workload shapeToken mixBetter pickMuse Spark OpenSummarize
Input-heavy / RAG5M input + 500K outputSummarize$8.38$0.2
Balanced workload1M input + 1M outputSummarize$5.5$0.04
Output-heavy chatbot1M input + 5M outputSummarize$22.5$0.04
Cheaper input Summarize $1.25 vs $0.04 / 1M

Summarize is $1.21 cheaper per 1M input tokens (96.8% lower; 31.2x difference).

Cheaper output Summarize $4.25 vs $0 / 1M

Summarize is free for output tokens while Muse Spark Open costs $4.25 per 1M tokens.

Larger context Muse Spark Open 1.05M vs 1M

Muse Spark Open has 48.58K more context (1.05x larger).

Sample workload Summarize $3.38 vs $0.04

Summarize is $3.33 cheaper on the standard workload (98.8% lower).

Estimate your workload cost

Your Workload Cost

Prices are normalized to USD per 1M tokens.
Muse Spark Open Calculating… Estimated API cost
Summarize Calculating… Estimated API cost
Cheaper for this workload Calculating… Difference: calculating…

This estimate uses normalized public API pricing per 1M tokens. It is a planning aid, not a billing quote. Verify provider pricing, limits, and terms before production use.

Quick Decision

Verdict

Summarize has the lower input price; Summarize has the lower output price; Muse Spark Open offers the larger context window. For the 1M input plus 500K output sample, Summarize is cheaper for the standard workload.

For a 1M input token plus 500K output token workload, the estimated API cost is $3.38 for Muse Spark Open and $0.04 for Summarize.

Best Fit

Choose Muse Spark Open when you care most about larger context window.

Choose Summarize when you care most about lower input-token price, and lower output-token price.

Decision Notes
  • On the standard 1M input plus 500K output workload, Summarize is estimated at $0.04 vs $3.38 for Muse Spark Open, saving $3.33 (98.8% lower).
  • Summarize is $3.33 cheaper on the standard workload (98.8% lower).
  • Summarize is $1.21 cheaper per 1M input tokens (96.8% lower; 31.2x difference).
  • Summarize is free for output tokens while Muse Spark Open costs $4.25 per 1M tokens.
  • Muse Spark Open has 48.58K more context (1.05x larger).
Head-to-Head Specs
FeatureNewMuse Spark Open
(Meta)
NewSummarize
(ScaleDown)
Input Price
prompt tokens per 1M
$1.25$0.04
Completion Price
per 1M tokens
$4.25$0
Sample Workload Cost
1M input + 500K output
$3.38$0.04
Context Window1.05M1M
Release Date

Use-Case Decision Matrix

Use caseBetter pickWhy
Budget-constrained productionSummarizeOn the standard 1M input plus 500K output workload, Summarize is estimated at $0.04 vs $3.38 for Muse Spark Open, saving $3.33 (98.8% lower).
High-volume input processingSummarizeLower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill.
Long responses and chatbotsSummarizeLower output-token price matters most when assistants generate many completion tokens.
RAG or long-document workMuse Spark OpenA larger context window leaves more room for retrieved passages, conversation history, or source files.

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Meta catalog

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ScaleDown catalog

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Muse Spark Open

Muse Spark Open is a coding-optimized open-weight model. Trained specifically for agentic coding workflows, it delivers higher first-attempt accuracy, reliable tool calling, and deep codebase understanding across the repos developers...

Summarize

Summarize is an abstractive summarization model from ScaleDown. It condenses long text and documents into a fluent, faithful rewrite rather than lifting sentences from the source, and is suited for...