API cost decision in 10 seconds

NewMuse Wonder vs NewNano Banana 2.1

Pick Nano Banana 2.1 for lower cost; pick Muse Wonder 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 Nano Banana 2.1 for lower cost; pick Muse Wonder only if the larger context window matters more.

On the standard 1M input plus 500K output workload, Nano Banana 2.1 is estimated at $5.25 vs $14 for Muse Wonder, saving $8.75 (62.5% lower).

Cost-first pickNano Banana 2.1
Context-first pickMuse Wonder
Sample savings$8.7562.5%
10x traffic gap$87.5

Muse Wonder has more context, but Nano Banana 2.1 saves $8.75 on the standard workload. At 10x that traffic, the same price gap is about $87.5. Use the calculator below to replace the sample workload with your own token volume.

Cost sensitivity

Workload Sensitivity

Same prices, different token mixes.

Nano Banana 2.1 stays cheaper across input-heavy, balanced, and output-heavy sample workloads.

Workload shapeToken mixBetter pickMuse WonderNano Banana 2.1
Input-heavy / RAG5M input + 500K outputNano Banana 2.1$30$11.25
Balanced workload1M input + 1M outputNano Banana 2.1$24$9
Output-heavy chatbot1M input + 5M outputNano Banana 2.1$104$39
Cheaper input Nano Banana 2.1 $4 vs $1.5 / 1M

Nano Banana 2.1 is $2.5 cheaper per 1M input tokens (62.5% lower; 2.67x difference).

Cheaper output Nano Banana 2.1 $20 vs $7.5 / 1M

Nano Banana 2.1 is $12.5 cheaper per 1M output tokens (62.5% lower; 2.67x difference).

Larger context Muse Wonder 1.05M vs 65.54K

Muse Wonder has 983.04K more context (16x larger).

Sample workload Nano Banana 2.1 $14 vs $5.25

Nano Banana 2.1 is $8.75 cheaper on the standard workload (62.5% lower).

Estimate your workload cost

Your Workload Cost

Prices are normalized to USD per 1M tokens.
Muse Wonder Calculating… Estimated API cost
Nano Banana 2.1 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

Nano Banana 2.1 has the lower input price; Nano Banana 2.1 has the lower output price; Muse Wonder offers the larger context window. For the 1M input plus 500K output sample, Nano Banana 2.1 is cheaper for the standard workload.

For a 1M input token plus 500K output token workload, the estimated API cost is $14 for Muse Wonder and $5.25 for Nano Banana 2.1.

Best Fit

Choose Muse Wonder when you care most about larger context window.

Choose Nano Banana 2.1 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, Nano Banana 2.1 is estimated at $5.25 vs $14 for Muse Wonder, saving $8.75 (62.5% lower).
  • Nano Banana 2.1 is $8.75 cheaper on the standard workload (62.5% lower).
  • Nano Banana 2.1 is $2.5 cheaper per 1M input tokens (62.5% lower; 2.67x difference).
  • Nano Banana 2.1 is $12.5 cheaper per 1M output tokens (62.5% lower; 2.67x difference).
  • Muse Wonder has 983.04K more context (16x larger).
Head-to-Head Specs
FeatureNewMuse Wonder
(Meta)
NewNano Banana 2.1
(Google)
Input Price
prompt tokens per 1M
$4$1.5
Completion Price
per 1M tokens
$20$7.5
Sample Workload Cost
1M input + 500K output
$14$5.25
Context Window1.05M65.54K
Release Date

Use-Case Decision Matrix

Use caseBetter pickWhy
Budget-constrained productionNano Banana 2.1On the standard 1M input plus 500K output workload, Nano Banana 2.1 is estimated at $5.25 vs $14 for Muse Wonder, saving $8.75 (62.5% lower).
High-volume input processingNano Banana 2.1Lower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill.
Long responses and chatbotsNano Banana 2.1Lower output-token price matters most when assistants generate many completion tokens.
RAG or long-document workMuse WonderA larger context window leaves more room for retrieved passages, conversation history, or source files.

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Provider catalogs

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Meta catalog

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Google catalog

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