Nano Banana 2.1 is $1 cheaper per 1M input tokens (40% lower; 1.67x difference).
API cost decision in 10 seconds
NewPareto 26.9 vs NewNano Banana 2.1
Pick Nano Banana 2.1 for lower cost; pick Pareto 26.9 only if the larger context window matters more.
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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 Pareto 26.9 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 $6.25 for Pareto 26.9, saving $1 (16% lower).
Cost-first pickNano Banana 2.1
Context-first pickPareto 26.9
Sample savings$116%
10x traffic gap$10
Pareto 26.9 has more context, but Nano Banana 2.1 saves $1 on the standard workload. At 10x that traffic, the same price gap is about $10. Use the calculator below to replace the sample workload with your own token volume.
Cost sensitivity
Workload Sensitivity
Nano Banana 2.1 stays cheaper across input-heavy, balanced, and output-heavy sample workloads.
| Workload shape | Token mix | Better pick | Pareto 26.9 | Nano Banana 2.1 |
|---|---|---|---|---|
| Input-heavy / RAG | 5M input + 500K output | Nano Banana 2.1 | $16.25 | $11.25 |
| Balanced workload | 1M input + 1M output | Nano Banana 2.1 | $10 | $9 |
| Output-heavy chatbot | 1M input + 5M output | Nano Banana 2.1 | $40 | $39 |
Both models report the same output price at $7.5 per 1M tokens.
Pareto 26.9 has 196.61K more context (4x larger).
Nano Banana 2.1 is $1 cheaper on the standard workload (16% lower).
Estimate your workload cost
Your Workload Cost
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
Nano Banana 2.1 has the lower input price; both models tie on output price; Pareto 26.9 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 $6.25 for Pareto 26.9 and $5.25 for Nano Banana 2.1.
Choose Pareto 26.9 when you care most about larger context window.
Choose Nano Banana 2.1 when you care most about lower input-token price.
- On the standard 1M input plus 500K output workload, Nano Banana 2.1 is estimated at $5.25 vs $6.25 for Pareto 26.9, saving $1 (16% lower).
- Nano Banana 2.1 is $1 cheaper on the standard workload (16% lower).
- Nano Banana 2.1 is $1 cheaper per 1M input tokens (40% lower; 1.67x difference).
- Both models report the same output price at $7.5 per 1M tokens.
- Pareto 26.9 has 196.61K more context (4x larger).
| Feature | NewPareto 26.9 (unbiased) | NewNano Banana 2.1 (Google) |
|---|---|---|
| Input Price prompt tokens per 1M | $2.5 | $1.5 |
| Completion Price per 1M tokens | $7.5 | $7.5 |
| Sample Workload Cost 1M input + 500K output | $6.25 | $5.25 |
| Context Window | 262.14K | 65.54K |
| Release Date |
Use-Case Decision Matrix
| Use case | Better pick | Why |
|---|---|---|
| Budget-constrained production | Nano Banana 2.1 | On the standard 1M input plus 500K output workload, Nano Banana 2.1 is estimated at $5.25 vs $6.25 for Pareto 26.9, saving $1 (16% lower). |
| High-volume input processing | Nano Banana 2.1 | Lower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill. |
| Long responses and chatbots | Tie | Lower output-token price matters most when assistants generate many completion tokens. |
| RAG or long-document work | Pareto 26.9 | A larger context window leaves more room for retrieved passages, conversation history, or source files. |
Related Alternatives
- Pareto 26.10 Preview can replace Pareto 26.9 when lower sample workload cost matters most: $2.4.
- Gemma 4 26B A4B (free) can replace Nano Banana 2.1 when lower sample workload cost matters most: $0.
- Gemma 4 31B (free) can replace Nano Banana 2.1 when lower sample workload cost matters most: $0.
- Lyria 3 Pro Preview can replace Nano Banana 2.1 when lower sample workload cost matters most: $0.
- Grok 4.20 Multi-Agent offers 2M context with $2.5 sample workload cost.
- Grok 4.20 offers 2M context with $2.5 sample workload cost.
- Llama 4 Scout offers 1.31M context with $0.47 sample workload cost.
- MiMo-V2.6-Flash offers 1.05M context with $0.28 sample workload cost.
- DeepSeek V4.1 Flash · DeepSeek · #1
- Step 5 Preview · StepFun · #2
- GLM 5.3 Flash · Z.ai · #3
- MiMo-V2.6-Flash · Xiaomi · #4
Cheaper alternatives
Review low-cost models sorted by a standard 1M input plus 500K output workload.
Open cheapest modelsLarger context alternatives
Find models with larger context windows for RAG, long documents, and codebase review.
Open largest context modelsProvider catalogs
Compare models within provider hubs before choosing a final API vendor.
Open provider hubsunbiased catalog
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Open unbiased modelsGoogle catalog
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Open Google modelsPareto is a multimodal composite model built for research, coding, and agentic workflows, while delivering frontier-level performance across a broad range of general-purpose tasks.
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