ricursiveAI/Ripple-65B-Preview is $0.75 cheaper per 1M input tokens (78.9% lower; 4.75x difference).
API cost decision in 10 seconds
NewricursiveAI/Ripple-65B-Preview vs Sakana Namazu
Pick ricursiveAI/Ripple-65B-Preview for lower cost; pick Sakana Namazu 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 ricursiveAI/Ripple-65B-Preview for lower cost; pick Sakana Namazu only if the larger context window matters more.
On the standard 1M input plus 500K output workload, ricursiveAI/Ripple-65B-Preview is estimated at $0.5 vs $2.95 for Sakana Namazu, saving $2.45 (83.1% lower).
Cost-first pickricursiveAI/Ripple-65B-Preview
Context-first pickSakana Namazu
Sample savings$2.4583.1%
10x traffic gap$24.5
Sakana Namazu has more context, but ricursiveAI/Ripple-65B-Preview saves $2.45 on the standard workload. At 10x that traffic, the same price gap is about $24.5. Use the calculator below to replace the sample workload with your own token volume.
Cost sensitivity
Workload Sensitivity
ricursiveAI/Ripple-65B-Preview stays cheaper across input-heavy, balanced, and output-heavy sample workloads.
| Workload shape | Token mix | Better pick | ricursiveAI/Ripple-65B-Preview | Sakana Namazu |
|---|---|---|---|---|
| Input-heavy / RAG | 5M input + 500K output | ricursiveAI/Ripple-65B-Preview | $1.3 | $6.75 |
| Balanced workload | 1M input + 1M output | ricursiveAI/Ripple-65B-Preview | $0.8 | $4.95 |
| Output-heavy chatbot | 1M input + 5M output | ricursiveAI/Ripple-65B-Preview | $3.2 | $20.95 |
ricursiveAI/Ripple-65B-Preview is $3.4 cheaper per 1M output tokens (85% lower; 6.67x difference).
Sakana Namazu has 245.76K more context (16x larger).
ricursiveAI/Ripple-65B-Preview is $2.45 cheaper on the standard workload (83.1% 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
ricursiveAI/Ripple-65B-Preview has the lower input price; ricursiveAI/Ripple-65B-Preview has the lower output price; Sakana Namazu offers the larger context window. For the 1M input plus 500K output sample, ricursiveAI/Ripple-65B-Preview is cheaper for the standard workload.
For a 1M input token plus 500K output token workload, the estimated API cost is $0.5 for ricursiveAI/Ripple-65B-Preview and $2.95 for Sakana Namazu.
Choose ricursiveAI/Ripple-65B-Preview when you care most about lower input-token price, and lower output-token price.
Choose Sakana Namazu when you care most about larger context window.
- On the standard 1M input plus 500K output workload, ricursiveAI/Ripple-65B-Preview is estimated at $0.5 vs $2.95 for Sakana Namazu, saving $2.45 (83.1% lower).
- ricursiveAI/Ripple-65B-Preview is $2.45 cheaper on the standard workload (83.1% lower).
- ricursiveAI/Ripple-65B-Preview is $0.75 cheaper per 1M input tokens (78.9% lower; 4.75x difference).
- ricursiveAI/Ripple-65B-Preview is $3.4 cheaper per 1M output tokens (85% lower; 6.67x difference).
- Sakana Namazu has 245.76K more context (16x larger).
| Feature | NewricursiveAI/Ripple-65B-Preview (ricursiveai) | Sakana Namazu (Sakana) |
|---|---|---|
| Input Price prompt tokens per 1M | $0.2 | $0.95 |
| Completion Price per 1M tokens | $0.6 | $4 |
| Sample Workload Cost 1M input + 500K output | $0.5 | $2.95 |
| Context Window | 16.38K | 262.14K |
| Release Date |
Use-Case Decision Matrix
| Use case | Better pick | Why |
|---|---|---|
| Budget-constrained production | ricursiveAI/Ripple-65B-Preview | On the standard 1M input plus 500K output workload, ricursiveAI/Ripple-65B-Preview is estimated at $0.5 vs $2.95 for Sakana Namazu, saving $2.45 (83.1% lower). |
| High-volume input processing | ricursiveAI/Ripple-65B-Preview | Lower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill. |
| Long responses and chatbots | ricursiveAI/Ripple-65B-Preview | Lower output-token price matters most when assistants generate many completion tokens. |
| RAG or long-document work | Sakana Namazu | A larger context window leaves more room for retrieved passages, conversation history, or source files. |
Related Alternatives
- No lower-cost same-provider swap is currently tracked for this pair.
- Grok 4.20 Multi-Agent offers 2M context with $2.5 sample workload cost.
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- Llama 4 Scout offers 1.31M context with $0.25 sample workload cost.
- GPT-6 Luna offers 1.05M context with $0.35 sample workload cost.
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Open Sakana modelsRipple-65B-Preview by ricursiveAI, a 65B model with native tool calling, served in BF16.
Sakana Namazu is a Japanese-specialized reasoning model from Sakana AI, based on Kimi K2.6 with additional training for Japanese language and business contexts. It is suited for Japanese instruction following,...