API cost decision in 10 seconds
Sakana Namazu vs 🔥DeepSeek V4 Flash 0731
Pick DeepSeek V4 Flash 0731 when budget and context both matter.
Pricing data updated:
Prices normalized to USD per 1M tokens
Sample workload: 1M input + 500K output
Budget verdict
Pick DeepSeek V4 Flash 0731 when budget and context both matter.
On the standard 1M input plus 500K output workload, DeepSeek V4 Flash 0731 is estimated at $0.08 vs $2.95 for Sakana Namazu, saving $2.87 (97.3% lower).
Cost-first pickDeepSeek V4 Flash 0731
Context-first pickDeepSeek V4 Flash 0731
Sample savings$2.8797.3%
10x traffic gap$28.7
DeepSeek V4 Flash 0731 is cheaper on the standard workload and also has the larger context window. At 10x that traffic, the same price gap is about $28.7. Use the calculator below to replace the sample workload with your own token volume.
Cost sensitivity
Workload Sensitivity
DeepSeek V4 Flash 0731 stays cheaper across input-heavy, balanced, and output-heavy sample workloads.
| Workload shape | Token mix | Better pick | Sakana Namazu | DeepSeek V4 Flash 0731 |
|---|---|---|---|---|
| Input-heavy / RAG | 5M input + 500K output | DeepSeek V4 Flash 0731 | $6.75 | $0.24 |
| Balanced workload | 1M input + 1M output | DeepSeek V4 Flash 0731 | $4.95 | $0.12 |
| Output-heavy chatbot | 1M input + 5M output | DeepSeek V4 Flash 0731 | $20.95 | $0.44 |
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
DeepSeek V4 Flash 0731 has the lower input price, DeepSeek V4 Flash 0731 has the lower output price, and DeepSeek V4 Flash 0731 offers the larger context window.
For a 1M input token plus 500K output token workload, the estimated API cost is $2.95 for Sakana Namazu and $0.08 for DeepSeek V4 Flash 0731.
Choose Sakana Namazu when its provider, model quality, latency, or availability is more important than the numeric price/context winner.
Choose DeepSeek V4 Flash 0731 when you care most about lower input-token price, lower output-token price, and larger context window.
| Feature | Sakana Namazu (Sakana) | 🔥DeepSeek V4 Flash 0731 (DeepSeek) |
|---|---|---|
| Input Price prompt tokens per 1M | $0.95 | $0.04 |
| Completion Price per 1M tokens | $4 | $0.08 |
| Sample Workload Cost 1M input + 500K output | $2.95 | $0.08 |
| Context Window | 262.14K | 1.31M |
| Release Date | 2026-08-11 | 2026-07-31 |
| Popularity | #4 |
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,...
DeepSeek V4 Flash 0731 is a sparse mixture-of-experts model from DeepSeek, with 13B active parameters out of 284B total. This re-post-trained revision is suited for coding, reasoning, and agent workflows....
Use-Case Decision Matrix
| Use case | Better pick | Why |
|---|---|---|
| Budget-constrained production | DeepSeek V4 Flash 0731 | On the standard 1M input plus 500K output workload, DeepSeek V4 Flash 0731 is estimated at $0.08 vs $2.95 for Sakana Namazu, saving $2.87 (97.3% lower). |
| High-volume input processing | DeepSeek V4 Flash 0731 | Lower prompt-token price matters most when prompts or retrieved passages dominate the bill. |
| Long responses and chatbots | DeepSeek V4 Flash 0731 | Lower output-token price matters most when assistants generate many completion tokens. |
| RAG or long-document work | DeepSeek V4 Flash 0731 | A larger context window leaves more room for retrieved passages and source files. |