DeepSeek-V4-Flash-Max vs Sakana Namazu: Specs & Benchmark Comparison
| Characteristic | DeepSeek-V4-Flash-Max | Sakana Namazu |
|---|---|---|
| Company | DeepSeek | Sakana AI |
| Release Date | April 23, 2026 | August 3, 2026 |
| Parameters | 284B | — |
| Multimodal | No | Yes |
| Context (input) | 1.0M | 256K |
| Context (output) | 393K | 256K |
| Input Price / 1M | $0.14 | $0.95 |
| Output Price / 1M | $0.28 | $4.00 |
| Average Score | 0.9 | 0.9 |
Verdict
DeepSeek-V4-Flash-Max leads in 2 out of 4 comparison categories.
Overall Performance
Both models show comparable average scores: DeepSeek-V4-Flash-Max — 0.9, Sakana Namazu — 0.9.
API Cost
DeepSeek-V4-Flash-Max is 11.8x cheaper: input $0.14/1M vs $0.95/1M tokens.
Context Window
DeepSeek-V4-Flash-Max supports a larger context: 1M vs 256K tokens.
Recency
Sakana Namazu is newer: released 8/3/2026 vs 4/23/2026.
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Frequently Asked Questions
Which is better for coding — DeepSeek-V4-Flash-Max or Sakana Namazu?
Direct comparison on the SWE-Bench benchmark is not available. We recommend reviewing other metrics on the comparison page.
Which model is cheaper — DeepSeek-V4-Flash-Max or Sakana Namazu?
DeepSeek-V4-Flash-Max is cheaper for input: $0.14 per 1M tokens vs $0.95.
Which has a larger context window — DeepSeek-V4-Flash-Max or Sakana Namazu?
DeepSeek-V4-Flash-Max supports a larger context: 1,000,000 tokens vs 256,000.
The DeepSeek-V4-Flash-Max and Sakana Namazu comparison is updated for 2026. Data includes benchmark results, API pricing, context window size and other specifications. For more detailed information, visit the DeepSeek-V4-Flash-Max or Sakana Namazu page. See also the complete list of AI model comparisons.