DeepSeek-V4-Pro-0813 vs Sakana Namazu: Specs & Benchmark Comparison

DeepSeek-V4-Pro-0813 is developed by DeepSeek, while Sakana Namazu comes from Sakana AI. Both were released in August 2026. DeepSeek-V4-Pro-0813 has a published size of about 1.6 trillion parameters; Sakana AI has not disclosed the parameter count of Sakana Namazu.

We have 12 benchmark results for DeepSeek-V4-Pro-0813 and 3 benchmark results for Sakana Namazu, but they were measured on different benchmarks, so there is no like-for-like scoreboard.

Sakana Namazu is the cheaper API at $0.95 per million input tokens and $4 per million output tokens, about 39% below DeepSeek-V4-Pro-0813 at $1.32 and $3.96. DeepSeek-V4-Pro-0813 takes the larger context window at 1M tokens, compared with 256K for Sakana Namazu. DeepSeek-V4-Pro-0813 accepts text as input, while Sakana Namazu accepts text and images. On tooling, only DeepSeek-V4-Pro-0813 supports function calling and only DeepSeek-V4-Pro-0813 offers structured output.

CharacteristicDeepSeek-V4-Pro-0813Sakana Namazu
CompanyDeepSeekSakana AI
Release DateAugust 13, 2026August 3, 2026
Parameters1.6T
MultimodalNoYes
Context (input)1.0M256K
Context (output)393K256K
Input Price / 1M$1.32$0.95
Output Price / 1M$3.96$4.00
Average Score60.6%92.4%

Verdict

Both models show equal results — the choice depends on your specific use case.

Overall Performance

Both models show comparable average scores: DeepSeek-V4-Pro-0813 — 0.6, Sakana Namazu — 0.9.

API Cost

Sakana Namazu is 1.1x cheaper: input $0.95/1M vs $1.32/1M tokens.

Context Window

DeepSeek-V4-Pro-0813 supports a larger context: 1M vs 256K tokens.

Recency

Both models were released around the same time: 8/13/2026 and 8/3/2026.

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Frequently Asked Questions

Which is better for coding — DeepSeek-V4-Pro-0813 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-Pro-0813 or Sakana Namazu?
Sakana Namazu is cheaper for input: $0.95 per 1M tokens vs $1.32.
Which has a larger context window — DeepSeek-V4-Pro-0813 or Sakana Namazu?
DeepSeek-V4-Pro-0813 supports a larger context: 1,000,000 tokens vs 256,000.

The DeepSeek-V4-Pro-0813 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-Pro-0813 or Sakana Namazu page. See also the complete list of AI model comparisons.