Gemini 3.7 Flash vs Sakana Namazu: Specs & Benchmark Comparison
| Characteristic | Gemini 3.7 Flash | Sakana Namazu |
|---|---|---|
| Company | Sakana AI | |
| Release Date | August 13, 2026 | August 3, 2026 |
| Parameters | — | — |
| Multimodal | Yes | Yes |
| Context (input) | 1.0M | 256K |
| Context (output) | 66K | 256K |
| Input Price / 1M | $0.75 | $0.95 |
| Output Price / 1M | $3.75 | $4.00 |
| Average Score | 0.8 | 0.9 |
Verdict
Gemini 3.7 Flash leads in 2 out of 4 comparison categories.
Overall Performance
Both models show comparable average scores: Gemini 3.7 Flash — 0.8, Sakana Namazu — 0.9.
API Cost
Gemini 3.7 Flash is 1.1x cheaper: input $0.75/1M vs $0.95/1M tokens.
Context Window
Gemini 3.7 Flash 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 — Gemini 3.7 Flash 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 — Gemini 3.7 Flash or Sakana Namazu?
Gemini 3.7 Flash is cheaper for input: $0.75 per 1M tokens vs $0.95.
Which has a larger context window — Gemini 3.7 Flash or Sakana Namazu?
Gemini 3.7 Flash supports a larger context: 1,048,576 tokens vs 256,000.
The Gemini 3.7 Flash 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 Gemini 3.7 Flash or Sakana Namazu page. See also the complete list of AI model comparisons.