Inkling-Small vs Sakana Namazu: Specs & Benchmark Comparison
| Characteristic | Inkling-Small | Sakana Namazu |
|---|---|---|
| Company | Thinking Machines Lab | Sakana AI |
| Release Date | July 30, 2026 | August 3, 2026 |
| Parameters | 276B | — |
| Multimodal | Yes | Yes |
| Context (input) | 256K | 256K |
| Context (output) | 256K | 256K |
| Input Price / 1M | $0.30 | $0.95 |
| Output Price / 1M | $1.20 | $4.00 |
| Average Score | 0.6 | 0.9 |
| Benchmarks | ||
| AIME 2026 | 1.0 | 1.0 |
Visual Benchmark Comparison
Inkling-Small
Sakana Namazu
AIME 20261.0 vs 1.0
1.0
1.0
Verdict
Inkling-Small leads in 1 out of 4 comparison categories.
Overall Performance
Both models show comparable average scores: Inkling-Small — 0.6, Sakana Namazu — 0.9.
API Cost
Inkling-Small is 3.3x cheaper: input $0.30/1M vs $0.95/1M tokens.
Context Window
Same context size: 256K tokens.
Recency
Both models were released around the same time: 7/30/2026 and 8/3/2026.
More About These Models
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Frequently Asked Questions
Which is better for coding — Inkling-Small 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 — Inkling-Small or Sakana Namazu?
Inkling-Small is cheaper for input: $0.30 per 1M tokens vs $0.95.
Which has a larger context window — Inkling-Small or Sakana Namazu?
Inkling-Small supports a larger context: 256,000 tokens vs 256,000.
The Inkling-Small 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 Inkling-Small or Sakana Namazu page. See also the complete list of AI model comparisons.