Inkling-Small vs Sakana Namazu: Specs & Benchmark Comparison
Inkling-Small is developed by Thinking Machines Lab, while Sakana Namazu comes from Sakana AI. Inkling-Small was released in July 2026, and Sakana Namazu followed a month later in August 2026. Inkling-Small has a published size of about 276 billion parameters; Sakana AI has not disclosed the parameter count of Sakana Namazu.
We have 24 benchmark results for Inkling-Small and 3 benchmark results for Sakana Namazu, but they overlap on a single test: AIME 2026, where Sakana Namazu scores 96.7% against 95.5%.
Inkling-Small is the cheaper API at $0.30 per million input tokens and $1.20 per million output tokens, roughly 3 times cheaper than Sakana Namazu at $0.95 and $4. Both accept a context window of about 256K tokens. Inkling-Small accepts text, images, and audio as input, while Sakana Namazu accepts text and images.
| 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 | 60.3% | 92.4% |
| Benchmarks | ||
| AIME 2026 | 95.5% | 96.7% |
Visual Benchmark Comparison
Verdict
Inkling-Small leads in 1 out of 4 comparison categories.
Both models show comparable average scores: Inkling-Small — 0.6, Sakana Namazu — 0.9.
Inkling-Small is 3.3x cheaper: input $0.30/1M vs $0.95/1M tokens.
Same context size: 256K tokens.
Both models were released around the same time: 7/30/2026 and 8/3/2026.
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Frequently Asked Questions
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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.