GLM-5.3 vs Sakana Namazu: Specs & Benchmark Comparison
GLM-5.3 is developed by Zhipu AI, while Sakana Namazu comes from Sakana AI. Both were released in August 2026. GLM-5.3 has a published size of about 753 billion parameters; Sakana AI has not disclosed the parameter count of Sakana Namazu.
We have 17 benchmark results for GLM-5.3 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 47% below GLM-5.3 at $1.40 and $4.40. GLM-5.3 takes the larger context window at 1M tokens, compared with 256K for Sakana Namazu. GLM-5.3 accepts text as input, while Sakana Namazu accepts text and images. On tooling, only GLM-5.3 supports function calling and only GLM-5.3 offers structured output.
| Characteristic | GLM-5.3 | Sakana Namazu |
|---|---|---|
| Company | Zhipu AI | Sakana AI |
| Release Date | August 14, 2026 | August 3, 2026 |
| Parameters | 753B | — |
| Multimodal | No | Yes |
| Context (input) | 1.0M | 256K |
| Context (output) | 131K | 256K |
| Input Price / 1M | $1.40 | $0.95 |
| Output Price / 1M | $4.40 | $4.00 |
| Average Score | 52.2% | 92.4% |
Verdict
Both models show equal results — the choice depends on your specific use case.
Both models show comparable average scores: GLM-5.3 — 0.5, Sakana Namazu — 0.9.
Sakana Namazu is 1.2x cheaper: input $0.95/1M vs $1.40/1M tokens.
GLM-5.3 supports a larger context: 1M vs 256K tokens.
Both models were released around the same time: 8/14/2026 and 8/3/2026.
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Frequently Asked Questions
Which is better for coding — GLM-5.3 or Sakana Namazu?
Which model is cheaper — GLM-5.3 or Sakana Namazu?
Which has a larger context window — GLM-5.3 or Sakana Namazu?
The GLM-5.3 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 GLM-5.3 or Sakana Namazu page. See also the complete list of AI model comparisons.