Qwen3.5 27B vs Sakana Namazu: Specs & Benchmark Comparison

Qwen3.5 27B is developed by Alibaba, while Sakana Namazu comes from Sakana AI. Qwen3.5 27B was released in March 2026, and Sakana Namazu followed 5 months later in August 2026. Qwen3.5 27B has a published size of about 27 billion parameters; Sakana AI has not disclosed the parameter count of Sakana Namazu.

The two models share 2 published benchmarks. Sakana Namazu leads on 2 of them. The widest gaps are on LiveCodeBench v6, where Sakana Namazu scores 90.3% against 80.7%; MMLU-Pro, where Sakana Namazu scores 90.3% against 86.1%. Averaged across everything we track, Qwen3.5 27B sits at 70.3% and Sakana Namazu at 92.4%.

Sakana Namazu is available through an API at $0.95 per million input tokens with a 256K-token context window. We do not track a hosted API for Qwen3.5 27B, so pricing and context cannot be compared directly.

CharacteristicQwen3.5 27BSakana Namazu
CompanyAlibabaSakana AI
Release DateMarch 1, 2026August 3, 2026
Parameters27B
MultimodalNoYes
Context (input)256K
Context (output)256K
Input Price / 1M$0.95
Output Price / 1M$4.00
Average Score70.3%92.4%
Benchmarks
LiveCodeBench v680.7%90.3%
MMLU-Pro86.1%90.3%

Visual Benchmark Comparison

Qwen3.5 27B
Sakana Namazu
LiveCodeBench v60.8 vs 0.9
0.8
0.9
MMLU-Pro0.9 vs 0.9
0.9
0.9

Verdict

Sakana Namazu leads in 1 out of 2 comparison categories.

Overall Performance

Both models show comparable average scores: Qwen3.5 27B — 0.7, Sakana Namazu — 0.9.

Recency

Sakana Namazu is newer: released 8/3/2026 vs 3/1/2026.

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Frequently Asked Questions

Which is better for coding — Qwen3.5 27B 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 — Qwen3.5 27B or Sakana Namazu?
API pricing data is available on the individual model pages.
Which has a larger context window — Qwen3.5 27B or Sakana Namazu?
Context window data is available on the individual model pages.

The Qwen3.5 27B 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 Qwen3.5 27B or Sakana Namazu page. See also the complete list of AI model comparisons.