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Qwen3.8-27B vs Sakana Namazu

Qwen3.8-27B and Sakana Namazu are closely matched at 45.2 and 42.8 on the LLM Stats Score.

Alibaba Cloud / Qwen Team · Sakana AI · Updated for 2026

Which is better?

Qwen3.8-27B and Sakana Namazu are closely matched on the overall LLM Stats Score at 45.2 and 42.8.

In the 1 individual benchmarks reported for both models, Sakana Namazu wins 1; this is a narrower head-to-head signal than the composite indexes.

Qwen3.8-27B also accepts a larger context window (262,144 input tokens), making it the stronger choice for long documents and large codebases.

Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.

Choose Qwen3.8-27B

  • you process long inputs — it offers a 262,144 token context window
  • you want the most recent training data — it shipped Aug 2026
  • you need open weights you can self-host or fine-tune

Choose Sakana Namazu

  • you value its reported benchmark strengths — it wins 1 of 1 exact shared results

At a glance

The differences that matter most.

Core performance indexes
45.2
#30
42.8
#43
44.8
#31
42.5
#42
Cost, coverage & limits
Benchmark wins
0 of 1
1 of 1
Input price
— / M
$0.95 / M
Output price
— / M
$4.00 / M
Context window
262,144
256,000

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
Qwen3.8-27B
Sakana Namazu
31.0#68
39.0#21
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

26 reported for Qwen3.8-27B · 3 for Sakana Namazu

1 shared

Qwen3.8-27B outperforms in 0 benchmarks, while Sakana Namazu is better at 1 benchmark (LiveCodeBench v6).

Sakana Namazu significantly outperforms across most benchmarks.

Sun Sep 06 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Context Window

Maximum input and output token capacity

Qwen3.8-27B accepts 262,144 input tokens compared to Sakana Namazu's 256,000 tokens. Sakana Namazu can generate longer responses up to 256,000 tokens, while Qwen3.8-27B is limited to 131,072 tokens.

Alibaba Cloud / Qwen Team
Qwen3.8-27B
Input262,144 tokens
Output131,072 tokens
Sakana AI
Sakana Namazu
Input256,000 tokens
Output256,000 tokens
Sun Sep 06 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Both Qwen3.8-27B and Sakana Namazu support multimodal inputs.

They are both capable of processing various types of data, offering versatility in application.

Qwen3.8-27B

Text
Images
Audio
Video

Sakana Namazu

Text
Images
Audio
Video

License

Usage and distribution terms

Qwen3.8-27B is licensed under Apache 2.0, while Sakana Namazu uses a proprietary license.

License differences may affect how you can use these models in commercial or open-source projects.

Qwen3.8-27B

Apache 2.0

Open weights

Sakana Namazu

Proprietary

Closed source

Release Timeline

When each model was launched

Qwen3.8-27B was released on 2026-08-14, while Sakana Namazu was released on 2026-08-03.

Qwen3.8-27B is 0 month newer than Sakana Namazu.

Qwen3.8-27B

Aug 14, 2026

3 weeks ago

1w newer
Sakana Namazu

Aug 3, 2026

1 months ago

Knowledge Cutoff

When training data ends

Neither model specifies a knowledge cutoff date.

Unable to compare the recency of their training data.

No cutoff dates available

Provider Availability

Qwen3.8-27B is available from FriendliAI. Sakana Namazu is available from Sakana AI.

Qwen3.8-27B

friendli logo
FriendliAI

Sakana Namazu

sakana logo
Unknown Organization
Input Price:Input: $0.95/1MOutput Price:Output: $4.00/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion

Judge for yourself.

Run your own prompts against Qwen3.8-27B and Sakana Namazu side-by-side, then vote on the output you prefer.

Qwen3.8-27B
✓ Preferred
Sakana Namazu
Open in Playground

FAQ

Common questions about Qwen3.8-27B vs Sakana Namazu.

Which is better, Qwen3.8-27B or Sakana Namazu?

Qwen3.8-27B and Sakana Namazu are closely matched on the LLM Stats Score at 45.2 and 42.8. Qwen3.8-27B is made by Alibaba Cloud / Qwen Team and Sakana Namazu is made by Sakana AI. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does Qwen3.8-27B compare to Sakana Namazu in benchmarks?

Qwen3.8-27B scores MathVision: 94.6%, OmniDocBench 1.5: 91.1%, LiveCodeBench v6: 90.3%, CharXiv-R: 90.2%, GPQA: 89.2%. Sakana Namazu scores AIME 2026: 96.7%, LiveCodeBench v6: 90.3%, MMLU-Pro: 90.3%.

What are the context window sizes for Qwen3.8-27B and Sakana Namazu?

Qwen3.8-27B supports 262K tokens and Sakana Namazu supports 256K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between Qwen3.8-27B and Sakana Namazu?

Key differences include LLM Stats Score (45.2 vs 42.8), context window (262K vs 256K), licensing (Apache 2.0 vs Proprietary). See the full comparison above for benchmark-by-benchmark results.

Who makes Qwen3.8-27B and Sakana Namazu?

Qwen3.8-27B is developed by Alibaba Cloud / Qwen Team and Sakana Namazu is developed by Sakana AI.