Qwen3.8-Flash-Next vs Sakana Namazu
Qwen3.8-Flash-Next significantly outperforms across most benchmarks.
Alibaba Cloud / Qwen Team · Sakana AI · Updated for 2026
Which is better?
Qwen3.8-Flash-Next outperforms in 1 benchmarks (LiveCodeBench v6), while Sakana Namazu is better at 0 benchmarks. Qwen3.8-Flash-Next significantly outperforms across most benchmarks.
Based on current benchmark, pricing, and model metadata for 2026.
Choose Qwen3.8-Flash-Next
- you want the strongest raw capability — it leads on 1 of 1 shared benchmarks
- 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 want predictable pricing at $0.95/M input and $4.00/M output
At a glance
The differences that matter most.
Performance Benchmarks
Comparative analysis across standard metrics
Qwen3.8-Flash-Next outperforms in 1 benchmarks (LiveCodeBench v6), while Sakana Namazu is better at 0 benchmarks.
Qwen3.8-Flash-Next significantly outperforms across most benchmarks.
Arena Performance
Playground indexes and blind preference scores
Context Window
Maximum input and output token capacity
Only Sakana Namazu specifies input context (256,000 tokens). Only Sakana Namazu specifies output context (256,000 tokens).
Input Capabilities
Supported data types and modalities
Both Qwen3.8-Flash-Next and Sakana Namazu support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
Qwen3.8-Flash-Next
Sakana Namazu
License
Usage and distribution terms
Qwen3.8-Flash-Next is licensed under Qwen Community License 1.0, while Sakana Namazu uses a proprietary license.
License differences may affect how you can use these models in commercial or open-source projects.
Qwen Community License 1.0
Open weights
Proprietary
Closed source
Release Timeline
When each model was launched
Qwen3.8-Flash-Next was released on 2026-08-26, while Sakana Namazu was released on 2026-08-03.
Qwen3.8-Flash-Next is 1 month newer than Sakana Namazu.
Aug 26, 2026
0 days ago
3w newerAug 3, 2026
3 weeks ago
Knowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Outputs Comparison
Judge for yourself.
Run your own prompts against Qwen3.8-Flash-Next and Sakana Namazu side-by-side, then vote on the output you prefer.
FAQ
Common questions about Qwen3.8-Flash-Next vs Sakana Namazu.