Qwen3.7-Plus vs Sakana Namazu
Qwen3.7-Plus and Sakana Namazu are closely matched at 43.3 and 43.2 on the LLM Stats Score. Qwen3.7-Plus is 3.1x cheaper per token.
Alibaba Cloud / Qwen Team · Sakana AI · Updated for 2026
Which is better?
Qwen3.7-Plus and Sakana Namazu are closely matched on the overall LLM Stats Score at 43.3 and 43.2.
In the 2 individual benchmarks reported for both models, Sakana Namazu wins 2; this is a narrower head-to-head signal than the composite indexes.
On price, Qwen3.7-Plus is roughly 3.1x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Qwen3.7-Plus also accepts a larger context window (1,000,000 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 Qwen3.7-Plus
- cost matters — it's about 3.1x cheaper per token
- you process long inputs — it offers a 1,000,000 token context window
Choose Sakana Namazu
- you value its reported benchmark strengths — it wins 2 of 2 exact shared results
- you want the most recent training data — it shipped Aug 2026
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
70 reported for Qwen3.7-Plus · 3 for Sakana Namazu
Qwen3.7-Plus outperforms in 0 benchmarks, while Sakana Namazu is better at 2 benchmarks (LiveCodeBench v6, MMLU-Pro).
Sakana Namazu significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, Qwen3.7-Plus ($0.32/1M tokens) is 3.0x cheaper than Sakana Namazu ($0.95/1M tokens).
For output processing, Qwen3.7-Plus ($1.28/1M tokens) is 3.1x cheaper than Sakana Namazu ($4.00/1M tokens).
In conclusion, Sakana Namazu is more expensive than Qwen3.7-Plus.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
Qwen3.7-Plus accepts 1,000,000 input tokens compared to Sakana Namazu's 256,000 tokens. Sakana Namazu can generate longer responses up to 256,000 tokens, while Qwen3.7-Plus is limited to 65,536 tokens.
Input capabilities
Documented input modalities across available providers
Both Qwen3.7-Plus and Sakana Namazu support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
Qwen3.7-Plus
Sakana Namazu
License
Usage and distribution terms
Both models are licensed under proprietary licenses.
Both models have usage restrictions defined by their respective organizations.
Proprietary
Closed source
Proprietary
Closed source
Release Timeline
When each model was launched
Qwen3.7-Plus was released on 2026-05-31, while Sakana Namazu was released on 2026-08-03.
Sakana Namazu is 2 months newer than Qwen3.7-Plus.
May 31, 2026
2 months ago
Aug 3, 2026
3 weeks ago
2mo newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
Qwen3.7-Plus is available from Together, Fireworks. Sakana Namazu is available from Sakana AI.
Qwen3.7-Plus
Sakana Namazu
Outputs Comparison
Judge for yourself.
Run your own prompts against Qwen3.7-Plus and Sakana Namazu side-by-side, then vote on the output you prefer.
FAQ
Common questions about Qwen3.7-Plus vs Sakana Namazu.