Gemini 3.6 Flash vs Sakana Namazu
Gemini 3.6 Flash and Sakana Namazu are closely matched at 44.4 and 43.2 on the LLM Stats Score. Sakana Namazu is 1.8x cheaper per token.
Google · Sakana AI · Updated for 2026
Which is better?
Gemini 3.6 Flash and Sakana Namazu are closely matched on the overall LLM Stats Score at 44.4 and 43.2.
On price, Sakana Namazu is roughly 1.8x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Gemini 3.6 Flash also accepts a larger context window (1,048,576 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 Gemini 3.6 Flash
- you process long inputs — it offers a 1,048,576 token context window
Choose Sakana Namazu
- cost matters — it's about 1.8x cheaper per token
- you want the most recent training data — it shipped Aug 2026
At a glance
The differences that matter most.
Individual benchmarks
7 reported for Gemini 3.6 Flash · 3 for Sakana Namazu
Gemini 3.6 Flash and Sakana Namazudon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, Gemini 3.6 Flash ($1.50/1M tokens) is 1.6x more expensive than Sakana Namazu ($0.95/1M tokens).
For output processing, Gemini 3.6 Flash ($7.50/1M tokens) is 1.9x more expensive than Sakana Namazu ($4.00/1M tokens).
In conclusion, Gemini 3.6 Flash is more expensive than Sakana Namazu.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
Gemini 3.6 Flash accepts 1,048,576 input tokens compared to Sakana Namazu's 256,000 tokens. Sakana Namazu can generate longer responses up to 256,000 tokens, while Gemini 3.6 Flash is limited to 65,536 tokens.
Input capabilities
Documented input modalities across available providers
Both Gemini 3.6 Flash and Sakana Namazu support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
Gemini 3.6 Flash
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
Gemini 3.6 Flash was released on 2026-07-21, while Sakana Namazu was released on 2026-08-03.
Sakana Namazu is 0 month newer than Gemini 3.6 Flash.
Jul 21, 2026
1 months ago
Aug 3, 2026
3 weeks ago
1w newerKnowledge Cutoff
When training data ends
Gemini 3.6 Flash has a documented knowledge cutoff of 2026-03-31, while Sakana Namazu's cutoff date is not specified.
We can confirm Gemini 3.6 Flash's training data extends to 2026-03-31, but cannot make a direct comparison without Sakana Namazu's cutoff date.
Mar 2026
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Provider Availability
Gemini 3.6 Flash is available from Google. Sakana Namazu is available from Sakana AI.
Gemini 3.6 Flash
Sakana Namazu
Outputs Comparison
Judge for yourself.
Run your own prompts against Gemini 3.6 Flash and Sakana Namazu side-by-side, then vote on the output you prefer.
FAQ
Common questions about Gemini 3.6 Flash vs Sakana Namazu.