Kimi K2.7 Code vs Sakana Namazu
Kimi K2.7 Code and Sakana Namazu are closely matched at 39.6 and 43.2 on the LLM Stats Score. Kimi K2.7 Code is 1.2x cheaper per token.
Moonshot AI · Sakana AI · Updated for 2026
Which is better?
Kimi K2.7 Code and Sakana Namazu are closely matched on the overall LLM Stats Score at 39.6 and 43.2.
On price, Kimi K2.7 Code is roughly 1.2x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Kimi K2.7 Code 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 Kimi K2.7 Code
- cost matters — it's about 1.2x cheaper per token
- you process long inputs — it offers a 262,144 token context window
- you need open weights you can self-host or fine-tune
Choose Sakana Namazu
- you want the most recent training data — it shipped Aug 2026
At a glance
The differences that matter most.
Individual benchmarks
9 reported for Kimi K2.7 Code · 3 for Sakana Namazu
Kimi K2.7 Code 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, Kimi K2.7 Code ($0.74/1M tokens) is 1.3x cheaper than Sakana Namazu ($0.95/1M tokens).
For output processing, Kimi K2.7 Code ($3.50/1M tokens) is 1.1x cheaper than Sakana Namazu ($4.00/1M tokens).
In conclusion, Sakana Namazu is more expensive than Kimi K2.7 Code.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
Kimi K2.7 Code 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 Kimi K2.7 Code is limited to 131,072 tokens.
Input capabilities
Documented input modalities across available providers
Both Kimi K2.7 Code and Sakana Namazu support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
Kimi K2.7 Code
Sakana Namazu
License
Usage and distribution terms
Kimi K2.7 Code is licensed under Modified MIT License, while Sakana Namazu uses a proprietary license.
License differences may affect how you can use these models in commercial or open-source projects.
Modified MIT License
Open weights
Proprietary
Closed source
Release Timeline
When each model was launched
Kimi K2.7 Code was released on 2026-06-12, while Sakana Namazu was released on 2026-08-03.
Sakana Namazu is 2 months newer than Kimi K2.7 Code.
Jun 12, 2026
2 months ago
Aug 3, 2026
3 weeks ago
1mo newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
Kimi K2.7 Code is available from DeepInfra, Fireworks, Moonshot AI, Novita, Together. Sakana Namazu is available from Sakana AI.
Kimi K2.7 Code
Sakana Namazu
Outputs Comparison
Judge for yourself.
Run your own prompts against Kimi K2.7 Code and Sakana Namazu side-by-side, then vote on the output you prefer.
FAQ
Common questions about Kimi K2.7 Code vs Sakana Namazu.