sakana
Sakana: Sakana Namazu
sakana/sakana-namazu
Our take
AI-assisted analysis based on the sources below. Suitability is an editorial assessment; test it on your own workload.
The OpenRouter catalog presents sakana/sakana-namazu (canonical sakana/namazu-20260811) as a text-output reasoning model accepting text, image, and file inputs. It describes the variant as derived from Kimi K2.6 and additionally trained for Japanese language and business contexts, with reasoning enabled by default at high effort and a no-reasoning option. The catalog reports a 262,144-token context window, tool-use and structured-output parameters, and optional web search. No benchmark results or independent model card were supplied.[1]
Strengths
- Accepts text, image, and file inputs and returns text, according to the catalog.[1]
- The reported 262,144-token context window and default high-effort reasoning may suit long or complex tasks.[1]
- Tool choice, structured outputs, reasoning controls, and optional web search offer integration flexibility.[1]
Limitations
- Only an OpenRouter catalog entry was supplied; without an independent model card, capabilities and provenance need verification.[1]
- The catalog's benchmark fields contained no results, so measured performance and comparisons remain unknown.[1]
- Knowledge cutoff, licensing, hardware requirements, and safety behavior were not reported; operational fit must be assessed separately.[1]
Where to use it
- Evaluate Japanese instruction-following and business-language assistance, provided workload tests confirm acceptable quality.[1]
- Test long-document or file-grounded text workflows that can benefit from multimodal inputs and the reported context window.[1]
- Prototype applications that need controllable reasoning effort, tool calls, or structured outputs, while validating latency and reliability.[1]
Sources
- [1] OpenRouter catalog · Sakana: Sakana NamazuSources checked: Nov 13, 2026
About this model
Description below is the original text supplied by OpenRouter, shown in the source language.
Sakana Namazu is a Japanese-specialized reasoning model from Sakana AI, based on Kimi K2.6 with additional training for Japanese language and business contexts. It is suited for Japanese instruction following,...
Specifications
- Model ID
- sakana/sakana-namazu
- Canonical ID
- sakana/namazu-20260811
- Creator
- sakana
- Added to OpenRouter
- 11.08.2026
- Context length
- 262,144
- Modality
- text+image+file->text
- Input modalities
- text, image, file
- Output modalities
- text
- Token pricing
- USD per 1M tokens: in $0.950 / out $4
- Knowledge cutoff
- —
- Expiration date
- —
Tasks and capabilities
A grade appears only where the source supplies a matching measurement for that task, the model is active and the cohort holds at least 10 comparable models. The capability column lists facts the source declares — supported formats, reasoning and tool parameters — which are not measured quality.
| Task | Grade | Source-declared capability |
|---|---|---|
| General quality | No measurement | reasoning: optional · default high · efforts: high, none · parameters: include_reasoning, reasoning, reasoning_effort |
| Coding | No measurement | — |
| Agents | No measurement | parameters: structured_outputs, tool_choice, tools |
| Writing | No measurement | output: text |
| Reasoning | No measurement | reasoning: optional · default high · efforts: high, none · parameters: include_reasoning, reasoning, reasoning_effort |
| Document analysis | No measurement | input: file |
| Vision | No measurement | input: image |
| Image generation | No measurement | — |
| Audio | No measurement | — |
| Video | No measurement | — |
| Embeddings | No measurement | — |
Evaluations
No evaluations are supplied for this model.
How grades work
Each letter grade compares a model only against other models scored by the same source and metric in the current snapshot. S means the top 10%, A the next 20%, B the next 30%, C the rest. Models without a published measurement are shown as not rated — a supported format alone never implies measured quality.
- S — S — top 10% of the cohort
- A — A — next 20% of the cohort
- B — B — next 30% of the cohort
- C — C — below the B band
Providers
Optional live provider statistics from OpenRouter. Missing values are unknown, not zero.
| Provider | Context length | Price in /1M | Price out /1M | Latency p50 (30m, s) | Throughput p50 (30m, tok/s) | Uptime (30m) |
|---|---|---|---|---|---|---|
| Sakana AI | 262,144 | $0.950 | $4 | — | — | — |
Provider data retrieved: 13.11.2026
Related articles
No published articles identify this model yet.