sakana
Sakana: Fugu Ultra v2
sakana/fugu-ultra-v2
Our take
AI-assisted analysis based on the sources below. Suitability is an editorial assessment; test it on your own workload.
OpenRouter’s catalog entry for sakana/fugu-ultra-v2 describes Sakana AI’s higher-performance Fugu model as a learned multi-agent orchestration system rather than a single monolithic model. The listing reports text, image, and file inputs with text output, a very large context window, mandatory reasoning at a high default effort, and API options for tools, structured responses, and web search. No independent model card was available in this source pack, and the catalog’s benchmark fields are empty, so performance remains unverified here.[1]
Strengths
Limitations
Where to use it
- Consider evaluating it for long-context document or file-analysis workflows that return text.[1]
- Potentially suitable for agent-style tasks where mandatory reasoning and tool options are desirable; validate on your workload.[1]
- Worth testing where structured outputs or optional web search are required.[1]
Sources
- [1] OpenRouter catalog · Sakana: Fugu Ultra v2Sources checked: Nov 13, 2026
About this model
Description below is the original text supplied by OpenRouter, shown in the source language.
Fugu Ultra v2 is the higher-performance model in Sakana AI's Fugu family. Rather than a single monolithic model, Fugu is a learned multi-agent orchestration system: a language model trained to...
Specifications
- Model ID
- sakana/fugu-ultra-v2
- Canonical ID
- sakana/fugu-ultra-v2-20260911
- Creator
- sakana
- Added to OpenRouter
- 11.09.2026
- Context length
- 1,000,000
- Modality
- text+image+file->text
- Input modalities
- text, image, file
- Output modalities
- text
- Token pricing
- USD per 1M tokens: in $5 / out $30
- Knowledge cutoff
- 28.08.2026
- 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: mandatory · default xhigh · efforts: max, xhigh, high · 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: mandatory · default xhigh · efforts: max, xhigh, high · 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 | 1,000,000 | $5 | $30 | — | — | — |
Provider data retrieved: 13.11.2026
Related articles
No published articles identify this model yet.