Compare models
Put up to 4 models beside each other — token prices, context windows, capabilities and provider, from the same catalogue the model pages read.
| Attribute | Fugu Ultrafugu-ultra | Gemini 3.1 Flash Lite Image (Google Vertex AI)gemini-3.1-flash-lite-image-vertex | Gemini 4 Argongemini-4-argon |
|---|---|---|---|
| Pricing | |||
| Input | $5.00 / 1M | — | $2.00 / 1M |
| Output | $30.00 / 1M | — | $10.00 / 1M |
| Cache Write (5m) | $5.00 / 1M | Not applicable | $2.00 / 1M |
| Cache Write (1h) | $5.00 / 1M | Not applicable | $2.00 / 1M |
| Cache Read | $5.00 / 1M | Not applicable | $2.00 / 1M |
| Web Search | $0 / 1M | — | $0 / 1M |
| Request | — | $0.0336 / request | — |
| Billing | — | Pay Per Request | — |
| Context | |||
| Max context | 1M | N/A | 1M |
| Max output | N/A | N/A | N/A |
| Capabilities | |||
| Vision | Yes | Yes | Yes |
| Function Calling | Yes | No | Yes |
| JSON Mode | Yes | No | Yes |
| Streaming | Yes | No | Yes |
| Catalogue | |||
| Provider | Sakana | ||
| Category | chat | image | chat |
| Charge type | Pay As You Go | Pay Per Request | Pay As You Go |
| Released | — | — | — |
| Description | |||
| Summary | Fugu Ultra is the high-performance model in Sakana AI's Fugu family, built as a learned multi-agent orchestration system rather than a single monolithic model. It intelligently routes tasks across a pool of underlying models and can recursively invoke itself to solve complex problems more effectively. Optimized for multi-step reasoning, coding, and agentic workflows, Fugu Ultra supports configurable reasoning effort, native tool calling, and built-in web search. Its orchestration-based design makes it well suited for advanced autonomous agents and complex task execution requiring adaptive model coordination. | Gemini 3.1 Flash Lite Image served from Google Vertex AI. Billed per image at US$0.0336. Call it through /v1/chat/completions with stream set to false; the image is returned in the message content as a base64 data URI. Maximum output resolution is 1K. A request for a larger size returns a 1K image with the same aspect ratio at the same price. When a size is reduced, the response carries an X-Image-Resolution-Capped header with the requested and delivered size. | Gemini 4 Argon is Google's flagship reasoning model, built for complex software engineering, deep mathematical and scientific problem solving, and autonomous multi-step agents. Google trained it to keep context across long, multi-step tasks and to turn long documents mixing text, tables, charts and images into a single grounded output. It leads the Vals Index across finance, legal, coding and tax work, and supports long decode of up to 1M output tokens in a single response. |