Fugu Ultra v1.1 vs Fugu Ultra v1.0

Fugu Ultra v1.1 and Fugu Ultra v1.0 side by side: specs, capabilities, parameters, and live pricing from the EmpirioLabs catalog.

Sakana AI Text Generation

Fugu Ultra v1.1 vs Fugu Ultra v1.0 at a glance

Fugu Ultra v1.1 and Fugu Ultra v1.0 are both Sakana AI models in the Text Generation category, available through the EmpirioLabs API.

Key differences

  • Fugu Ultra v1.1 is the newer release (Jul 23, 2026); Fugu Ultra v1.0 was released on Jun 21, 2026.
  • Both models have a context window of 1M tokens.

Fugu Ultra v1.1 vs Fugu Ultra v1.0: specs

SpecFugu Ultra v1.1Fugu Ultra v1.0
Model IDfugu-ultra-v1-1fugu-ultra-v1-0
AuthorSakana AISakana AI
ReleasedJul 23, 2026Jun 21, 2026
Context window1M tokens1M tokens
Max output131,072 tokens131,072 tokens
Input
Text Image
Text Image
Output
Text
Text
Structured outputJSON SchemaJSON Mode
Endpoints
POST /v1/chat/completions POST /v1/responses POST /v1/messages POST /v1beta/models/fugu-ultra-v1-1:generateContent
POST /v1/chat/completions POST /v1/responses POST /v1/messages POST /v1beta/models/fugu-ultra-v1-0:generateContent
Capabilities
reasoning multimodal web search function calling agentic coding cache
reasoning multimodal web search function calling agentic coding cache

Fugu Ultra v1.1 vs Fugu Ultra v1.0: API pricing

Live rates from the EmpirioLabs catalog for both models. Each rate card always matches what the API charges.

Fugu Ultra v1.1 vs Fugu Ultra v1.0: API parameters

Request parameters each model lists on EmpirioLabs, with the allowed values or range where one applies. A dash marks a parameter the model does not list.

ParameterFugu Ultra v1.1Fugu Ultra v1.0
max_tokens16 to 13107216 to 131072
reasoning_efforthigh, xhigh, max Default: highhigh, xhigh, max Default: high
tool_web_searchboolean Default: falseboolean Default: false
toolsarray Default: []array Default: []
tool_choiceobjectobject
response_formatenumenum

Fugu Ultra v1.1 vs Fugu Ultra v1.0: limits and notes

Fugu Ultra v1.1

Fugu Ultra v1.1 is an updated multi-agent conductor: each request coordinates a pool of expert models and composes their work into a single answer.

Latency and streaming

  • Responses can take from a few seconds to a few minutes on complex prompts.
  • The full answer is returned all at once when the model finishes, not token by token. Streaming is accepted, but it delivers the complete response at the end rather than streaming tokens as they generate.
  • max_tokens must be at least 16. Leave generous headroom, since very small limits can truncate or empty the answer.

Capabilities

  • Text and image input, with a 1M token context.
  • Always-on reasoning with high, xhigh, and a distinct max level for the hardest problems.
  • Function calling, strict JSON Schema structured output, and built-in web search that cites its sources when available (no separate fee).

Versioning

  • Use fugu-ultra-v1-1 for v1.1. The legacy fugu-ultra id remains pinned to v1.0 for backward compatibility.

Billing

  • Billed on full token usage, including the orchestration tokens the model uses internally, so even short prompts carry some cost.
  • Context-tiered: requests above 272K total input tokens use the higher rate shown.

Fugu Ultra v1.0

Fugu Ultra v1.0 is the original multi-agent conductor: each request coordinates a pool of expert models and composes their work into a single answer.

Latency and streaming

  • Responses can take from a few seconds to a few minutes on complex prompts.
  • The full answer is returned all at once when the model finishes, not token by token. Streaming is accepted, but it delivers the complete response at the end rather than streaming tokens as they generate.
  • max_tokens must be at least 16. Leave generous headroom, since very small limits can truncate or empty the answer.

Capabilities

  • Text and image input, with a 1M token context.
  • Always-on reasoning. high is the default; xhigh and max are aliases of the same maximum effort.
  • Function calling, JSON mode, and built-in web search that cites its sources when available (no separate fee).

Compatibility

  • The legacy fugu-ultra, fugu-ultra-20260615, and sakana/fugu-ultra ids remain pinned to this version.

Billing

  • Billed on full token usage, including the orchestration tokens the model uses internally, so even short prompts carry some cost.
  • Context-tiered: requests above 272K total input tokens use the higher rate shown.

How to call Fugu Ultra v1.1 and Fugu Ultra v1.0

Fugu Ultra v1.1 serves the OpenAI-compatible Chat Completions API. Point any OpenAI SDK at https://api.empiriolabs.ai/v1 with your EmpirioLabs API key and use the model id fugu-ultra-v1-1. Both models are called through the same endpoint. Set model to fugu-ultra-v1-1 or fugu-ultra-v1-0. Get an API key from the EmpirioLabs dashboard.

cURL
curl https://api.empiriolabs.ai/v1/chat/completions \
  -H "Authorization: Bearer $EMPIRIOLABS_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "fugu-ultra-v1-1",
    "messages": [
      {"role": "user", "content": "Write a haiku about the ocean."}
    ]
  }'

Fugu Ultra v1.1 vs Fugu Ultra v1.0: common questions

What is the difference between Fugu Ultra v1.1 and Fugu Ultra v1.0?

Fugu Ultra v1.1 is the newer release (Jul 23, 2026); Fugu Ultra v1.0 was released on Jun 21, 2026. Both models have a context window of 1M tokens. The specs, rate cards, and parameters on this page come from the live EmpirioLabs catalog.

Which is newer, Fugu Ultra v1.1 or Fugu Ultra v1.0?

Fugu Ultra v1.1 is the newer release (Jul 23, 2026); Fugu Ultra v1.0 was released on Jun 21, 2026.

Which has the lower rate, Fugu Ultra v1.1 or Fugu Ultra v1.0?

The two models are priced on different units or tiers, so compare the live rate cards on this page. They always match what the API charges.

Can I switch between Fugu Ultra v1.1 and Fugu Ultra v1.0 without rebuilding my integration?

Yes. Both models use POST /v1/chat/completions with the same EmpirioLabs API key, so most integrations switch by changing the model value. Check the parameters table on this page first if you rely on a model-specific parameter.

Can I try Fugu Ultra v1.1 and Fugu Ultra v1.0 in the browser before integrating?

Yes. Open each model in the EmpirioLabs playground and run the same prompt on both, with the parameters the API exposes.

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