AI model comparison

Fugu vs Grok 4.5

Compare pricing, context limits, supported inputs and deployment options to choose a model for your workflow.

Fugu from Sakana AI lists 1M context. Grok 4.5 from xAI lists 500K context, 500K maximum output, $2.00 input per 1M tokens, $6.00 output per 1M tokens. Compare the inputs, outputs and deployment options below to see which fits your workflow.

Side-by-sideCapabilities and practical differences

Sakana AI

Fugu

Fugu from Sakana AI: Multi-agent model for routing expert agents across complex analytical tasks.

Context
1M

Accepts

  • Text input
  • Image input

Produces

  • Text output
VS

xAI

Grok 4.5

Grok 4.5 from xAI: xAI's Grok model for chat, coding, agentic tools, and lower hallucination risk.

Context
500K
Max output
500K
Input / 1M tokens
$2.00
Output / 1M tokens
$6.00

Accepts

  • Text input
  • Image input

Produces

  • Text output

At a glance

Key differences

Compare the available figures below, then try both models on the work you need to do.

Fugu

  • Context capacity: 1M

Context capacity

Higher listed limit

Fugu:1M

Grok 4.5:500K

Fugu

Specifications

Pricing, limits and capabilities

Specifications for Fugu and Grok 4.5. Higher limits and lower prices describe these figures only.
SpecificationFuguGrok 4.5
ProviderSakana AIxAI
Listed pricing routeSakana AIxAI
Model familyfugugrok
Accepted inputstext, imagetext, image
Produced outputstexttext
Context window1MHigher500K
Max output—500K
Input price / 1M—$2.00
Output price / 1M—$6.00
Reasoning modeDocumentedDocumented
Tool callingDocumentedDocumented
Image inputDocumentedDocumented
Audio inputNot documentedNot documented
Structured outputDocumentedDocumented
LicenseProprietaryProprietary

Workload guidance

Which model should you choose?

Consider Fugu if you need larger context. Test both on the same representative examples and judge the output against your acceptance criteria. Include tool failures, retries and the time to a completed task.

Documentation and model profiles

Explore each model’s features, API requirements and licence terms in the sources below.

Questions people ask

It brings together documented inputs and outputs, token limits, deployment terms and available pricing. When both models have source-linked, verified results on a shared benchmark, those results are shown with their individual sources. The comparison is a starting point for evaluating your own workload.

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