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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.

  1. Fugu UltraSakanaRemove
  2. Gemini 3.8 FlashGoogleRemove
  3. Hy4 previewTencentRemove
  4. Muse Spark 1.3MetaRemove

4 is the maximum. Remove one to add another.

fugu-ultra vs gemini-3.8-flash vs hy4-preview vs muse-spark-1.3
AttributeFugu Ultrafugu-ultraGemini 3.8 Flashgemini-3.8-flashHy4 previewhy4-previewMuse Spark 1.3muse-spark-1.3
Pricing
Input$5.00 / 1M$0.75 / 1M$0.834 / 1M$1.25 / 1M
Output$30.00 / 1M$3.75 / 1M$2.50 / 1M$4.25 / 1M
Cache Write (5m)$5.00 / 1M$0.75 / 1M$0.834 / 1M$1.25 / 1M
Cache Write (1h)$5.00 / 1M$0.75 / 1M$0.834 / 1M$1.25 / 1M
Cache Read$5.00 / 1M$0.75 / 1M$0.834 / 1M$1.25 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M$0 / 1M
Context
Max context1M1M1M1M
Max outputN/AN/AN/AN/A
Capabilities
VisionYesYesYesYes
Function CallingYesYesYesYes
JSON ModeYesYesYesYes
StreamingYesYesYesYes
Catalogue
ProviderSakanaGoogleTencentMeta
Categorychatchatchatchat
Charge typePay As You GoPay As You GoPay As You GoPay As You Go
Released
Description
SummaryFugu 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 3.8 Flash is Google's most intelligent Flash-class model, delivering significant improvements over Gemini 3.7 Flash across software engineering, agentic workflows, and complex multi-step reasoning. Designed to combine strong capability with Flash-tier efficiency, it is well suited for coding assistants, autonomous agents, and high-throughput production workflows that require responsive performance without sacrificing reasoning quality.Tencent Hy4 Preview is a Mixture-of-Experts (MoE) model from Tencent, featuring 770B total parameters with 49B activated per token. It is designed for coding agents, complex tool-driven workflows, and professional productivity tasks that require strong planning and reliable execution. Optimized for context continuity and sustained multi-step work, Hy4 Preview is well suited for long-horizon coding, agentic automation, tool orchestration, and complex real-world workflows.Muse Spark 1.3 is Meta's multimodal reasoning model designed for long-running agentic, multi-agent, and coding workflows. It maintains context and information across extended tasks, enabling reliable execution in complex, multi-step environments. The model is optimized to resolve conflicting information, seek clarification or confirmation when necessary, and execute concisely, making it well suited for autonomous agents, collaborative multi-agent systems, and long-horizon software engineering workflows.