@rohanpaul_ai: Sakana Fugu Ultra just beat the other models on visual polish in a live trading-desk coding test, got close to GLM 5.2,…
Summary
Sakana's Fugu Ultra model orchestration system outperformed other models in a live coding test for a trading desk UI, though at 17x higher cost, demonstrating its strength in visual polish and multi-agent coordination.
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Cached at: 06/23/26, 09:47 AM
Sakana Fugu Ultra just beat the other models on visual polish in a live trading-desk coding test, got close to GLM 5.2, but at 17x the cost.
Test was done on atomic[.]chat, a desktop app that runs LLMs locally.
Fugu produced the richest interface, with multiple panels, watchlists, charts, tape-style activity, status labels, and a more finished product feel.
To note that Fugu Ultra is an orchestration layer that assembles and routes subtasks across a pool of models through one OpenAI-compatible endpoint.
So Fugu is a learned coordinator model inside a multi-agent system.
When you send a prompt, Fugu decides whether to answer alone or hand pieces of the job to other models, then it gathers the outputs and produces one final response.
atomic.chat (@atomic_chat_hq): Sakana Fugu surprisingly performed near GLM 5.2 level but 17× more expensive!
We gave the same prompt to 4 models: build a complete live Trader Desk with both frontend and backend components, real-time market data fetched from external APIs for 8 symbols, and a custom dark-theme
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