Hermes MoA vs Fugu Ultra 1.1

What I tested — same prompt, two models

I run the same fixed prompt set through every new model the day it drops — same string, one shot, single HTML file out — and I score the result 0–10 on whether it ran, how close it hit the brief, and how good it looked. Below is what came out when I gave the exact same prompts to Hermes MoA and Fugu Ultra 1.1, side by side, on 0 shared tasks inside the Agent Operating System.

Both models were given identical prompts inside the Agent Operating System — no help, no iteration, no "best of N" tricks. I run each prompt once, save the HTML file the model produces, and score it 0–10 on whether it ran, how close it hit the brief, and how good it looked. The scoring is mine. The verdicts below are pulled from my source comparison guides at agentos.guide where I publish every score and the reasoning behind it.

Hermes MoA · Run from the Mixture tab in the Hermes Agent OS. On this bench the panel built each demo and the aggregator merged the best of every draft.

Fugu Ultra 1.1 · Benched on GoldieBench via Sakana's Responses API (fugu-ultra-v1.1, xhigh reasoning). Game tasks use the skill-infused threejs-game-director prompt plus a controls+graphics fix loop with an anti-regression clamp, judged on a real mid-play frame by the same Opus judge as the field.

Strengths & weaknesses I logged

Pricing & context — the spec sheet

The verdict — which should you pick?

Not enough scored shared tasks yet for a head-to-head average. The live demos for both are on the matrix above — play them and form your own opinion.

If you only run one of these inside your stack, the head-to-head average above is the call. If you can run both, my honest play is to wire Hermes MoA and Fugu Ultra 1.1 both into the Agent Operating System and dispatch each from the kanban by task type — high-stakes single prompts where ensemble quality beats single-model speed → Hermes MoA, hard, high-stakes coding and reasoning where answer quality beats latency → Fugu Ultra 1.1. That's the same setup I run for the 4,000+ founders inside the AI Profit Boardroom.

FAQ — Hermes MoA vs Fugu Ultra 1.1

Which is better, Hermes MoA or Fugu Ultra 1.1?

On Goldie Bench, Hermes MoA averages no scored verdicts yet across the shared tasks, with 6 gold, 9 silver, 4 bronze overall. Fugu Ultra 1.1 averages no scored verdicts yet, with 0 gold, 0 silver, 0 bronze. Not enough scored shared tasks yet to call a winner.

How much does Hermes MoA cost vs Fugu Ultra 1.1?

Hermes MoA: Hermes Mixture of Agents dispatches one prompt to a configurable panel of frontier models in parallel, then a named aggregator reads every draft and writes one better final answer. Default panel: Claude Opus 4.8 + GPT-5.5, aggregated by Opus 4.8 — all via the OpenRouter key. Unlike a black-box ensemble, every slot is yours to swap from the Mixture tab in the Agent OS. Fugu Ultra 1.1: Sakana's Fugu Ultra v1.1 — a multi-agent system served as a model: an orchestrator routes each request across one to three expert agents and synthesises the answer. Reported (v1.0): SWE-Bench Pro 73.7, LiveCodeBench 93.2, GPQA Diamond 95.5. NOTE: Sakana geo-blocks the EU/EEA/UK/Switzerland pending GDPR compliance — benched from an allowed region.

What's the context window for Hermes MoA vs Fugu Ultra 1.1?

Hermes MoA has a Varies — the sum of the panel models' contexts (Opus 4.8 + GPT-5.5) context window. Fugu Ultra 1.1 has a 1,000,000-token context window context window.

When should I pick Hermes MoA over Fugu Ultra 1.1?

Pick Hermes MoA for: High-stakes single prompts where ensemble quality beats single-model speed; Squeezing frontier-plus output from models you already have while Fable 5 / GPT-5.6 are still in preview; Production agents that want a configurable panel + vendor-redundancy on every call. The trade-off is the weaknesses we logged on the bench: Latency is the panel's slowest draft plus the aggregator pass — ~110–140s per single-file build vs a solo model's one call; Costs more per task than any single model (every panel slot + the aggregator are separate calls); Only 3 of 42 bench tasks run so far — a representative slice, not the full board.

When should I pick Fugu Ultra 1.1 over Hermes MoA?

Pick Fugu Ultra 1.1 for: Hard, high-stakes coding and reasoning where answer quality beats latency; Agentic workflows in Codex / Claude Code via the drop-in provider config; One-shot builds you want a panel of experts on, not a single model. The trade-off is the weaknesses we logged on the bench: Benched as a partial run until the full 50-task batch completes; Region-locked: unavailable across the EU/EEA/UK/CH — access depends on where you are.

How does Goldie Bench score Hermes MoA vs Fugu Ultra 1.1?

Every demo on this page was built by Julian Goldie inside the Agent Operating System — same fixed prompt for both models, one shot, single HTML file out. Each result gets a 0–10 score on whether it ran, how close it hit the brief, and how good it looked. The highest score on each task gets gold; second gets silver; third gets bronze. See methodology for full provenance.

Related comparisons

Other head-to-heads using the same scoring system:

Full model pages: Hermes MoA · Fugu Ultra 1.1 · back to the leaderboard