Hermes MoA vs Fugu Ultra

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, side by side, on 42 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 · Dispatched from Agent OS as the panel-ensemble alternative to OpenRouter Fusion. Bench scored by Claude judge against the same 42 prompts as every other model.

Where Hermes MoA beat Fugu Ultra

The tasks where I gave Hermes MoA a higher 0–10 score on the same prompt — with the actual commentary from my source guides.

Where Fugu Ultra beat Hermes MoA

The tasks where I gave Fugu Ultra a higher 0–10 score on the same prompt — with the actual commentary from my source guides.

Strengths & weaknesses I logged

Pricing & context — the spec sheet

The verdict — which should you pick?

Across 42 scored shared tasks, Hermes MoA averaged 8.38/10, beating Fugu Ultra's 7.94/10 by 0.44 points. Pick Hermes MoA when the build has to ship on the first prompt and you can afford the trade-offs in the comparison below.

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 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, teams that want fusion-class quality but need a different vendor risk profile → Fugu Ultra. That's the same setup I run for the 3,600+ founders inside the AI Profit Boardroom.

FAQ — Hermes MoA vs Fugu Ultra

Which is better, Hermes MoA or Fugu Ultra?

On Goldie Bench, Hermes MoA averages 8.38/10 across the shared tasks, with 12 gold, 8 silver, 4 bronze overall. Fugu Ultra averages 7.94/10, with 8 gold, 8 silver, 8 bronze. Hermes MoA wins the head-to-head 27–15.

How much does Hermes MoA cost vs Fugu Ultra?

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: Sakana's multi-agent orchestration: a single API call internally dispatches to multiple frontier models and synthesises the answer. Subscription plans run $20-$200/mo (Standard / Pro / Max); PAYG is $5/M input + $30/M output for Fugu Ultra. Direct competitor to OpenRouter Fusion's panel approach.

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

Hermes MoA has a Varies — the sum of the panel models' contexts (Opus 4.8 + GPT-5.5) context window. Fugu Ultra has a 272,000 tokens with the standard rate. Calls exceeding 272K context are billed at the higher 'long-context' rates. context window.

When should I pick Hermes MoA over Fugu Ultra?

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 over Hermes MoA?

Pick Fugu Ultra for: Teams that want Fusion-class quality but need a different vendor risk profile; Operators avoiding export-controlled providers (Sakana emphasises this in their pitch); Deep-research workflows where ensemble verdicts beat single-model answers. The trade-off is the weaknesses we logged on the bench: Panel orchestration adds latency — even a 'pong' burns ~2k orchestration tokens; Newer than Fusion; less community calibration on long-tail prompts.

How does Goldie Bench score Hermes MoA vs Fugu Ultra?

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 · back to the leaderboard