
Fusion vs Fugu Ultra 1.1
Multi-model panel — Fable 5 + GPT-5.5, ensembled. Beats Fable 5 at half the price. vs Sakana's multi-agent orchestrator, v1.1 — routes experts per request.
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 Fusion 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.
Fusion · Dispatched from Agent OS for research-heavy prompts where ensemble accuracy outweighs single-model speed.
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.
Side-by-side on 47 shared tasks
Click any cell to play that model's actual one-shot attempt. Medals are derived from my 0–10 scores per task (highest = 🥇, second = 🥈, third = 🥉).
Strengths & weaknesses I logged
Fusion
Strengths
- Premium Fusion panel scored 69.0% on DRACO deep-research benchmark — beats solo Fable 5 by +3.7 points
- Budget panel ties Fable 5 at ~64.7% for roughly half the cost
- Vendor-agnostic — model panel can swap as new frontier releases land
Trade-offs
- Ensemble latency higher than any single model (panel calls run in parallel but the slowest still gates the response)
- No per-task goldiebench scoring yet — bench rank pending
Fugu Ultra 1.1
Strengths
- Orchestrates 1-3 expert agents per request and synthesises their answers
- Reported SWE-Bench Pro 73.7 — above Opus 4.8 and GPT-5.5 on Sakana's table
- OpenAI- and Anthropic-compatible API — drop-in for Codex and Claude Code
Trade-offs
- 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
Pricing & context — the spec sheet
| Spec | Fusion | Fugu Ultra 1.1 |
|---|---|---|
| Vendor | OpenRouter | Sakana AI |
| Context window | Varies — depends on which panel models are dispatched | 1,000,000-token context window |
| Price | OpenRouter Fusion API pricing | API · orchestration billed |
| Pricing detail | OpenRouter's Fusion API dispatches a single prompt to multiple frontier models and ensembles the answers. Premium panel: Fable 5 + GPT-5.5. Budget panel: cheaper open-weights models. Roughly half the per-token cost of a Fable 5 solo call. | 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. |
| Release | 2026-06-14 | 2026-07 |
| Bench coverage | 47/47 scored · avg 8.59/10 | 0/0 scored · avg — |
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 Fusion and Fugu Ultra 1.1 both into the Agent Operating System and dispatch each from the kanban by task type — deep-research workflows where panel consensus beats single-model answers → Fusion, 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 — Fusion vs Fugu Ultra 1.1
Which is better, Fusion or Fugu Ultra 1.1?
On Goldie Bench, Fusion averages no scored verdicts yet across the shared tasks, with 22 gold, 2 silver, 6 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 Fusion cost vs Fugu Ultra 1.1?
Fusion: OpenRouter's Fusion API dispatches a single prompt to multiple frontier models and ensembles the answers. Premium panel: Fable 5 + GPT-5.5. Budget panel: cheaper open-weights models. Roughly half the per-token cost of a Fable 5 solo call. 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 Fusion vs Fugu Ultra 1.1?
Fusion has a Varies — depends on which panel models are dispatched context window. Fugu Ultra 1.1 has a 1,000,000-token context window context window.
When should I pick Fusion over Fugu Ultra 1.1?
Pick Fusion for: Deep-research workflows where panel consensus beats single-model answers; Cost-sensitive operators who want Fable-5-class output at ~half the bill; Production agents that benefit from vendor-redundancy on every call. The trade-off is the weaknesses we logged on the bench: Ensemble latency higher than any single model (panel calls run in parallel but the slowest still gates the response); No per-task goldiebench scoring yet — bench rank pending.
When should I pick Fugu Ultra 1.1 over Fusion?
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 Fusion 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:
Fusion vs Hermes MoA Fugu Ultra 1.1 vs Hermes MoA Fusion vs GPT-5.6 Sol Fugu Ultra 1.1 vs GPT-5.6 Sol Fusion vs Claude Fable 5 Fugu Ultra 1.1 vs Claude Fable 5 Fusion vs Qwen 3.8 Fugu Ultra 1.1 vs Qwen 3.8Full model pages: Fusion · Fugu Ultra 1.1 · back to the leaderboard
Run this stack yourself.
Every demo on this bench was built inside the Agent Operating System — one prompt, one shot, single HTML file out. The Agent OS, the prompts, the templates, the weekly walkthroughs and 4,000+ founders shipping with it every day all live inside the AI Profit Boardroom.






















