Opus 4.8 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 Opus 4.8 and Fugu Ultra, side by side, on 5 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.

Opus 4.8 · The default when the build has to ship on the first prompt — Opus is the safety net inside Agent OS for hard one-shots.

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 Opus 4.8 beat Fugu Ultra

The tasks where I gave Opus 4.8 a higher 0–10 score on the same prompt — with the actual commentary from my source guides.

Where Fugu Ultra beat Opus 4.8

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 5 scored shared tasks, Opus 4.8 averaged 8.60/10, beating Fugu Ultra's 7.60/10 by 1.00 points. Pick Opus 4.8 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 Opus 4.8 and Fugu Ultra both into the Agent Operating System and dispatch each from the kanban by task type — mission-critical one-shot builds where 'has to work the first time' matters → Opus 4.8, 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 — Opus 4.8 vs Fugu Ultra

Which is better, Opus 4.8 or Fugu Ultra?

On Goldie Bench, Opus 4.8 averages 8.60/10 across the shared tasks, with 7 gold, 3 silver, 1 bronze overall. Fugu Ultra averages 7.60/10, with 3 gold, 1 silver, 0 bronze. Opus 4.8 wins the head-to-head 2–1.

How much does Opus 4.8 cost vs Fugu Ultra?

Opus 4.8: Premium pricing via the Anthropic API: $15 per million input tokens, $75 per million output tokens. Extended thinking is included but adds latency. 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 Opus 4.8 vs Fugu Ultra?

Opus 4.8 has a 200,000 tokens (1M with extended thinking) 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 Opus 4.8 over Fugu Ultra?

Pick Opus 4.8 for: Mission-critical one-shot builds where 'has to work the first time' matters; Hard reasoning tasks (planning, multi-step) where you'll pay for the depth; Anything where vendor reliability beats the per-token bill. The trade-off is the weaknesses we logged on the bench: 5–10× the per-token cost of every other model on the bench; Less flair on cinematic visuals than GLM-5.2 — playing it safer wins on accuracy, costs you on showpiece moments.

When should I pick Fugu Ultra over Opus 4.8?

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 Opus 4.8 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: Opus 4.8 · Fugu Ultra · back to the leaderboard