
Real head-to-head · same prompt, one shot
Claude Sonnet 5 vs Fugu Ultra 1.1
The agentic SWE frontier — 82% SWE-bench Verified, Dev Team mode. 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 Claude Sonnet 5 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.
Claude Sonnet 5 · Reach for it in Agent OS when the job is iterative, tool-using software engineering. For one-shot visual builds, GLM 5.2 (free) beat it 4-1 here.
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 = 🥉).
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Strengths & weaknesses I logged
Claude Sonnet 5
Strengths
- 82.1% SWE-bench Verified — first model past 80% on real GitHub-issue repair
- Dev Team multi-agent mode + 1M context for repo-level agentic work
- Precision on hard logic — won the raycaster the open-weight field kept botching
Trade-offs
- One-shot creative-visual builds trail GLM 5.2 here (lost 4 of 5) — no iteration to catch its own bugs
- A temporal-dead-zone bug blanked its N-body orbit sim on the first shot
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 | Claude Sonnet 5 | Fugu Ultra 1.1 |
|---|---|---|
| Vendor | Anthropic | Sakana AI |
| Context window | 1,000,000 tokens | 1,000,000-token context window |
| Price | $3 / $15 per M ($2/$10 intro) | API · orchestration billed |
| Pricing detail | $3.00 input / $15.00 output per million tokens; introductory $2.00/$10.00 through 2026-08-31. | 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 | 2026-06-30 | 2026-07 |
| Bench coverage | 47/47 scored · avg 7.01/10 | 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 Claude Sonnet 5 and Fugu Ultra 1.1 both into the Agent Operating System and dispatch each from the kanban by task type — agentic software engineering — write / run / test / fix loops on real repos → Claude Sonnet 5, 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 — Claude Sonnet 5 vs Fugu Ultra 1.1
Which is better, Claude Sonnet 5 or Fugu Ultra 1.1?
On Goldie Bench, Claude Sonnet 5 averages no scored verdicts yet across the shared tasks, with 0 gold, 2 silver, 2 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 Claude Sonnet 5 cost vs Fugu Ultra 1.1?
Claude Sonnet 5: $3.00 input / $15.00 output per million tokens; introductory $2.00/$10.00 through 2026-08-31. 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 Claude Sonnet 5 vs Fugu Ultra 1.1?
Claude Sonnet 5 has a 1,000,000 tokens context window. Fugu Ultra 1.1 has a 1,000,000-token context window context window.
When should I pick Claude Sonnet 5 over Fugu Ultra 1.1?
Pick Claude Sonnet 5 for: Agentic software engineering — write / run / test / fix loops on real repos; Repo-level reasoning across a 1M-token context (Dev Team multi-agent mode); Precise logic — raycasters, physics — where one-shot open models slip. The trade-off is the weaknesses we logged on the bench: One-shot creative-visual builds trail GLM 5.2 here (lost 4 of 5) — no iteration to catch its own bugs; A temporal-dead-zone bug blanked its N-body orbit sim on the first shot.
When should I pick Fugu Ultra 1.1 over Claude Sonnet 5?
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 Claude Sonnet 5 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:
Claude Sonnet 5 vs Fusion Fugu Ultra 1.1 vs Fusion Claude Sonnet 5 vs Hermes MoA Fugu Ultra 1.1 vs Hermes MoA Claude Sonnet 5 vs GPT-5.6 Sol Fugu Ultra 1.1 vs GPT-5.6 Sol Claude Sonnet 5 vs Claude Fable 5 Fugu Ultra 1.1 vs Claude Fable 5Full model pages: Claude Sonnet 5 · Fugu Ultra 1.1 · back to the leaderboard
The same stack Julian uses
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.
4,000+founders
258documented wins
38countries
$59/momonthly






















