
Real head-to-head · same prompt, one shot
Fugu Mini vs Kilo Code
Fugu's fast mini variant — single model, no panel, ~3 min per build. vs Fable 5-class intelligence at ~59% less. The split-the-cost play.
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 Fugu Mini and Kilo Code, 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.
Fugu Mini · Dispatched from Agent OS as the fast Sakana lane. Bench scored by Claude judge against the same 42 prompts.
Kilo Code · Used inside Agent OS as a routing layer: Fable 5 generates the plan, cheaper models execute. Bench scoring pending a head-to-head comparison.
Side-by-side on 26 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 = 🥉).
Task ↓
Fugu Mini
Kilo Code
Game
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Visual
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Strengths & weaknesses I logged
Fugu Mini
Strengths
- Zero panel orchestration — much lower latency than Ultra
- Same Sakana subscription, no extra cost
- Doesn't time out on heavy game/3D prompts where Ultra stalls
Trade-offs
- Single model only — no ensemble verdict
- Newer than Ultra — less calibration / verification
Kilo Code
Strengths
- Kilo's own rubric: Fable 5 plan = 9.1/10, GPT-5.5 plan = 8.3/10 — Kilo isolates where the intelligence actually lives
- Plan quality stays high while execution cost drops
- Drop-in for Agent OS — Kilo Split framework already wired
Trade-offs
- Adds routing complexity — two model providers in one workflow
- No per-task goldiebench head-to-heads yet
Pricing & context — the spec sheet
| Spec | Fugu Mini | Kilo Code |
|---|---|---|
| Vendor | Sakana AI | Kilo |
| Context window | Single-model variant of Sakana's Fugu — no panel orchestration. Same API endpoint, much faster per call. | Varies — Kilo splits planning from execution across multiple models |
| Price | Same Sakana subscription pool as Fugu Ultra | ~59% less than Fable 5 solo |
| Pricing detail | The non-Ultra `fugu` model on Sakana's API. Sakana describes it as 'Fast mini model optimized for low latency yet high quality responses.' Crucially: zero orchestration tokens per call (vs Ultra's panel of thousands). Returns in ~3 min instead of 6-15 min and doesn't time out on heavy prompts. | Kilo Code is a routing layer that splits planning (heavy model) from execution (cheaper model) so you get Fable-5-class plans driving GPT-5.5-class builds. Total spend lands at ~59% less than running Fable 5 end-to-end. |
| Release | 2026-06-15 | 2026-06-16 |
| Bench coverage | 2/26 scored · avg 5.50/10 | 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 Fugu Mini and Kilo Code both into the Agent Operating System and dispatch each from the kanban by task type — agent loops where latency matters more than panel consensus → Fugu Mini, cost-conscious operators who run high-volume agent loops → Kilo Code. That's the same setup I run for the 3,600+ founders inside the AI Profit Boardroom.
FAQ — Fugu Mini vs Kilo Code
Which is better, Fugu Mini or Kilo Code?
On Goldie Bench, Fugu Mini averages no scored verdicts yet across the shared tasks, with 0 gold, 0 silver, 0 bronze overall. Kilo Code 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 Fugu Mini cost vs Kilo Code?
Fugu Mini: The non-Ultra `fugu` model on Sakana's API. Sakana describes it as 'Fast mini model optimized for low latency yet high quality responses.' Crucially: zero orchestration tokens per call (vs Ultra's panel of thousands). Returns in ~3 min instead of 6-15 min and doesn't time out on heavy prompts. Kilo Code: Kilo Code is a routing layer that splits planning (heavy model) from execution (cheaper model) so you get Fable-5-class plans driving GPT-5.5-class builds. Total spend lands at ~59% less than running Fable 5 end-to-end.
What's the context window for Fugu Mini vs Kilo Code?
Fugu Mini has a Single-model variant of Sakana's Fugu — no panel orchestration. Same API endpoint, much faster per call. context window. Kilo Code has a Varies — Kilo splits planning from execution across multiple models context window.
When should I pick Fugu Mini over Kilo Code?
Pick Fugu Mini for: Agent loops where latency matters more than panel consensus; Quick first-drafts you'll refine downstream; Filling out a bench when Ultra is timing out. The trade-off is the weaknesses we logged on the bench: Single model only — no ensemble verdict; Newer than Ultra — less calibration / verification.
When should I pick Kilo Code over Fugu Mini?
Pick Kilo Code for: Cost-conscious operators who run high-volume agent loops; Multi-step workflows where the plan is the expensive part; Teams already paying for Fable 5 who want to keep the plan but drop the execution bill. The trade-off is the weaknesses we logged on the bench: Adds routing complexity — two model providers in one workflow; No per-task goldiebench head-to-heads yet.
How does Goldie Bench score Fugu Mini vs Kilo Code?
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:
Fugu Mini vs Fusion Kilo Code vs Fusion Fugu Mini vs Opus 4.8 Kilo Code vs Opus 4.8 Fugu Mini vs GLM-5.2 Kilo Code vs GLM-5.2 Fugu Mini vs Grok Kilo Code vs GrokFull model pages: Fugu Mini · Kilo Code · 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 3,600+ founders shipping with it every day all live inside the AI Profit Boardroom.
3,600+founders
258documented wins
38countries
$100k+/mocommunity MRR





















